Passionate about building AI models from the ground up and deploying them in production
Excited about joining early-stage startups and working directly with founders
Interested in shaping AI strategy and leading the development of AI-powered products
SignalFire partners with top early-stage startups shaping the future of technology. They have a portfolio of over 200 innovative companies across AI, cybersecurity, healthtech, fintech, developer tools, and enterprise SaaS.
Define and execute AI strategy, partnering with executive leadership to build AssetWatch's AI-native vision and roadmap.
Lead the AI and Data Science organization, building, mentoring, and developing high-performing teams across Machine Learning Engineering and AI Engineering.
Partner across the business to identify AI opportunities, implement governance, and measure impact on customer outcomes and revenue.
AssetWatch powers manufacturing uptime by delivering condition monitoring solutions for global manufacturers. They are a devoted team of world-renowned engineers and distinguished business leaders united by a common goal to build the future of predictive maintenance.
Lead the design and operation of production machine learning systems for batch and online use cases with a focus on reliability and scalability.
Build and improve ML lifecycle infrastructure including training pipelines, inference workflows, monitoring, and automation.
Partner with cross-functional teams to translate business problems into ML solutions and guide prototypes to robust production systems.
Included Health is a healthcare company delivering integrated virtual care and navigation, aiming to raise the standard of healthcare for everyone. They are a remote-first organization offering comprehensive benefits and fostering a culture of inclusion.
Design, build, and deploy production ML and LLM-based systems (RAG, agentic workflows, fine-tuning, embeddings) for enterprise clients.
Own technical delivery end-to-end: from architecture and prototyping to deployment, monitoring, and iteration.
Mentor and support other ML engineers on the team with code reviews, technical guidance, and knowledge sharing.
TensorOps is a boutique AI consultancy that bridges strategy and execution, designing and shipping production-grade AI systems for enterprise clients. We are a 100% remote team of 11+ people, partnering with unicorns and NASDAQ-listed companies, and have a culture of autonomy, open communication, and continuous learning.
Shape and scale enterprise-wide AI capabilities as a strategic leader, bridging business teams, technology platforms, and AI initiatives.
Design scalable AI architectures and workflows across departments like Engineering, Sales, Marketing, Finance, Legal, HR, and Operations.
Create AI enablement programs including workshops, playbooks, and training materials to increase organizational AI maturity.
This role is listed on behalf of a partner company that manages applications and next steps. They are a global organization focused on enterprise-wide artificial intelligence capabilities, with a collaborative culture that values innovation and learning.
Design, develop, and deploy production-grade AI-powered backend systems integrating LLMs and traditional ML models.
Integrate and optimize vector databases for RAG pipelines, and write clean, well-structured Python code.
Debug complex cross-layer issues and collaborate with product and engineering teams to deliver cohesive solutions.
We are a fast-growing product company integrating cutting-edge AI capabilities into our core offering to deliver exceptional value to customers. Our small, fast-moving team works on practical, real-world AI applications with high autonomy.
Define and execute the product vision, strategy, roadmap, and prioritization for a portfolio of AI-powered products.
Lead cross-functional teams through product discovery, development, launch, and continuous improvement, balancing customer needs and business objectives.
Drive the successful delivery of scalable, secure, and reliable AI solutions using iterative development, experimentation, and user feedback.
Our partner is a leading organization in artificial intelligence and digital products. They foster a collaborative, innovation-focused culture with a strong emphasis on research and development.
Design, develop, and deploy production-grade AI-powered backend systems.
Integrate large language models and machine learning models into scalable architectures.
Optimize system performance and implement strong testing practices.
Our partner company is building advanced AI-powered systems to create meaningful customer value. The team operates in a high-autonomy, fast-moving environment focused on production-ready AI solutions.
Lead end-to-end development of advanced AI solutions including agentic systems, RAG pipelines, and multi-agent workflows.
Architect AI infrastructure with guardrails, access controls, and compliance protocols for ethical deployment.
Guide multi-disciplinary teams, setting technical playbook and best practices.
Nava is a consultancy and public benefit corporation that makes government services simple and effective. Since 2015, federal, state, and local agencies have trusted Nava to solve technology modernization challenges, and they maintain a collaborative, remote-friendly team environment.
Design and own the playbook for AI productization, governance, and reusable internal tooling.
Champion AI-assisted development, TDD, and modern CI/CD practices across the organization.
Act as the primary technical authority bridging AI/ML architecture and executive strategy.
RYZ Labs is a startup studio that creates industry-defining companies by leveraging top talent and cutting-edge cloud technologies. Founded in 2021, we have a remote team across the US and Latam, with a culture of autonomy, ownership, and continuous improvement.
Hands-on design and development of AI product features for Veeva QualityDocs and Training
Design and deliver production AI Agent applications including data flow, orchestration, and prompts
Work with engineering and UX to automate key business processes using AI
Veeva Systems is a mission-driven pioneer in industry cloud, helping life sciences companies bring therapies to patients faster. It is one of the fastest-growing SaaS companies in history, surpassing $3B in revenue, and operates as a public benefit corporation with a focus on customers, employees, society, and investors.
Own AI operations and governance across the enterprise, ensuring systems are reliable, compliant, and secure.
Provide hands-on technical leadership in model evaluation, tuning, and troubleshooting alongside program oversight.
Build and lead a team responsible for AI sustainment, including strategic planning and executive communication.
Shield AI builds autonomous systems for defense and aerospace. As a growing company, it emphasizes a culture of innovation and technical rigor, seeking leaders to operationalize AI governance.
Own the application engineering strategy and execution across backend, mobile, and desktop.
Lead and grow a small, senior applications team.
Ensure production-grade reliability and integration of AI capabilities.
We help companies hire technical leads and IT professionals for jobs in San Francisco and other cities. We are a recruiting agency focused on IT staffing.
Design and build the company's AI-first platform architecture.
Develop agent-based systems, orchestration layers, and inference pipelines.
Build scalable data ingestion, transformation, and feature engineering pipelines.
Our client is an early-stage healthcare AI company leveraging AI, data science, and clinical expertise to generate actionable insights from health data. The small team works alongside experienced founders and world-class advisors, building an AI-native platform from scratch.
Design, develop, and deploy ML models, including large language models, for various NLP tasks.
Collaborate with cross-functional teams to gather requirements, define architectures, and iterate on model development.
Stay up-to-date with latest research and contribute to best practices for responsible ML development.
Reddit is a community of communities built on shared interests, passion, and trust, hosting the most open and authentic conversations on the internet. With over 100,000 active communities and approximately 126 million daily active users, it is one of the internet's largest sources of information, fostering a culture of authenticity and community.
Own end-to-end Machine Learning (ML) system execution including data pipelines, training, and deployment.
Fine-tune and adapt models using state-of-the-art methods like LoRA and DPO.
Architect scalable inference systems and collaborate closely with application engineering.
This company develops advanced production-grade machine learning systems. The team is small and high-trust, with a culture of ownership and pragmatism.
Own end-to-end delivery quality for major engagements, translating ambiguous client needs into practical execution plans.
Lead solution architecture and technical decision-making, making pragmatic tradeoffs between speed, quality, and client value.
Build and ship production AI/ML systems using Python, ML frameworks, and cloud-native infrastructure while mentoring other engineers.
Eliza is a technology services company and Advanced-tier OpenAI partner that helps organizations build and deploy AI solutions, from generative AI to predictive analytics. They are a collaborative, mission-driven team focused on real-world AI impact.
Evaluate LLM architecture logic for technical accuracy and audit ML code and notebooks for efficiency.
Refine RLHF frameworks to align models with human intent and analyze model reasoning in complex chain-of-thought prompts.
Benchmark performance by conducting comparative testing between model outputs based on technical metrics.
Prolific connects researchers with a global pool of participants for collecting high-quality human data to train AI models. With over 35,000 users, they focus on ethical data gathering to advance AI capabilities.
Architect and build AI platforms, working across distributed teams to deliver GenAI products like Abacus Agents, MCP, and RAG systems.
Develop ML/AI pipelines for data preprocessing, model training, and evaluation, enabling rapid experimentation and self-healing systems.
Mentor software developers, participate in architectural discussions, and communicate technical direction to align teams and stakeholders.
Abacus Insights transforms healthcare data for health plans to improve outcomes, reduce waste, and enhance member and provider experiences. Backed by $100M from top investors, the company is a collaborative, curiosity-driven team of bold individuals embracing AI and automation to innovate in the healthcare industry.