Design and maintain reliable, low-latency ML APIs to integrate Safety AI model outputs into cloud applications.
Build scalable data pipelines for continuous model iteration, backtesting, and online evaluation.
Optimize model artifacts for production and monitor rollout health, ensuring predictable failure modes.
Samsara builds a Connected Operations Cloud that helps physical operations use IoT data to improve safety, efficiency, and sustainability. Samsara is a recently public company with an employee-led remote culture and a long-term focus.
Productionize ML models into reliable, scalable systems with CI/CD, data versioning, and model governance.
Implement monitoring for data quality, drift, model performance, and pipeline health with clear alerting.
Refactor research code into reusable components and enforce engineering best practices.
Nift is disrupting performance marketing, delivering millions of new customers to brands every month. We are a data-driven, cash-flow-positive company that has experienced 731% growth over the last three years, backed by Spark Capital & Foundry.
Design, build, and operate scalable backend services, APIs, and data pipelines for ML-driven personalization.
Improve reliability, performance, and observability of production ML systems, including model versioning and safe rollout.
Collaborate with data scientists and product engineers to translate business needs into robust technical solutions.
Hungryroot uses AI to build a consumer-centric food and wellness company, acting as a personal assistant for healthy living by recommending and delivering healthy groceries, recipes, and supplements. They are a distributed team across 28+ US states with a remote-first culture emphasizing collaboration, flexibility, and an annual company retreat.
Develop tools and automate manual processes to improve operational efficiency and accelerate experimentation.
Build, integrate, and monitor end-to-end lifecycles of large-scale distributed machine learning systems.
Enhance ML pipelines for forecasting platforms with automated retraining and deployment.
Apella applies computer vision and machine learning to improve the standard of care in surgery. They are a remote-first startup focused on building reliable ML solutions for healthcare.
Build and operate model and inference serving infrastructure, managing latency, throughput, autoscaling, and reliability for real-time and batch inference.
Own the ML deployment lifecycle: model registry, versioning, promotion workflows, rollout strategies, and safe rollback.
Operate agentic and LLM workloads in production, managing inference providers, gateways, quotas, guardrails, and graceful degradation under load.
ReadyOn is an AI-native Labor Operating System that redefines how enterprises manage frontline labor by matching workers to shifts in real time. Headquartered in San Francisco with over 100 employees, it grew revenue 8x year over year in 2025.
Build monitoring infrastructure for production ML and GenAI models.
Define and track model health metrics including accuracy, drift, and output quality.
Partner with data scientists and ML engineers to integrate monitoring into deployment lifecycle.
Liberty Mutual is a global insurance company that provides property and casualty insurance. The company values inclusion, professional development, and employee well-being, offering comprehensive benefits and workplace flexibility.
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.
Own the infrastructure layer for AI workloads including inference serving, Kubernetes, and agent-sandboxing platforms.
Manage the serving tier for open-weight models, Kubernetes operators, and stateful data planes.
Oversee the sandbox runtime, control-plane services, and observability tooling.
AZX accelerates positive impact in critical industries through AI transformation, specializing in physics-informed ML and enterprise AI solutions for climate and sustainability. Founded in 2024, the company is a profitable public benefit corporation with a growing team working with category leaders in real estate, energy, logistics, and utilities.
Drive and continuously improve MLOps practices across the machine learning environment.
Build, optimize, and maintain CI/CD pipelines using GitLab for reliable ML delivery.
Productionize and maintain machine learning models using AWS, with a focus on SageMaker.
The company operates a globally deployed recommender system and focuses on machine learning infrastructure. The team is collaborative and supportive, with an emphasis on knowledge sharing and professional development.
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.
Own the ML/AI platform including training infrastructure, model serving, inference pipelines, and production integration.
Drive the GenAI/LLM strategy including retrieval architectures, evaluation harnesses, and agentic workflows.
Partner with data scientists, DevOps, and backend engineers to productionize models and define API contracts.
SavvyMoney is a US-based financial technology company providing integrated credit score and personal finance solutions to over 1,600 banks and credit unions throughout the United States. The company was recognized as a 'Top 25 Places to Work' in the San Francisco Bay Area and is an Inc. 5000 Fastest Growing Company.
Drive innovation across the machine learning ecosystem and architect advanced ML solutions.
Mentor junior ML engineers and lead complex ML initiatives at scale.
Own models in production including deployment, monitoring, drift detection, and retraining.
Xsolla is a global commerce company providing tools and services to help video game developers fund, distribute, market, and monetize their games. Headquartered in Los Angeles, California, Xsolla has helped over 1,500 game developers grow their businesses worldwide.
Drive backend development for AI workflows using Python and FastAPI as part of a collaborative team.
Productionize LLM integrations with systems for Bedrock usage, quotas, retries, and cost controls.
Build for scale by optimizing async job orchestration, performance, and data-layer for petabyte-scale enterprise data.
Smarsh empowers organizations to manage risk and uncover intelligence in digital communications. With over 6500 clients in regulated industries and consistent recognition from Gartner and Forrester, Smarsh has been listed on the Inc. 5000 as one of America's fastest-growing companies since 2008.
Build and maintain infrastructure for training, deploying, and monitoring ML models and GenAI services.
Develop and operate production backend services, APIs, and pipelines supporting recommendations and agent workflows.
Strengthen platform reliability, scalability, security, performance, and cost efficiency across the technology stack.
Jobgether uses an AI-powered matching process to help candidates apply for jobs. It processes personal data to evaluate applications and shares relevant information with hiring employers.
Lead AI production operations, including deployment support, monitoring, and incident response for traditional ML, GenAI, and agentic systems.
Build observability practices like drift detection and latency tracking to ensure production health and performance.
Serve as the key liaison between AI systems and Security, Infrastructure, and Governance teams to enforce security and ethical AI standards.
Xsolis is an AI-driven technology company reducing administrative waste in healthcare by enabling smarter collaboration between providers and payers. Since 2013, the company has grown rapidly, with recognition on the Inc. 5000 and Deloitte Technology Fast 500 lists, and fosters a passionate, fast-moving culture.
Architect and execute Machine Learning solutions, develop Large Language Models (LLMs), and build the AI stack to automate complex Data Analytics workflows.
Own the AI stack roadmap from opportunity sizing through prototyping to deployment and impact measurement.
Translate complex technical work into clear recommendations for senior stakeholders and mentor analysts.
JumpCloud is an AI-powered unified IT management platform that secures the modern workforce by consolidating identity, device, and access management. With teams in 15+ countries, it is a fast-paced, SaaS-based environment that values innovation and collaboration.
Build and operate containerized services using orchestration platforms such as Kubernetes.
Develop maintainable and well-tested Python code for production services, automation, and internal tooling.
Implement data and model versioning, validation, and observability to support integrity and reproducibility throughout the ML lifecycle.
Redcare Pharmacy is Europe's No.1 e-pharmacy, dedicated to providing health products and services. With a focus on innovation and collaboration, the company fosters a supportive culture where employees are valued.
Design, build, deploy, and maintain scalable machine learning and AI systems in GCP to solve complex business problems and create new value.
Partner across teams to understand problem definitions, data needs, and solution approaches, and support model deployment with MLOps practices.
Take ownership of production issues, perform root cause analysis, and improve documentation and quality assurance processes for ML systems.
General Mills makes food the world loves, operating across 100+ markets. As a large company, it prioritizes being a force for good and fosters a culture of bold thinking and big hearts, where employees challenge each other and grow together.
Architect and maintain end-to-end traffic classification ML systems
Build rigorous evaluation frameworks to ensure model improvements are measurable
Partner with security and data engineering teams to integrate scoring intelligence
Airbnb is an online marketplace that connects hosts with guests, offering unique stays and experiences. Founded in 2007, the company has grown to over 5 million hosts and 2 billion guest arrivals, with a culture committed to inclusion and belonging.