Build and scale ML infrastructure and tools to support AI-driven genetic medicine research.
Partner with scientists and engineers to translate research prototypes into robust systems.
Optimize model training and inference performance using advanced computing frameworks.
Dyno Therapeutics is building high-performance genetic technologies to transform patient lives. Their team unites world-class experts at the intersection of AI and genetic medicine.
Develop AI-assisted methods for classifying, summarizing, and quality-checking Zero Trust assessment data.
Prototype analytical capabilities to identify maturity trends and implementation anomalies.
Integrate approved AI services with existing data and automation workflows using secure interfaces.
True Zero Technologies is a veteran-owned small business that enables people and technology to improve organizational outcomes. Recognized as a Best Places to Work honoree and on the Inc. 5000 list, it fosters a community of driven innovators committed to top-tier services and a people-first culture.
Design and write high-performing, scalable software for training models.
Develop new tools to support and accelerate research and LLM training.
Collaborate with engineering and scientific teams to create a strong post-training ecosystem.
Cohere is a security-first enterprise AI company building cutting-edge foundation models and end-to-end products to solve real-world business problems. They are a global team of researchers, engineers, and designers passionate about their craft, with offices in Toronto, London, New York, San Francisco, Montreal, Paris, Berlin, and Seoul.
Build cutting-edge technology using deep learning and machine learning to personalize Pinterest.
Partner with teams to improve ML models for product surfaces like Homefeed and Search.
Use data-driven methods to improve content recommendation and ads delivery.
Pinterest is a platform where millions of people find creative ideas and plan for memories. The company is mission-driven, focusing on innovation and inclusion, with a large and diverse user base.
Experiment with modern neural network architectures and techniques driven by research
Design and implement machine learning perception solutions in new domains
Collaborate with AI Data Team, ML engineers, and Cloud infrastructure engineers
AMP applies AI-powered sortation to modernize recycling infrastructure and maximize waste value. Recognized as a top workplace in Colorado, AMP has hundreds of global deployments and is backed by top-tier investors.
Define and maintain end-to-end system architecture for secure AI evaluation platforms.
Evaluate open-source and commercial technologies to guide build-versus-buy decisions.
Guide technical solutions and mentor engineering teams across distributed environments.
OpenTeams helps enterprises and governments build AI they can fully control and govern. Built by pioneers from NumPy, SciPy, and PyTorch, the company fosters a culture of ownership and innovation with a global, distributed team.
Own the technical vision and roadmap for ML systems powering forecasting, supply positioning, and fleet optimization.
Lead end-to-end execution of complex, cross-functional ML initiatives, from problem framing through production impact, ensuring alignment with business goals.
Mentor and develop engineers, providing technical guidance and raising the overall bar for ML and software engineering excellence.
Lime is the largest global shared micromobility business, on a mission to build a future where transportation is shared, affordable, and carbon-free. A Time Magazine 100 Most Influential Company, Lime has powered more than one billion rides in close to 30 countries across five continents, spurring a new generation of clean alternatives to car ownership.
Design, build, and operate end-to-end ML systems across batch and real-time workloads.
Develop production capabilities for personalization, recommendations, optimization, and experimentation.
Provide technical leadership for ML architecture and distributed systems.
Kard is building commerce media infrastructure that connects financial institutions, financial-services platforms, and merchants through data and merchant-funded rewards. It is a remote-first company that values initiative, openness, and humility.
Design, develop, and evaluate machine learning models using real-world health data for personalized interventions.
Work with engineering teams to integrate models into production digital therapeutic solutions as Software as a Medical Device.
Ensure models meet regulatory, privacy, and explainability requirements while exploring generative AI applications.
They develop AI and machine learning solutions for digital therapies to improve patient outcomes. They are a technology-focused healthcare company with a remote-first culture.
Lead the architectural design and development of scalable AI/ML pipelines for enterprise initiatives.
Provide technical leadership and mentorship to AI/ML engineers and data scientists.
Deploy and manage advanced models including LLMs and Generative AI in production environments.
They are an organization focused on delivering enterprise AI and Machine Learning solutions. They offer a fully remote, flexible work environment with a strong emphasis on professional growth and collaboration.
Own the applied AI and ML solutions that power patient-provider matching, clinical workflows, and patient engagement.
Develop production-grade AI systems including recommendation engines, search ranking, and NLP applications.
Set technical direction for AI infrastructure and ensure responsible, safe AI in a high-stakes healthcare environment.
Rula is a mental health company dedicated to providing quality, evidence-based, and compassionate care to empower individuals to take charge of their mental health. It is a remote-first company with a culture of inclusion and diversity, hiring in most US states.
Design, develop, and optimize computer vision models and deep learning capabilities across the product portfolio.
Build and maintain ETL pipelines, clean datasets, and perform feature engineering for machine learning applications.
Collaborate with cross-functional teams to productionize, deploy, and monitor models in real-world environments.
FloVision is a remote-first startup improving the food supply chain with computer vision and ML. It is a Series A company with a distributed team across the US, UK, and Ireland.
Build and improve the inference layer of the Gcore Inference platform, integrating frameworks like vLLM and TensorRT-LLM.
Bring new language and multimodal models into production, optimizing latency, throughput, and cost efficiency.
Debug performance issues across model code, GPU execution, and Kubernetes, collaborating with cross-functional teams.
Gcore is a global provider of AI, cloud, network, and security infrastructure and software. They are a team of 550+ professionals with a collaborative culture and partnerships with Intel, NVIDIA, Dell, and Equinix.
Provide on-call MLOps support for model development teams, triaging and resolving pipeline issues.
Assist in debugging model workflows and identifying root causes across the ML stack.
Collaborate with senior engineers to improve tooling, documentation, and operational processes.
Torc is an autonomous driving leader since 2007 and now part of Daimler, building software for automated trucks. The culture is collaborative, energetic, and team-focused.
Build the environments and verifiers our models train against
Own the synthetic data pipeline, from generation through quality gates
Ship models into production and keep improving them on real usage
LiveKit builds the infrastructure layer for the voice-driven era of computing, enabling developers to build, deploy, and scale voice AI applications. Founded in 2021, they power voice AI for major companies and have a small, senior team that values craft and creativity.
Design, develop, and deploy AI models to solve complex business challenges.
Collaborate with cross-functional teams to integrate AI solutions into production systems.
Continuously improve and optimize AI pipelines for performance, scalability, and reliability.
We are passionate about helping businesses navigate the rapidly changing and complex world of emerging technologies. We create well-structured, secure, scalable solutions at speed to provide the foundation for groundbreaking change.
Evaluate GPU kernel tasks for technical accuracy, realism, solvability, reproducibility, and robust testing criteria.
Rigorously test and troubleshoot complex GPU programming scenarios to identify memory allocation bugs, execution bottlenecks, and parallel computing logic errors.
Review CUDA, Triton, and other GPU kernel implementations and provide clear, actionable technical feedback.
Our partner is a company specializing in AI training and evaluation, seeking experienced GPU kernel specialists to audit AI training tasks. The project is globally distributed and offers fully remote freelance work.
Help define and drive the ML engineering strategy for Discovery Mode and related royalty programs.
Design, build, evaluate, ship, and refine production ML systems through hands-on development.
Provide technical leadership across complex ML initiatives and collaborate with cross-functional teams.
Spotify is the world's most popular audio streaming subscription service, focused on unlocking human creativity. With a strong emphasis on inclusivity and innovation, the company employs thousands worldwide and values diverse perspectives.
Own the full ML delivery lifecycle from data discovery to deployment, monitoring, and retraining.
Build forecasting and detection models robust to real-world data quality issues and defend tradeoffs.
Maintain client-facing presence and feedback loop, shipping usable capability like FastAPI, React, or scheduled jobs.
We accelerate positive impact in critical industries through AI transformation, specializing in physics-informed ML and enterprise AI solutions for climate and sustainability. We're a fast-growing, profitable public benefit corporation founded in 2024, working with category leaders in real estate, energy, logistics, and utilities.
Design and maintain scalable ML infrastructure for deploying models to edge devices worldwide.
Own the model compilation platform, optimizing neural networks with TensorRT for hardware-specific inference.
Collaborate with Data Scientists and Embedded Engineers to automate deployment, monitoring, and reliability.
Hudl provides video analysis and data tools that help sports teams and athletes improve their performance. The company fosters a collaborative culture and has been named one of Newsweek's Top 100 Global Most Loved Workplaces.