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AI Developer Experience & Media Lead
DatologyAI · Redwood City, California, USA
$160k–230k
36 days ago
♡
Software Engineer, Cloud Infrastructure
DatologyAI · Redwood City, California, USA
$180k–300k
242 days ago
♡
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AI Developer Experience & Media Lead
DatologyAI · Redwood City, California, USA
Pay
$160k–230k
Setting
On-site
ABOUT THE COMPANY
Models are what they eat. But a large portion of training compute is wasted training on data that are already learned, irrelevant, or even harmful, leading to worse models that cost more to train and deploy.
At DatologyAI, we’ve built a state of the art data curation suite to automatically curate and optimize petabytes of data to create the best possible training data for your models. Training on curated data can dramatically reduce training time and cost (7-40x faster training depending on the use case), dramatically increase model performance as if you had trained on >10x more raw data without increasing the cost of training, and allow smaller models with fewer than half the parameters to outperform larger models despite using far less compute at inference time, substantially reducing the cost of deployment. For more details, check out our recent research on synthetic data scaling (BeyondWeb https://www.datologyai.com/blog/beyondweb) and pretraining with domain-specific data (The Finetuner’s Fallacy https://www.datologyai.com/blog/finetuners-fallacy).
We raised a total of $57.5M in two rounds, a Seed and Series A. Our investors include Felicis Ventures, Radical Ventures, Amplify Partners, Microsoft, Amazon, and AI visionaries like Geoff Hinton, Yann LeCun, Jeff Dean, and many others who deeply understand the importance and difficulty of identifying and optimizing the best possible training data for models. Our team has pioneered this frontier research area and has the deep expertise on both data research and data engineering necessary to solve this incredibly challenging problem and make data curation easy for anyone who wants to train their own model on their own data.
This role is based in Redwood City, CA. We are in office 4 days a week.
ABOUT THE ROLE
In this role, you'll be our expert on social, the person who knows how to make DatologyAI's research travel on X and across the AI community. You'll turn our research into narratives, demos, threads, videos, and launches, build a voice on X that people recognize and trust, and take part in the conversation as it happens. You'll also help our founders and researchers communicate in their own voices.
The work sits where engineering meets media. You can read one of our results, understand why it matters, and build a demo or write a thread that a technical audience respects. You have a creator's instincts for hooks, video, distribution, and taste. And you're genuinely active in the AI community on X, replying, experimenting, and engaging, not just posting announcements.
You'll build the playbook as you operate it. We have real research worth talking about, credible founders, and an audience that's already here, and we're looking for someone who can meet them where they are and be trusted to run with it.
WHAT YOU'LL WORK ON
- Technical storytelling and demos. Take our research and product work and turn it into narratives, threads, videos, live demos, and launches that a technical audience finds genuinely interesting.
- Company voice on X. Build a recognizable, native voice for DatologyAI on X and run it day to day. Reply, quote-post, and participate in live conversations in real time.
- Founder and researcher enablement. Help leadership and our research team show up in their own voices.
- Research launches, end to end. Own the public launch of our research across X, the technical blog, and video: the angle, the assets, the sequencing, and the follow-through, so each result gets the attention it deserves.
- Community and relationships. Build real relationships with researchers, open-source developers, AI creators, and technical founders.
- Feedback loop into product and research. Bring what you learn in the community back to the team, so what we hear from developers and researchers informs what we build and what we say next.
- Experiments and measurement. Run experiments across X, technical writing, video, launches, and events. Track what earns attention and trust from the right people, and use it to sharpen what we do next.
ABOUT YOU
- Technical legitimacy. You can build and explain real AI systems. You can read a paper or a launch brief, understand it, comment on it accurately, and produce a demo or a technically serious thread from it.
- X-native. You genuinely live on the platform. You post and reply frequently, participate in live conversations, and have a native tone. We care far more about your reply and quote-post behavior and your taste than your follower count.
- Creator instincts. You understand hooks, compression, video, personality, and distribution. You have a recognizable voice and a feel for what makes people stop scrolling and engage.
- Ambient participant, not a broadcaster. You interact, experiment, and joke in the conversation rather than only publishing polished company announcements.
- Able to write in other voices. You can help a founder or researcher sound like themselves, credibly, without flattening what makes them distinctive.
- Self-starter with a bias toward action. You take an objective, build the approach, and run with it.
- Startup-ready. Comfortable building the playbook as you operate it, moving fast, and owning outcomes end to end.
Nice to Have
- Your own audience on X, or a track record of building one, with side projects or demos that have circulated organically
- Experience at an AI model or infrastructure company, or in developer relations, developer marketing, or growth engineering
- A body of technical content spanning agents, inference, multimodality, coding workflows, or similar
- Comfort in front of a camera and the ability to produce short technical video
Don't meet every single requirement? We still encourage you to apply. If you're excited about our mission and eager to learn, we want to hear from you!
COMPENSATION
At DatologyAI, we are dedicated to rewarding talent with a highly competitive salary and significant equity. The base salary range for this position is 160,000 - $230,000.
- The candidate's starting pay will be determined based on job-related skills, experience, qualifications, and interview performance.
Benefits:
- 100% covered health benefits (medical, vision, and dental).
- 401(k) plan with a generous 4% company match.
- Unlimited PTO policy
- Paid Parental Leave of 12 weeks, plus 6 months of WFH flexibility.
- Annual $2,000 wellness stipend.
- Annual $1,000 learning and development stipend.
- Daily lunches and snacks are provided in our office!
- Relocation assistance for employees moving to the Bay Area.
Listed by DatologyAI for a position based in the United States. Employers on this board attest they are hiring domestically.
Software Engineer, Front-end
DatologyAI · Redwood City, California, USA
Pay
$180k–300k
Setting
On-site
ABOUT THE COMPANY
Models are what they eat. But a large portion of training compute is wasted training on data that are already learned, irrelevant, or even harmful, leading to worse models that cost more to train and deploy.
At DatologyAI, we’ve built a state of the art data curation suite to automatically curate and optimize petabytes of data to create the best possible training data for your models. Training on curated data can dramatically reduce training time and cost (7-40x faster training depending on the use case), dramatically increase model performance as if you had trained on >10x more raw data without increasing the cost of training, and allow smaller models with fewer than half the parameters to outperform larger models despite using far less compute at inference time, substantially reducing the cost of deployment. For more details, check out our recent research on synthetic data scaling (BeyondWeb https://www.datologyai.com/blog/beyondweb) and pretraining with domain-specific data (The Finetuner’s Fallacy https://www.datologyai.com/blog/finetuners-fallacy).
We raised a total of $57.5M in two rounds, a Seed and Series A. Our investors include Felicis Ventures, Radical Ventures, Amplify Partners, Microsoft, Amazon, and AI visionaries like Geoff Hinton, Yann LeCun, Jeff Dean, and many others who deeply understand the importance and difficulty of identifying and optimizing the best possible training data for models. Our team has pioneered this frontier research area and has the deep expertise on both data research and data engineering necessary to solve this incredibly challenging problem and make data curation easy for anyone who wants to train their own model on their own data.
This role is based in Redwood City, CA. We are in office 4 days a week.
ABOUT THE ROLE
We are looking for Front-end engineers who love building new products in an iterative and fast-moving environment. In this role, you will build software from the ground up to solve critical bottlenecks for DatologyAI customers and internally. As one of our key hires, you will partner closely with our founders on the direction of our product and drive business-critical technical decisions.
WHAT YOU'LL WORK ON
You will contribute to developing the core product that customers use for curating their datasets and the visualizations around it, as well as the internal tooling that our team uses daily to develop the core product. You will have a broad impact on the technology, product, and our company's culture.
- Own the full front-end development lifecycle for customer-facing data curation products, from design through implementation, as well as new internal tooling interfaces.
- Talk to customers and internal stakeholders to understand their problems and design solutions to address them.
- Collaborate with a cross-functional team of engineers, researchers, designers, etc to bring new features and research capabilities to our customers.
- Ensure that our products and systems are reliable, secure, and worthy of our customers' trust.
ABOUT YOU
- 4+ years of relevant experience
- Have meaningful experience with leading and building production front-end systems that deliver on major product initiatives
- Proficiency in JavaScript/TypeScript, React, other web technologies, and Python.
- Care deeply about quality, functionality, and the humans we’re communicating to by sweating the details, down to the last page request.
- Experience maintaining a high-quality bar for design, correctness, and testing.
- Own problems end-to-end and are willing to pick up whatever knowledge you're missing to get the job done.
- Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed
- Have prior experience in ML/AI (preferred but not required).
COMPENSATION
At DatologyAI, we are dedicated to rewarding talent with competitive salary and meaningful equity. The salary for this position ranges from $180,000 to $300,000.
- Starting pay is based on job-related skills, experience, qualifications, and interview performance.
Benefits:
- 100% covered health benefits (medical, vision, and dental).
- 401(k) plan with a generous 4% company match.
- Unlimited PTO policy
- Paid Parental Leave of 12 weeks, plus 6 months of WFH flexibility.
- Annual $2,000 wellness stipend.
- Annual $1,000 learning and development stipend.
- Daily lunches and snacks are provided in our office!
- Relocation assistance for employees moving to the Bay Area.
Listed by DatologyAI for a position based in the United States. Employers on this board attest they are hiring domestically.
Software Engineer, Cloud Infrastructure
DatologyAI · Redwood City, California, USA
Pay
$180k–300k
Setting
On-site
ABOUT THE COMPANY
Models are what they eat. But a large portion of training compute is wasted training on data that are already learned, irrelevant, or even harmful, leading to worse models that cost more to train and deploy.
At DatologyAI, we’ve built a state of the art data curation suite to automatically curate and optimize petabytes of data to create the best possible training data for your models. Training on curated data can dramatically reduce training time and cost (7-40x faster training depending on the use case), dramatically increase model performance as if you had trained on >10x more raw data without increasing the cost of training, and allow smaller models with fewer than half the parameters to outperform larger models despite using far less compute at inference time, substantially reducing the cost of deployment. For more details, check out our recent research on synthetic data scaling (BeyondWeb https://www.datologyai.com/blog/beyondweb) and pretraining with domain-specific data (The Finetuner’s Fallacy https://www.datologyai.com/blog/finetuners-fallacy).
We raised a total of $57.5M in two rounds, a Seed and Series A. Our investors include Felicis Ventures, Radical Ventures, Amplify Partners, Microsoft, Amazon, and AI visionaries like Geoff Hinton, Yann LeCun, Jeff Dean, and many others who deeply understand the importance and difficulty of identifying and optimizing the best possible training data for models. Our team has pioneered this frontier research area and has the deep expertise on both data research and data engineering necessary to solve this incredibly challenging problem and make data curation easy for anyone who wants to train their own model on their own data.
This role is based in Redwood City, CA. We are in office 4 days a week.
ABOUT THE ROLE
We’re looking for an experienced Cloud Infrastructure Engineer to join our core team at DatologyAI. In this role, you will lead the design, build, and operation of highly available, secure, and scalable cloud infrastructure that powers our training, inference, and data curation pipelines. You’ll work closely with engineering, research, and product teams to define how we deploy and manage compute resources across AWS and other cloud providers. This role is a key early hire and offers an opportunity to have a deep technical and cultural impact.
WHAT YOU'LL WORK ON
- Architect and maintain our multi-cloud infrastructure (primarily AWS, potentially Azure/GCP), with a focus on reliability, security, and scalability
- Define and implement infrastructure-as-code best practices using Terraform, CloudFormation, Pulumi (and similar technologies)
- Design and manage Kubernetes-based systems for model training, inference, and data processing workloads
- Optimize our CI/CD pipelines and streamline deployment of services across environments
- Build monitoring, alerting, and logging systems to ensure high system availability and observability
- Collaborate with research and engineering teams to provide infrastructure support for training large-scale ML models
- Ensure our infrastructure supports various deployment models (cloud, on-prem, hybrid) for enterprise use cases
- Drive cost-efficiency strategies across compute and storage resources
- Respond to and resolve infrastructure-related incidents with a sense of ownership and urgency
ABOUT YOU
- 4+ years of relevant experience
- You’ve led or helped build robust infrastructure systems at a startup or fast-moving engineering organization
- Deep experience working with cloud providers (especially AWS), and ideally exposure to multi-cloud or hybrid-cloud setups
- Strong with Kubernetes, Terraform, and containerized architectures
- Confident with systems-level debugging—networking issues, memory leaks, resource bottlenecks, etc.
- Comfortable writing clean, maintainable scripts in Bash, Python, or Go
- You care deeply about building secure and scalable systems and take pride in reliable infrastructure
- You’re collaborative, humble, and ready to own high-impact projects end-to-end
Nice to Have
- Experience supporting infrastructure for ML workloads (training pipelines, inference clusters, GPU orchestration)
- Built or scaled infrastructure for teams working with large-scale datasets
- Exposure to cost monitoring and optimization tools in cloud environments
- Background supporting compliance and security in enterprise deployments
COMPENSATION
At DatologyAI, we are dedicated to rewarding talent with competitive salary and meaningful equity. The salary for this position ranges from $180,000 to $300,000.
- Starting pay is based on job-related skills, experience, qualifications, and interview performance.
Benefits:
- 100% covered health benefits (medical, vision, and dental).
- 401(k) plan with a generous 4% company match.
- Unlimited PTO policy
- Paid Parental Leave of 12 weeks, plus 6 months of WFH flexibility.
- Annual $2,000 wellness stipend.
- Annual $1,000 learning and development stipend.
- Daily lunches and snacks are provided in our office!
- Relocation assistance for employees moving to the Bay Area.
Listed by DatologyAI for a position based in the United States. Employers on this board attest they are hiring domestically.
Software Engineer, Infrastructure
DatologyAI · Redwood City, California, USA
Pay
$180k–300k
Setting
On-site
ABOUT THE COMPANY
Models are what they eat. But a large portion of training compute is wasted training on data that are already learned, irrelevant, or even harmful, leading to worse models that cost more to train and deploy.
At DatologyAI, we’ve built a state of the art data curation suite to automatically curate and optimize petabytes of data to create the best possible training data for your models. Training on curated data can dramatically reduce training time and cost (7-40x faster training depending on the use case), dramatically increase model performance as if you had trained on >10x more raw data without increasing the cost of training, and allow smaller models with fewer than half the parameters to outperform larger models despite using far less compute at inference time, substantially reducing the cost of deployment. For more details, check out our recent research on synthetic data scaling (BeyondWeb https://www.datologyai.com/blog/beyondweb) and pretraining with domain-specific data (The Finetuner’s Fallacy https://www.datologyai.com/blog/finetuners-fallacy).
We raised a total of $57.5M in two rounds, a Seed and Series A. Our investors include Felicis Ventures, Radical Ventures, Amplify Partners, Microsoft, Amazon, and AI visionaries like Geoff Hinton, Yann LeCun, Jeff Dean, and many others who deeply understand the importance and difficulty of identifying and optimizing the best possible training data for models. Our team has pioneered this frontier research area and has the deep expertise on both data research and data engineering necessary to solve this incredibly challenging problem and make data curation easy for anyone who wants to train their own model on their own data.
This role is based in Redwood City, CA. We are in office 4 days a week.
ABOUT THE ROLE
We're looking for an experienced Infrastructure Engineer to join as a member of our core Datology AI team. As one of our early senior hires, you will partner closely with our founders on the direction of our product and drive business-critical technical decisions. You will lead the development of our data infrastructure capabilities, including multi-cloud support and support for various deployment models, as well as training and inference infrastructure. You will have a broad impact on the technology, product, and our company's culture.
WHAT YOU'LL WORK ON
- Design and build the development and production platforms that power our products, enabling reliability and security at scale
- Architect, build, and deploy our core infrastructure while supporting multiple cloud providers and various deployment models
- Accelerate company productivity by empowering your fellow engineers & teammates with excellent tooling and systems, providing a best-in-case experience
- Partner with researchers and engineers to bring new features and research capabilities to our customers
ABOUT YOU
- 4+ years of relevant experience
- Have meaningful experience in spearheading and constructing large-scale infrastructure
- Proficiency in bash, Kubernetes, Python, and/or Terraform or similar technologies
- Have experience working with AWS, other cloud platforms such as Azure or GCP and/or on-prem environments
- Have expertise in debugging problems across the stack, such as networking issues, performance problems, hardware issues or memory leaks
- Take pride in building and operating scalable, reliable, secure systems
- Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed
- Own problems end-to-end and are willing to pick up whatever knowledge you're missing to get the job done
We would love it if you had:
- Built out data infrastructure from, or nearly from, scratch at a fast-growing startup.
- Experience building ML/DL infrastructure and/or data infrastructure that feeds into training large ML models
Don’t meet every single requirement? We still encourage you to apply. If you’re excited about our mission and eager to learn, we want to hear from you!
COMPENSATION
At DatologyAI, we are dedicated to rewarding talent with competitive salary and meaningful equity. The salary for this position ranges from $180,000 to $300,000.
- Starting pay is based on job-related skills, experience, qualifications, and interview performance.
Benefits:
- 100% covered health benefits (medical, vision, and dental).
- 401(k) plan with a generous 4% company match.
- Unlimited PTO policy
- Paid Parental Leave of 12 weeks, plus 6 months of WFH flexibility.
- Annual $2,000 wellness stipend.
- Annual $1,000 learning and development stipend.
- Daily lunches and snacks are provided in our office!
- Relocation assistance for employees moving to the Bay Area.
Listed by DatologyAI for a position based in the United States. Employers on this board attest they are hiring domestically.
Software Engineer, Data Infrastructure
DatologyAI · Redwood City, California, USA
Pay
$180k–300k
Setting
On-site
Data Infrastructure Engineer
Listed by DatologyAI for a position based in the United States. Employers on this board attest they are hiring domestically.
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