Head of Product - VC Backed Startups
Join SignalFire’s Talent Network for Head of Product (Director/VP) Roles at VC-Backed Startups
🛑 This is not an application for a specific job. Instead, this is a way to get on the radar of VC-backed startups that are actively hiring Product leaders. If you have any questions, please direct inquiries to talentnetwork@signalfire.com.
At SignalFire, we partner with top early-stage startups that are shaping the future of technology. Our spans 200+ innovative companies across AI, cybersecurity, healthtech, fintech, developer tools, and enterprise SaaS.
We’re looking to connect with exceptional Heads of Product (Director/VP-level leaders) who are excited about owning product vision, scaling product teams, and driving strategy at high-growth startups. By joining SignalFire’s Talent Network, your profile will be shared with our portfolio companies, giving you visibility into exclusive early-stage opportunities that may not be publicly listed.
Who Should Join?
We’re looking for product leaders who are:
✔ Passionate about driving product strategy and execution for category-defining products
✔ Experienced in scaling product organizations, setting vision, and managing roadmaps
✔ Excited to collaborate with executives, engineering, and go-to-market teams to build world-class products
Typical Roles & Responsibilities
Own and define product vision, strategy, and roadmap to drive business impact
Build and scale high-performing product teams, hiring and mentoring top product talent
Drive cross-functional alignment across engineering, design, marketing, and sales
Oversee feature prioritization, execution, and product development lifecycles
Develop data-driven decision-making frameworks, using analytics and user research to optimize product success
Own go-to-market strategy, working with sales and marketing to ensure strong product adoption
Identify and evaluate new market opportunities, competitive positioning, and growth strategies
Ensure best-in-class user experience, customer feedback loops, and rapid iteration cycles
Collaborate with founders and executive teams to align product direction with company objectives
Common Qualifications
While each startup has its own hiring criteria, many Head of Product (Director/VP-level) roles in our network look for:
8+ years of experience in product management, with 3+ years leading product teams
Proven ability to scale and manage product teams in high-growth environments
Strong track record of defining product vision and executing go-to-market strategies
Deep experience in B2B SaaS, AI, fintech, marketplaces, or developer tools
Strong understanding of UX/UI design principles, customer research, and product analytics
Ability to balance long-term strategic vision with rapid product execution
Hands-on experience with A/B testing, data analysis, and growth optimization
Experience working in venture-backed startups or fast-scaling technology companies
💡 Tools & Technologies You Might Work With:
Product Management & Analytics: Jira, Asana, Trello, Notion, Amplitude, Mixpanel, Google Analytics
Design & Prototyping: Figma, Sketch, Adobe XD, Framer, InVision
Collaboration & Documentation: Slack, Notion, Confluence, Miro, Loom
Data & Experimentation: SQL, Looker, Tableau, A/B Testing Platforms
What Happens Next?
Submit your application to join SignalFire’s Talent Ecosystem.
We review applications on an ongoing basis to identify strong candidates.
If there’s a match, a SignalFire talent partner or a leader from one of our startups may reach out directly.
No match yet? We’ll keep your profile on file for future product leadership roles in our portfolio.
Head of Product - VC Backed Startups
Join SignalFire’s Talent Network for Head of Product (Director/VP) Roles at VC-Backed Startups
🛑 This is not an application for a specific job. Instead, this is a way to get on the radar of VC-backed startups that are actively hiring Product leaders. If you have any questions, please direct inquiries to talentnetwork@signalfire.com.
At SignalFire, we partner with top early-stage startups that are shaping the future of technology. Our spans 200+ innovative companies across AI, cybersecurity, healthtech, fintech, developer tools, and enterprise SaaS.
We’re looking to connect with exceptional Heads of Product (Director/VP-level leaders) who are excited about owning product vision, scaling product teams, and driving strategy at high-growth startups. By joining SignalFire’s Talent Network, your profile will be shared with our portfolio companies, giving you visibility into exclusive early-stage opportunities that may not be publicly listed.
Who Should Join?
We’re looking for product leaders who are:
✔ Passionate about driving product strategy and execution for category-defining products
✔ Experienced in scaling product organizations, setting vision, and managing roadmaps
✔ Excited to collaborate with executives, engineering, and go-to-market teams to build world-class products
Typical Roles & Responsibilities
Own and define product vision, strategy, and roadmap to drive business impact
Build and scale high-performing product teams, hiring and mentoring top product talent
Drive cross-functional alignment across engineering, design, marketing, and sales
Oversee feature prioritization, execution, and product development lifecycles
Develop data-driven decision-making frameworks, using analytics and user research to optimize product success
Own go-to-market strategy, working with sales and marketing to ensure strong product adoption
Identify and evaluate new market opportunities, competitive positioning, and growth strategies
Ensure best-in-class user experience, customer feedback loops, and rapid iteration cycles
Collaborate with founders and executive teams to align product direction with company objectives
Common Qualifications
While each startup has its own hiring criteria, many Head of Product (Director/VP-level) roles in our network look for:
8+ years of experience in product management, with 3+ years leading product teams
Proven ability to scale and manage product teams in high-growth environments
Strong track record of defining product vision and executing go-to-market strategies
Deep experience in B2B SaaS, AI, fintech, marketplaces, or developer tools
Strong understanding of UX/UI design principles, customer research, and product analytics
Ability to balance long-term strategic vision with rapid product execution
Hands-on experience with A/B testing, data analysis, and growth optimization
Experience working in venture-backed startups or fast-scaling technology companies
💡 Tools & Technologies You Might Work With:
Product Management & Analytics: Jira, Asana, Trello, Notion, Amplitude, Mixpanel, Google Analytics
Design & Prototyping: Figma, Sketch, Adobe XD, Framer, InVision
Collaboration & Documentation: Slack, Notion, Confluence, Miro, Loom
Data & Experimentation: SQL, Looker, Tableau, A/B Testing Platforms
What Happens Next?
Submit your application to join SignalFire’s Talent Ecosystem.
We review applications on an ongoing basis to identify strong candidates.
If there’s a match, a SignalFire talent partner or a leader from one of our startups may reach out directly.
No match yet? We’ll keep your profile on file for future product leadership roles in our portfolio.
Data Scientist (Senior/Staff) - VC Backed Startups
Join SignalFire’s Talent Network for Senior/Staff Data Scientist Roles at VC-Backed Startups
🛑 This is not an application for a specific job. Instead, this is a way to get on the radar of VC-backed startups that are actively hiring Data Science talent. If you have any questions, please direct inquiries to talentnetwork@signalfire.com.
At SignalFire, we partner with top early-stage startups that are shaping the future of technology. Our portfolio spans 200+ innovative companies across AI, cybersecurity, healthtech, fintech, developer tools, and enterprise SaaS.
We’re looking to connect with exceptional Senior and Staff Data Scientists who are excited about using data, experimentation, and machine learning to solve complex product and business problems at high-growth startups.
By joining SignalFire’s Talent Network, your profile will be shared with our portfolio companies, giving you visibility into exclusive early-stage opportunities that may not be publicly listed.
Who Should Join?
We’re looking for data scientists who are:
✔ Passionate about using data to improve products, customer outcomes, and business decisions
✔ Experienced in experimentation, statistical analysis, predictive modeling, or causal inference
✔ Excited to work closely with product, engineering, operations, and business teams
✔ Comfortable operating with incomplete data and ambiguous problems in fast-moving startup environments
✔ Interested in building scalable analytical frameworks, models, and decision-making systems
Typical Roles & Responsibilities
Partner with product, engineering, and business leaders to identify high-impact opportunities for data science
Design and analyze experiments to evaluate product changes, growth initiatives, and operational strategies
Develop predictive, forecasting, recommendation, ranking, or optimization models
Apply statistical methods and causal inference techniques to measure impact and inform decisions
Build metrics, analytical frameworks, and dashboards that improve visibility into product and business performance
Translate complex analyses into clear recommendations for technical and non-technical stakeholders
Collaborate with engineers to productionize models and integrate data science into customer-facing products
Identify patterns in user, customer, operational, and market data
Establish best practices for experimentation, model evaluation, data quality, and analytical rigor
Mentor other data scientists and raise the technical standard of the broader data organization
Help shape the company’s data strategy, tooling, and long-term analytical roadmap
Common Qualifications
While each startup has its own hiring criteria, many Senior and Staff Data Scientist roles in our network look for:
5+ years of experience in data science, applied statistics, machine learning, decision science, or a related field
Strong proficiency in Python, R, SQL, or similar analytical languages
Experience with statistical modeling, experimentation, causal inference, forecasting, or predictive analytics
Track record of using data to influence product strategy, customer outcomes, or business performance
Ability to work with large, complex, and imperfect datasets
Experience partnering closely with product managers, engineers, operators, and executive stakeholders
Strong communication skills and the ability to explain technical findings clearly
Experience developing models or analytical systems that are used in production or operational decision-making
Strong judgment around methodology, measurement, tradeoffs, and uncertainty
Experience in venture-backed startups or rapidly scaling technology companies may be preferred
Advanced degree in statistics, economics, computer science, mathematics, operations research, or a related field may be preferred, but is not always required
💡 Technologies You Might Work With:
Languages & Analysis: Python, R, SQL, pandas, NumPy, SciPy
Modeling & Machine Learning: scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow
Experimentation & Statistics: A/B testing, causal inference, Bayesian methods, time-series analysis
Data Platforms: Snowflake, BigQuery, Redshift, Databricks, Spark
Visualization & Analytics: Looker, Tableau, Mode, Hex, Amplitude
Workflow & Development: Jupyter, dbt, Airflow, Git, Docker, cloud platforms
What Happens Next?
Submit your application to join SignalFire’s Talent Ecosystem.
We review applications on an ongoing basis to identify strong candidates.
If there’s a match, a SignalFire talent partner or a leader from one of our startups may reach out directly.
No match yet? We’ll keep your profile on file for future Senior and Staff Data Scientist roles across our portfolio.
Enterprise Account Executive (EAE) - VC Backed Startups
Join SignalFire’s Talent Network for Enterprise Account Executives at VC-Backed Startups
🛑 This is not an application for a specific job. Instead, this is a way to get on the radar of VC-backed startups that are actively hiring Sales talent.
At SignalFire, we partner with top early-stage startups that are shaping the future of technology. Our portfolio spans 200+ innovative companies across AI, cybersecurity, healthtech, fintech, developer tools, and enterprise SaaS.
We’re looking to connect with Enterprise Account Executives (EAEs) who have experience navigating complex sales cycles and closing high-value deals with Fortune 1000 and Global 2000 companies. By joining SignalFire’s Talent Network, your profile will be shared with our portfolio companies, giving you visibility into exclusive early-stage enterprise sales opportunities that may not be publicly listed.
Who Should Join?
We’re looking for strategic sellers who are:
✔ Experienced in managing complex, multi-stakeholder sales cycles
✔ Comfortable with longer deal timelines and seven-figure+ ACVs
✔ Skilled at navigating enterprise procurement, legal, and security reviews
✔ Energized by building pipeline in greenfield territories or verticals
Typical Roles & Responsibilities
Drive new business acquisition across named enterprise accounts or verticals
Develop account plans and engage multiple stakeholders across departments and functions
Lead highly consultative sales processes, including custom demos, proof of concepts, and ROI analyses
Collaborate cross-functionally with solutions engineers, product, marketing, and leadership to win strategic deals
Navigate procurement, security assessments, and enterprise-level contract negotiations
Forecast pipeline accurately and contribute to overall sales strategy and growth planning
Serve as a trusted advisor to C-level buyers and help shape product roadmap with feedback
Common Qualifications
While each startup has unique needs, strong EAEs in our network typically have:
5+ years of quota-carrying experience in enterprise B2B sales
Proven track record of closing $100K–$1M+ ACV deals
Experience selling into technical and business decision-makers across the enterprise
Strong familiarity with sales methodologies like MEDDIC, Challenger, or SPIN
Ability to build commercial relationships with C-suite executives
Skilled in managing multi-threaded sales cycles with long lead times
Background in AI, SaaS, cybersecurity, data, or developer tools is a plus
💡 Tools & Technologies You Might Work With:
CRM & Sales Enablement: Salesforce, HubSpot, Clari, Gong, Highspot
Account Intelligence & Prospecting: ZoomInfo, LinkedIn Sales Navigator, 6sense, Demandbase
Sales Methodology: MEDDIC, Challenger, Force Management
Collaboration Tools: Slack, Notion, Loom, Zoom
Reporting & Forecasting: Looker, Tableau, Excel
What Happens Next?
Submit your application to join SignalFire’s Talent Ecosystem.
We review applications on an ongoing basis to identify strong candidates.
If there’s a match, a SignalFire talent partner or a leader from one of our startups may reach out directly.
No match yet? We’ll keep your profile on file for future sales roles in our portfolio.
🚀 Ready to accelerate your career in sales? Join our Talent Network today!
Enterprise Account Executive (EAE) - VC Backed Startups
Join SignalFire’s Talent Network for Enterprise Account Executives at VC-Backed Startups
🛑 This is not an application for a specific job. Instead, this is a way to get on the radar of VC-backed startups that are actively hiring Sales talent.
At SignalFire, we partner with top early-stage startups that are shaping the future of technology. Our portfolio spans 200+ innovative companies across AI, cybersecurity, healthtech, fintech, developer tools, and enterprise SaaS.
We’re looking to connect with Enterprise Account Executives (EAEs) who have experience navigating complex sales cycles and closing high-value deals with Fortune 1000 and Global 2000 companies. By joining SignalFire’s Talent Network, your profile will be shared with our portfolio companies, giving you visibility into exclusive early-stage enterprise sales opportunities that may not be publicly listed.
Who Should Join?
We’re looking for strategic sellers who are:
✔ Experienced in managing complex, multi-stakeholder sales cycles
✔ Comfortable with longer deal timelines and seven-figure+ ACVs
✔ Skilled at navigating enterprise procurement, legal, and security reviews
✔ Energized by building pipeline in greenfield territories or verticals
Typical Roles & Responsibilities
Drive new business acquisition across named enterprise accounts or verticals
Develop account plans and engage multiple stakeholders across departments and functions
Lead highly consultative sales processes, including custom demos, proof of concepts, and ROI analyses
Collaborate cross-functionally with solutions engineers, product, marketing, and leadership to win strategic deals
Navigate procurement, security assessments, and enterprise-level contract negotiations
Forecast pipeline accurately and contribute to overall sales strategy and growth planning
Serve as a trusted advisor to C-level buyers and help shape product roadmap with feedback
Common Qualifications
While each startup has unique needs, strong EAEs in our network typically have:
5+ years of quota-carrying experience in enterprise B2B sales
Proven track record of closing $100K–$1M+ ACV deals
Experience selling into technical and business decision-makers across the enterprise
Strong familiarity with sales methodologies like MEDDIC, Challenger, or SPIN
Ability to build commercial relationships with C-suite executives
Skilled in managing multi-threaded sales cycles with long lead times
Background in AI, SaaS, cybersecurity, data, or developer tools is a plus
💡 Tools & Technologies You Might Work With:
CRM & Sales Enablement: Salesforce, HubSpot, Clari, Gong, Highspot
Account Intelligence & Prospecting: ZoomInfo, LinkedIn Sales Navigator, 6sense, Demandbase
Sales Methodology: MEDDIC, Challenger, Force Management
Collaboration Tools: Slack, Notion, Loom, Zoom
Reporting & Forecasting: Looker, Tableau, Excel
What Happens Next?
Submit your application to join SignalFire’s Talent Ecosystem.
We review applications on an ongoing basis to identify strong candidates.
If there’s a match, a SignalFire talent partner or a leader from one of our startups may reach out directly.
No match yet? We’ll keep your profile on file for future sales roles in our portfolio.
🚀 Ready to accelerate your career in sales? Join our Talent Network today!
Data Scientist (Senior/Staff) - VC Backed Startups
Join SignalFire’s Talent Network for Senior/Staff Data Scientist Roles at VC-Backed Startups
🛑 This is not an application for a specific job. Instead, this is a way to get on the radar of VC-backed startups that are actively hiring Data Science talent. If you have any questions, please direct inquiries to talentnetwork@signalfire.com.
At SignalFire, we partner with top early-stage startups that are shaping the future of technology. Our portfolio spans 200+ innovative companies across AI, cybersecurity, healthtech, fintech, developer tools, and enterprise SaaS.
We’re looking to connect with exceptional Senior and Staff Data Scientists who are excited about using data, experimentation, and machine learning to solve complex product and business problems at high-growth startups.
By joining SignalFire’s Talent Network, your profile will be shared with our portfolio companies, giving you visibility into exclusive early-stage opportunities that may not be publicly listed.
Who Should Join?
We’re looking for data scientists who are:
✔ Passionate about using data to improve products, customer outcomes, and business decisions
✔ Experienced in experimentation, statistical analysis, predictive modeling, or causal inference
✔ Excited to work closely with product, engineering, operations, and business teams
✔ Comfortable operating with incomplete data and ambiguous problems in fast-moving startup environments
✔ Interested in building scalable analytical frameworks, models, and decision-making systems
Typical Roles & Responsibilities
Partner with product, engineering, and business leaders to identify high-impact opportunities for data science
Design and analyze experiments to evaluate product changes, growth initiatives, and operational strategies
Develop predictive, forecasting, recommendation, ranking, or optimization models
Apply statistical methods and causal inference techniques to measure impact and inform decisions
Build metrics, analytical frameworks, and dashboards that improve visibility into product and business performance
Translate complex analyses into clear recommendations for technical and non-technical stakeholders
Collaborate with engineers to productionize models and integrate data science into customer-facing products
Identify patterns in user, customer, operational, and market data
Establish best practices for experimentation, model evaluation, data quality, and analytical rigor
Mentor other data scientists and raise the technical standard of the broader data organization
Help shape the company’s data strategy, tooling, and long-term analytical roadmap
Common Qualifications
While each startup has its own hiring criteria, many Senior and Staff Data Scientist roles in our network look for:
5+ years of experience in data science, applied statistics, machine learning, decision science, or a related field
Strong proficiency in Python, R, SQL, or similar analytical languages
Experience with statistical modeling, experimentation, causal inference, forecasting, or predictive analytics
Track record of using data to influence product strategy, customer outcomes, or business performance
Ability to work with large, complex, and imperfect datasets
Experience partnering closely with product managers, engineers, operators, and executive stakeholders
Strong communication skills and the ability to explain technical findings clearly
Experience developing models or analytical systems that are used in production or operational decision-making
Strong judgment around methodology, measurement, tradeoffs, and uncertainty
Experience in venture-backed startups or rapidly scaling technology companies may be preferred
Advanced degree in statistics, economics, computer science, mathematics, operations research, or a related field may be preferred, but is not always required
💡 Technologies You Might Work With:
Languages & Analysis: Python, R, SQL, pandas, NumPy, SciPy
Modeling & Machine Learning: scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow
Experimentation & Statistics: A/B testing, causal inference, Bayesian methods, time-series analysis
Data Platforms: Snowflake, BigQuery, Redshift, Databricks, Spark
Visualization & Analytics: Looker, Tableau, Mode, Hex, Amplitude
Workflow & Development: Jupyter, dbt, Airflow, Git, Docker, cloud platforms
What Happens Next?
Submit your application to join SignalFire’s Talent Ecosystem.
We review applications on an ongoing basis to identify strong candidates.
If there’s a match, a SignalFire talent partner or a leader from one of our startups may reach out directly.
No match yet? We’ll keep your profile on file for future Senior and Staff Data Scientist roles across our portfolio.
Applied AI Scientist/Researcher (Senior/Staff) - VC Backed Startups
Join SignalFire’s Talent Network for Senior/Staff Applied AI Scientist & Researcher Roles at VC-Backed Startups
🛑 This is not an application for a specific job. Instead, this is a way to get on the radar of VC-backed startups that are actively hiring Applied AI Scientists and Researchers. If you have any questions, please direct inquiries to talentnetwork@signalfire.com.
At SignalFire, we partner with top early-stage startups that are shaping the future of technology. Our portfolio spans 200+ innovative companies across AI, cybersecurity, healthtech, fintech, developer tools, and enterprise SaaS.
We’re looking to connect with exceptional Senior and Staff Applied AI Scientists and Researchers who are excited about developing advanced AI capabilities, solving complex technical problems, and translating emerging research into differentiated products.
By joining SignalFire’s Talent Network, your profile will be shared with our portfolio companies, giving you visibility into exclusive early-stage opportunities that may not be publicly listed.
Who Should Join?
We’re looking for scientists and researchers who are:
✔ Passionate about advancing the capabilities and real-world applications of artificial intelligence
✔ Experienced in developing, adapting, and evaluating modern machine learning models
✔ Excited to translate research and experimentation into production-ready product capabilities
✔ Comfortable operating at the intersection of research, engineering, product, and customer needs
✔ Interested in solving open-ended technical problems in fast-moving startup environments
Typical Roles & Responsibilities
Research, develop, and evaluate machine learning methods that improve product capabilities and customer outcomes
Design experiments to test new model architectures, training approaches, data strategies, and system designs
Adapt foundation models through fine-tuning, post-training, prompt optimization, retrieval, or other techniques
Develop evaluation frameworks and benchmarks for model quality, reliability, safety, and performance
Build prototypes and proofs of concept that demonstrate the potential of emerging AI techniques
Partner with AI/ML engineers and software engineers to translate successful experiments into production systems
Improve model accuracy, reasoning, latency, efficiency, robustness, and cost
Curate, generate, and evaluate datasets used for training, fine-tuning, and model assessment
Investigate model failures, edge cases, and unexpected behavior to identify opportunities for improvement
Stay current with relevant research and determine which advances can create practical product value
Communicate findings, tradeoffs, and technical recommendations to product, engineering, and executive stakeholders
Mentor other scientists and contribute to the company’s research culture, technical standards, and AI roadmap
Publish research, contribute to open-source projects, or represent the company within the broader technical community where appropriate
Common Qualifications
While each startup has its own hiring criteria, many Senior and Staff Applied AI Scientist and Researcher roles in our network look for:
5+ years of experience in machine learning, artificial intelligence, applied research, or a related technical field
Strong foundation in deep learning, statistics, optimization, and experimental design
Experience developing or adapting models for real-world product applications
Expertise in one or more areas such as natural language processing, generative AI, computer vision, multimodal learning, reinforcement learning, recommendation systems, or speech
Proficiency in Python and modern machine learning frameworks such as PyTorch, TensorFlow, or JAX
Experience with model training, fine-tuning, post-training, evaluation, or inference
Ability to design rigorous experiments and draw sound conclusions from incomplete or ambiguous results
Track record of translating research concepts into prototypes, production systems, or measurable product improvements
Ability to collaborate closely with research, engineering, product, and domain experts
Strong written and verbal communication skills, including the ability to explain complex technical concepts clearly
Staff-level candidates may be expected to define research direction, lead cross-functional initiatives, and influence broader AI strategy
Advanced degree in computer science, machine learning, statistics, mathematics, or a related field may be preferred, although equivalent applied experience may be considered
💡 Technologies You Might Work With:
Languages & Frameworks: Python, PyTorch, TensorFlow, JAX, Hugging Face, scikit-learn
Models & Techniques: Large language models, transformers, multimodal models, diffusion models, reinforcement learning, recommendation and ranking systems
Model Adaptation: Fine-tuning, reinforcement learning from feedback, preference optimization, distillation, synthetic data, prompt optimization
AI Systems: Retrieval-augmented generation, agents, tool use, structured generation, reasoning systems, model routing
Evaluation & Experimentation: Offline and online evaluation, human evaluation, benchmarking, red teaming, interpretability, model observability
Data & Infrastructure: Spark, Databricks, Snowflake, vector databases, distributed training, GPUs, Kubernetes
Models & Platforms: OpenAI, Anthropic, Google, Meta, open-source foundation models, and proprietary model architectures
What Happens Next?
Submit your application to join SignalFire’s Talent Ecosystem.
We review applications on an ongoing basis to identify strong candidates.
If there’s a match, a SignalFire talent partner or a leader from one of our startups may reach out directly.
No match yet? We’ll keep your profile on file for future Senior and Staff Applied AI Scientist and Researcher roles across our portfolio.
Applied AI Scientist/Researcher (Senior/Staff) - VC Backed Startups
Join SignalFire’s Talent Network for Senior/Staff Applied AI Scientist & Researcher Roles at VC-Backed Startups
🛑 This is not an application for a specific job. Instead, this is a way to get on the radar of VC-backed startups that are actively hiring Applied AI Scientists and Researchers. If you have any questions, please direct inquiries to talentnetwork@signalfire.com.
At SignalFire, we partner with top early-stage startups that are shaping the future of technology. Our portfolio spans 200+ innovative companies across AI, cybersecurity, healthtech, fintech, developer tools, and enterprise SaaS.
We’re looking to connect with exceptional Senior and Staff Applied AI Scientists and Researchers who are excited about developing advanced AI capabilities, solving complex technical problems, and translating emerging research into differentiated products.
By joining SignalFire’s Talent Network, your profile will be shared with our portfolio companies, giving you visibility into exclusive early-stage opportunities that may not be publicly listed.
Who Should Join?
We’re looking for scientists and researchers who are:
✔ Passionate about advancing the capabilities and real-world applications of artificial intelligence
✔ Experienced in developing, adapting, and evaluating modern machine learning models
✔ Excited to translate research and experimentation into production-ready product capabilities
✔ Comfortable operating at the intersection of research, engineering, product, and customer needs
✔ Interested in solving open-ended technical problems in fast-moving startup environments
Typical Roles & Responsibilities
Research, develop, and evaluate machine learning methods that improve product capabilities and customer outcomes
Design experiments to test new model architectures, training approaches, data strategies, and system designs
Adapt foundation models through fine-tuning, post-training, prompt optimization, retrieval, or other techniques
Develop evaluation frameworks and benchmarks for model quality, reliability, safety, and performance
Build prototypes and proofs of concept that demonstrate the potential of emerging AI techniques
Partner with AI/ML engineers and software engineers to translate successful experiments into production systems
Improve model accuracy, reasoning, latency, efficiency, robustness, and cost
Curate, generate, and evaluate datasets used for training, fine-tuning, and model assessment
Investigate model failures, edge cases, and unexpected behavior to identify opportunities for improvement
Stay current with relevant research and determine which advances can create practical product value
Communicate findings, tradeoffs, and technical recommendations to product, engineering, and executive stakeholders
Mentor other scientists and contribute to the company’s research culture, technical standards, and AI roadmap
Publish research, contribute to open-source projects, or represent the company within the broader technical community where appropriate
Common Qualifications
While each startup has its own hiring criteria, many Senior and Staff Applied AI Scientist and Researcher roles in our network look for:
5+ years of experience in machine learning, artificial intelligence, applied research, or a related technical field
Strong foundation in deep learning, statistics, optimization, and experimental design
Experience developing or adapting models for real-world product applications
Expertise in one or more areas such as natural language processing, generative AI, computer vision, multimodal learning, reinforcement learning, recommendation systems, or speech
Proficiency in Python and modern machine learning frameworks such as PyTorch, TensorFlow, or JAX
Experience with model training, fine-tuning, post-training, evaluation, or inference
Ability to design rigorous experiments and draw sound conclusions from incomplete or ambiguous results
Track record of translating research concepts into prototypes, production systems, or measurable product improvements
Ability to collaborate closely with research, engineering, product, and domain experts
Strong written and verbal communication skills, including the ability to explain complex technical concepts clearly
Staff-level candidates may be expected to define research direction, lead cross-functional initiatives, and influence broader AI strategy
Advanced degree in computer science, machine learning, statistics, mathematics, or a related field may be preferred, although equivalent applied experience may be considered
💡 Technologies You Might Work With:
Languages & Frameworks: Python, PyTorch, TensorFlow, JAX, Hugging Face, scikit-learn
Models & Techniques: Large language models, transformers, multimodal models, diffusion models, reinforcement learning, recommendation and ranking systems
Model Adaptation: Fine-tuning, reinforcement learning from feedback, preference optimization, distillation, synthetic data, prompt optimization
AI Systems: Retrieval-augmented generation, agents, tool use, structured generation, reasoning systems, model routing
Evaluation & Experimentation: Offline and online evaluation, human evaluation, benchmarking, red teaming, interpretability, model observability
Data & Infrastructure: Spark, Databricks, Snowflake, vector databases, distributed training, GPUs, Kubernetes
Models & Platforms: OpenAI, Anthropic, Google, Meta, open-source foundation models, and proprietary model architectures
What Happens Next?
Submit your application to join SignalFire’s Talent Ecosystem.
We review applications on an ongoing basis to identify strong candidates.
If there’s a match, a SignalFire talent partner or a leader from one of our startups may reach out directly.
No match yet? We’ll keep your profile on file for future Senior and Staff Applied AI Scientist and Researcher roles across our portfolio.
The full posting opens here — pay, setting and the full description, without leaving the list.