Cantina is a new social platform founded by Sean Parker with the most advanced AI character creator. Our bots are lifelike, social creatures that can interact wherever people are online—across voice, video, and text. Create yourself, imagine someone new, or choose from thousands of characters to share infinitely scalable, personalized content and seamless group chat.
If you’re excited about how AI can shape creativity and social interaction, come help us build what’s next.
About the Role:
We’re looking for a Research / ML Engineer to join our Speech Team to build state-of-the-art speech systems end-to-end—from data specs through production inference. You’ll drive the model ↔ data ↔ eval flywheel for VC and adjacent tasks (controllable TTS, voice design and more), partnering closely with research, data, and infra to ship fast, reliable, and cost-aware models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems.
You will thrive in this role if you:
See research and engineering as two sides of the same coin and enjoy owning work end-to-end.
Are results-oriented, flexible, and willing to pick up whatever moves the needle.
Like collaborating closely with infra, data, and product to ship measurable improvements.
Enjoy designing experiments, listening tests, and metrics that correlate with user-perceived quality.
Eager to learn every-day, find and solve unique large-scale problems.
What You’ll Do:
Model Building: Architect, implement, pre-train, fine-tune, and post-train/alignment (e.g., GRPO/DPO) for large-scale speech models.
Experimental Design: Design, run, and analyze scientific experiments to advance our understanding of the models.
Tool Development: Develop and improve dev tooling to enhance team productivity.
Full-Stack Contribution: Contribute to the entire stack, from low-level optimizations to high-level model design.
Data Ownership: Define data requirements and collaborate on acquisition, curation, augmentation, labeling quality, and synthetic data strategies.
Pipeline Delivery: Harden the training → evaluation → inference pipeline; profile latency, memory, and cost; and meet production SLAs with robust monitoring and rollback.
Safety & Responsibility: Contribute to safety/consent guardrails and to misuse/abuse mitigation for responsible speech technology.
What You’ll Bring:
Exceptional research/development experience with large-scale audio models (>8B parameters, >500k hours of data).
Deep hands-on experience with diffusion and/or flow-matching transformers, including practical knowledge of samplers, schedules, conditioning mechanisms, and distillation.
Deep hands-on experience training audio VAEs, neural audio codecs, and vocoders latent/tokenizer design, reconstruction and perceptual objectives, adversarial training.
Strong experience with multi-node, multi-GPU distributed training (FSDP/DeepSpeed or equivalent).
Strong software engineering skills with a proven track record of building complex systems.
Strong with PyTorch and performance work (profiling, CUDA/Triton/C++ as needed) and writing reliable production-quality code.
Shipped large-scale speech/audio or multimodal generative models to production.
Background in working with large-scale ML data, and the ability to iterate on data and triangulate quality using both subjective and objective signals.
Experience with voice cloning, speech control/steerability, or expressive speech generation.
Notable publications and/or open-source contributions in speech/audio/ML.
Compensation:
The anticipated annual base salary range for this role is between $200,000-$220,000 (€170,000-€190,000). When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.
Benefits for U.S.-based roles:
Competitive salary and generous company equity
Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina
42 days of paid time off, including:
15 PTO days
10 sick days
15 company holidays
2 floating holidays
Generous parental leave & fertility support
401(k) retirement savings plan
Lifestyle spending account – $500/month to use however you’d like
Complimentary lunch and snacks for in-office employees
One Medical membership, and more!
Listed by Cantina for a position based in the United States. Employers on this board attest they are hiring domestically.
Machine Learning Engineer, Speech - Joint Audio-Video Modeling
Location
Remote (U.S. or Europe)
Employment Type
Full time
Department
Research
Overview
Application
About Cantina:
Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning.
If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future!
About the Role:
We're looking for a Research / ML Engineer to join our Speech Team to build state-of-the-art speech and audio generation systems end-to-end from data specs through production inference with a focus on joint audio-video modeling.
You'll own the audio side of multimodal generation: the representations (audio VAEs, neural codecs), the generative backbone (diffusion / flow-matching transformers), and the conditioning and alignment machinery that makes characters speak, sing, and emote in sync with what's on screen. That includes voice cloning and multi-speaker conditioning inside joint AV models, cinematic dialogue with music and sound design, and adjacent speech tasks (controllable TTS, voice conversion) that feed the same stack.
You'll drive the model ↔ data ↔ eval flywheel, partnering closely with research, video, data, and infra to ship fast, reliable, and cost-aware models. In this role you'll work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems.
You will thrive in this role if you:
See research and engineering as two sides of the same coin and enjoy owning work end-to-end.
Are excited to work across modalities and collaborate closely with a video generation team rather than staying inside audio.
Are results-oriented, flexible, and willing to pick up whatever moves the needle.
Like collaborating closely with infra, data, and product to ship measurable improvements.
Enjoy designing experiments, listening tests, and metrics that correlate with user-perceived quality.
Are eager to learn every day, and to find and solve unique large-scale problems.
What You’ll Do:
Audio Representations: Design, train, and improve the audio VAEs, neural codecs, and vocoders our generative models sit on top of latent design, reconstruction and perceptual objectives, compression-vs-fidelity tradeoffs.
Model Building: Architect, implement, pre-train, fine-tune, and post-train/alignment (e.g., GRPO/DPO) diffusion and flow-matching transformers for large-scale audio and video generation.
Joint Audio-Video Modeling: Design the audio conditioning and cross-modal alignment inside joint AV models, audio latents alongside video latents, reference-audio and multi-speaker conditioning, multi shot generation audio/video modeling.
Experimental Design: Design, run, and analyze scientific experiments to advance our understanding of the models.
Data Ownership: Define data requirements and collaborate on acquisition, curation, AV-sync and quality filtering, annotation quality, and synthetic data strategies for paired audio-video and speech corpora.
Rigorous Evaluation: Design automated objective/subjective evaluations audio fidelity and intelligibility metrics, AV-sync, listening and viewing tests, robustness & bias checks, and red-team studies.
Inference Efficiency: Drive distillation, step-count reduction, quantization, and kernel/memory optimization to meet interactive latency and cost targets.
Pipeline Delivery: Harden the training → evaluation → inference pipeline; profile latency, memory, and cost; and meet production SLAs with robust monitoring and rollback.
GPU Scaling: Partner with infrastructure to run distributed training/inference on cloud fleets and productionize models with reliability and observability.
Project Leadership: Independently lead small research projects while collaborating on larger team initiatives, including cross-team work with video generation.
Tool Development: Develop and improve dev tooling to enhance team productivity.
Safety & Responsibility: Contribute to safety/consent guardrails, watermarking, and misuse/abuse mitigation for responsible voice and likeness technology.
What You’ll Bring:
Exceptional research/development experience with large-scale audio models (>8B parameters, >500k hours of data).
Deep hands-on experience with diffusion and/or flow-matching transformers, including practical knowledge of samplers, schedules, conditioning mechanisms, and distillation.
Deep hands-on experience training audio VAEs, neural audio codecs, and vocoders latent/tokenizer design, reconstruction and perceptual objectives, adversarial training.
Strong experience with multi-node, multi-GPU distributed training (FSDP/DeepSpeed or equivalent).
Strong software engineering skills with a proven track record of building complex systems.
Strong with PyTorch and performance work (profiling, CUDA/Triton/C++ as needed) and writing reliable production-quality code.
Shipped large-scale speech/audio or multimodal generative models to production.
Background in working with large-scale ML data, and the ability to iterate on data and triangulate quality using both subjective and objective signals.
Experience with voice cloning, speech control/steerability, or expressive speech generation.
Notable publications and/or open-source contributions in speech/audio/ML.
Strongly preferred:
Experience with multimodal audio-video modeling: joint AV generation of multi-shot, multi-speaker scenes with dialogue, music, and sound design generated jointly with video, and the cross-modal alignment that keeps them in sync.
Experience with video generation: video diffusion/flow-matching transformers, video VAEs, conditioned and multi-shot generation, building data pipelines for video models.
Streaming or real-time generation, causal distillation (e.g., Self Forcing / Self Forcing++).
Compensation:
The anticipated annual base salary range for this role is between $200,000-$220,000 (€170,000-€190,000). When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.
Benefits for U.S.-based roles:
Competitive salary and generous company equity
Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina
42 days of paid time off, including:
15 PTO days
10 sick days
15 company holidays
2 floating holidays
Generous parental leave & fertility support
401(k) retirement savings plan
Lifestyle spending account – $500/month to use however you’d like
Complimentary lunch and snacks for in-office employees
One Medical membership, and more!
Apply for this Job
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Listed by Cantina for a position based in the United States. Employers on this board attest they are hiring domestically.
Machine Learning Engineer, Ops
Location
Remote (U.S. or Europe)
Employment Type
Full time
Department
Research
Overview
Application
About Cantina:
Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning.
If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future!
About the Role:
We are looking for an MLOps Engineer to build and scale the inference infrastructure for our generative audio models, including Text-to-Speech (TTS), voice conversion, and Automatic Speech Recognition (ASR). You will be responsible for designing and deploying high-performance systems that ensure low-latency, reliable, and scalable model serving for both streaming and batch inference. This role is central to bridging the gap between research and production, ensuring our audio models are optimized for performance and cost-efficiency as we scale.
What You’ll Do:
Design and maintain inference infrastructure for generative audio model architectures.
Implement and manage high-performance inference engines.
Orchestrate service deployments using Kubernetes (K8S), implementing advanced autoscaling paradigms to handle varying traffic loads efficiently.
Develop and automate robust CI/CD pipelines to streamline the testing and deployment of model artifacts and inference configurations.
Monitor production systems, establishing observability practices to track latency, resource utilization, and overall model performance.
Collaborate closely with research teams to optimize model serving paths and evaluate various inference strategies.
Optimize inference performance for both streaming and batch applications.
What You’ll Bring:
Deep understanding of modern audio model architectures (e.g., TTS, ASR) and their specific inference requirements.
Strong hands-on experience with Kubernetes (K8S), container orchestration, and implementing autoscaling strategies for production workloads.
Solid background in MLOps, including CI/CD automation and managing scalable cloud infrastructure.
Proficiency in software engineering principles and experience with Python or Go for infrastructure tooling and backend services.
Experience with GPU-accelerated inference and performance profiling techniques.
Familiarity with high-performance inference engines (e.g., Triton Inference Server, vLLM-Omni) is a plus.
Compensation:
The anticipated annual base salary range for this role is between $125,000-$165,000 (€110,000-€145,000). When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.
Benefits for U.S.-based roles:
Competitive salary and generous company equity
Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina
42 days of paid time off, including:
15 PTO days
10 sick days
15 company holidays
2 floating holidays
Generous parental leave & fertility support
401(k) retirement savings plan
Lifestyle spending account – $500/month to use however you’d like
Complimentary lunch and snacks for in-office employees
One Medical membership, and more!
Apply for this Job
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Listed by Cantina for a position based in the United States. Employers on this board attest they are hiring domestically.
Senior Creative Strategist, Performance Marketing
Location
Remote
Employment Type
Full time
Location Type
Remote
Department
Marketing
Overview
Application
About Cantina:
Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning.
If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future!
About the Role:
Cantina’s marketing team is expanding! We're looking for a Senior Creative Strategist with expertise in both traditional and AI-based performance ad production and a track record of systematically developing concept-driven ads at scale that lower CPIs. In this role, you'll manage external agencies and in-house creative teams to deliver high-impact creative that drives users to download and become engaged users in Cantina.
The Senior Creative Strategist, Performance Marketing will drive the creative quality and strategic direction of our paid performance marketing campaigns.
What You’ll Do:
Produce and direct scaled creative across all performance marketing surfaces (Meta, TikTok, YouTube, mobile ad networks, etc) with multi-million dollar ad spend.
Develop performance creative concepts built on intimate understanding of Cantina as a product/platform and its consumer use-cases.
Build and own processes for producing high volume, iterative ads leveraging both traditional and AI-generated production.
Define creative strategies and vision for AI-generated ads.
Own creative performance analytics to track what's working and iterate on best-performing concepts and campaigns.
Set the creative inputs across creative testing plans to optimize creative.
Manage external agencies and cross-functional teams to ensure high-quality creative output across all performance marketing channels.
Lead regular creative brainstorms, reviews, and presentations to internal stakeholders, including leadership.
Oversee the QC process for in-house and external creatives: Create scalable creative review processes and quality standards that maintain excellence at high volume.
Stay up-to-date on and apply emerging technologies, production methods, and best practices in performance creative and performance marketing.
What You’ll Bring:
5+ years of experience in creative direction for performance marketing
Experience building creative testing frameworks and production pipelines at scale
Bias for clear systems and processes
Active use of AI tools, automation, and workflows
Data fluency: you can build infrastructure to ingest campaign performance data and translate insights into creative direction
Demonstrated portfolio of high-performing performance creative, particularly short-form video ads
Deep understanding of the consumer marketing landscape and channels (Meta, TikTok, etc)
Demonstrated experience collaborating effectively with external agencies and cross-functional teams
Demonstrated ability to drive measurable impact (e.g. creative quality improvements combined with quantitative performance improvements)
Compensation:
The anticipated annual base salary range for this role is between $150,000-$200,000. When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.
Benefits:
Competitive salary and generous company equity
Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina
42 days of paid time off, including:
15 PTO days
10 sick days
15 company holidays
2 floating holidays
Generous parental leave & fertility support
401(k) retirement savings plan
Lifestyle spending account – $500/month to use however you’d like
Complimentary lunch and snacks for in-office employees
One Medical membership, and more!
Apply for this Job
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Listed by Cantina for a position based in the United States. Employers on this board attest they are hiring domestically.
Staff Software Engineer, Backend
Location
Los Angeles or San Francisco
Employment Type
Full time
Department
Engineering
Overview
Application
About Cantina:
Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning.
If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future!
About the Role:
As part of the Backend Engineering team, you'll design, build, and scale systems and services that revolutionize how users engage with our cutting-edge AI-powered platform. This role is ideal for a self-sufficient senior software engineer who thrives in fast-paced environments.
What you’ll do:
Collaborate closely with cross-functional teams, including product managers, designers, and data specialists, to deliver high-quality, performant, and maintainable features.
Build and enhance AI-powered systems supporting user acquisition, onboarding, and engagement.
Experiment with and implement new technologies to optimize user journeys and streamline customer experiences.
Gain exposure to the architecture and operations behind one of the fastest-growing social AI products globally.
Contribute your expertise to help evolve team processes and technical infrastructure, ensuring scalability and reliability.
What you’ll bring:
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
5–10 years of professional software engineering experience, with expertise in backend and cloud architectures.
Proficiency in Golang, Node.js, Javascript, TypeScript, Postgres, and AWS (Lambda, DynamoDB, API Gateway, S3).
Solid understanding of software design patterns, microservices architecture, and RESTful APIs.
Familiarity with third party services like Segment, Branch.io, or similar marketing tools.
Strong communication skills and a collaborative, team-oriented mindset.
Compensation:
The anticipated annual base salary range for this role is between $200,000 - $240,000. When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.
Benefits:
Competitive salary and generous company equity
Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina
42 days of paid time off, including:
15 PTO days
10 sick days
15 company holidays
2 floating holidays
Generous parental leave & fertility support
401(k) retirement savings plan
Lifestyle spending account – $500/month to use however you’d like
Complimentary lunch and snacks for in-office employees
One Medical membership, and more!
Apply for this Job
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Listed by Cantina for a position based in the United States. Employers on this board attest they are hiring domestically.
Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning.
If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future!
About the Role:
We are seeking an experienced Machine Learning Engineer (MLE) to focus on audio model evaluation, specifically for speech generation and recognition models.
This role involves designing and developing comprehensive model evaluation pipelines for both development and production environments, as well as creating automated dashboards for reporting evaluation results.
As the founding member of our evaluation team, the ideal candidate is expected to leverage their experience to lead our evaluation efforts and play a key role in the future growth of the evaluation team.
What You’ll Do:
Designing model evaluation pipelines for models in development and production
Designing user studies for subjective model evaluations.
Converting requirements into measurable metrics.
Designing and developing automated evaluation dashboard to see model performances and compare results.
Training new models to capture new and different evaluation metrics.
Communicating with the model team to help design better models based on the evaluation results.
Communicating with the data team to help decide the type of data necessary to improve model performance.
Communication with the product-manager to make sure product requirements are correctly measured.
Help grow the evaluation team as the founding member.
Lead the evaluation team in the future.
What You’ll Bring:
Strong experience and intuition for designing metrics that capture model performance.
Strong experience with designing user studies on Mechanical Turk or similar platforms. .
Strong experience with model training and fine-tuning for model evaluation.
Strong statistical knowledge and experience to statistically compare evaluation results and take decisions.
Very strong engineering and programming skills.
Experience with training ASR, TTS models.
Experience at ML teams working on large-scale machine learning problems. (>3B models with >1m hours of data)
Compensation:
The anticipated annual base salary range for this role is between $200,000-$220,000 (€170,000-€190,000). When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.
Benefits for U.S.-based roles:
Competitive salary and generous company equity
Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina
42 days of paid time off, including:
15 PTO days
10 sick days
15 company holidays
2 floating holidays
Generous parental leave & fertility support
401(k) retirement savings plan
Lifestyle spending account – $500/month to use however you’d like
Complimentary lunch and snacks for in-office employees
One Medical membership, and more!
Listed by Cantina for a position based in the United States. Employers on this board attest they are hiring domestically.
Engineering
205 days ago
Member of Technical Staff, Data & ML Infrastructure for Video Models
Member of Technical Staff, Data & ML Infrastructure for Video Models
Location
Remote (U.S. or Europe)
Employment Type
Full time
Department
Engineering
Overview
Application
About Cantina:
Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning.
If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future!
About the Role:
We are looking for a new Member of Technical Staff to build and scale the data pipelines behind our large video generation models. This role is focused on collecting large amounts of relevant video data, preparing high-quality training samples, and developing robust preprocessing, filtering, and parsing workflows. You'll orchestrate annotation pipelines across platforms such as MTurk and own the full lifecycle of training data, from raw ingestion to clean, model-ready samples that directly drive quality improvements. This role sits at the intersection of data engineering and ML research, making it central to how we turn messy real-world data into the fuel that moves our models forward.
What You’ll Do:
Build and maintain data pipelines for large video generation models, including data ingestion, parsing, filtering, preprocessing, and dataset curation at scale, using tools such as AWS S3 and DynamoDB.
Design and run annotation workflows across platforms such as MTurk, Prolific, and Mechanical Turk, including task design, quality control, and label validation.
Train, evaluate, and improve smaller supporting models used for data filtering, quality assessment, preprocessing, or other parts of the ML pipeline.
Partner closely with research and engineering teams to turn experimental workflows into scalable, repeatable systems that support model training and evaluation.
Own data quality across the pipeline by identifying bottlenecks, failure modes, and low-quality sources, and continuously improving tooling and processes.
Build internal tools and automation that make it easier to prepare datasets, launch annotation jobs, monitor outputs, and support model development end to end.
Drive larger pipeline projects from start to finish, such as new dataset creation efforts or upgrades to labeling and preprocessing infrastructure.
Work within a Kubernetes-based training infrastructure, ensuring datasets are properly prepared, formatted, and delivered to training clusters.
Profile and optimize research model inference scripts used in preprocessing steps, ensuring that model-driven filtering and transformation stages run within practical time and cost constraints when applied to large-scale raw data.
What You’ll Bring:
3+ years of experience in machine learning, applied ML, data pipelines, or related engineering roles, ideally working on large-scale multimodal, video, or vision-based systems.
Strong programming skills in Python and solid experience building reliable data processing and preprocessing pipelines for ML workflows.
Hands-on experience preparing training data for ML models, including parsing, filtering, dataset curation, quality control, and large-scale data handling using tools such as AWS S3 and DynamoDB.
Familiarity with annotation and labeling workflows, including task design, vendor or crowd-platform orchestration such as MTurk or Prolific, and methods for ensuring label quality.
Experience working with Kubernetes for orchestrating distributed workloads, including data preprocessing, pipeline execution, and dataset delivery to training clusters.
Comfort working across cloud and on-demand compute environments such as AWS and RunPod, with the ability to port and optimize pipelines across infrastructure.
Familiarity with distributed data processing frameworks and experience designing systems that operate reliably at scale across many nodes or workers.
Working knowledge of PyTorch and the broader deep learning stack, with the ability to read, debug, and optimize research model inference code for use in production preprocessing pipelines.
Ability to work cross-functionally with research and engineering teams and translate experimental ideas into robust, scalable systems.
Bachelor's, Master's, or PhD in Computer Science, Machine Learning, Engineering, Mathematics, or a related technical field; experience in generative video, computer vision, or multimodal ML is strongly preferred.
Bonus: Experience training, evaluating, or fine-tuning smaller ML models used for classification, filtering, ranking, quality assessment, or other supporting tasks in an ML pipeline.
Compensation:
The anticipated annual base salary range for this role is between $200,000-$260,000 (€170,000-€225,000). When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.
Benefits for U.S.-based roles:
Competitive salary and generous company equity
Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina
42 days of paid time off, including:
15 PTO days
10 sick days
15 company holidays
2 floating holidays
Generous parental leave & fertility support
401(k) retirement savings plan
Lifestyle spending account – $500/month to use however you’d like
Complimentary lunch and snacks for in-office employees
One Medical membership, and more!
Apply for this Job
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Listed by Cantina for a position based in the United States. Employers on this board attest they are hiring domestically.
Machine Learning Engineer, Images
Location
Bay Area or Remote
Employment Type
Full time
Department
Engineering
Overview
Application
About Cantina:
Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning.
If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future!
About the Role:
As a Senior Machine Learning Engineer on the AI Image Generation (Imagine) team, you'll design, implement, fine tune, improve and debug the image AI models that power our lifelike AI bots. The Imagine Team at Cantina is responsible for all generative image and machine vision services. Your expertise in machine learning and scalable ML infrastructure will be crucial in developing innovative features that revolutionize how people connect and create online.
AI bots on Cantina are multimodal and can text and talk with you as well as send you selfies. To provide these capabilities, we continually develop and deploy new image generation pipelines that create photorealistic, consistent characters.
The Imagine team is constantly striving to improve the quality, character consistency, responsiveness to prompting, inference time, and incorporation of an ever increasing number of custom looks and appearance traits.
What You’ll Do:
Evaluate new image generation and identity preservation papers and models.
Develop and deploy new versions of the image generation and image analysis pipelines
Monitor and fix production issues that impact users
Fine-tune and optimize models to improve character consistency, prompt responsiveness, and inference latency
Design and run experiments to benchmark model performance, tracking quality metrics across generations of pipeline improvements
Collaborate with cross-functional teams to translate product requirements into ML solutions and bring new generative features from prototype to production
What You’ll Bring:
Demonstrated interest in AI image generation. This includes both personal and professional projects
Deep technical foundation in machine learning specifically in image synthesis
5+ years experience as a software engineer, preferably in services
2+ years of experience of building production-grade machine learning models in industry and/or academic research settings
Strong programming skills in Python and deploying Python based services
Familiarity with tools and frameworks involved in AI image generation including but not limited to Stable Diffusion, Diffusion Transformers (DiT), Visual Transformers (ViT), Tensorflow, PyTorch, Diffusers, ComfyUI, TensorRT, and CUDA
Experience building end-to-end scalable ML infrastructure with on-premise or cloud platforms including Baseten, Google Cloud Platform (GCP), Amazon Web Services (AWS) or Azure
Strong teamwork skills including communication and collaboration with both technical and non-technical team members
Compensation:
The anticipated annual base salary range for this role is between $200,000-$265,000. When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.
Benefits We Offer:
Competitive salary and generous company equity
Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina
42 days of paid time off, including:
15 PTO days
10 sick days
15 company holidays
2 floating holidays
Generous parental leave & fertility support
401(k) retirement savings plan
Lifestyle spending account – $500/month to use however you’d like
Complimentary lunch and snacks for in-office employees
One Medical membership, and more!
Apply for this Job
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Listed by Cantina for a position based in the United States. Employers on this board attest they are hiring domestically.
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