Top Machine Learning Jobs

Lead and grow a small ML engineering team while staying hands-on: design and ship GenAI features, build agentic LLM systems (NER, classification, retrieval, summarization), partner with PM and engineering, scope ambiguous problems, and reduce COGS through ML automation.

Build and validate production-grade ML and AI systems across pricing, underwriting, claims, and portfolio management. Work with structured and unstructured data, LLMs and agentic workflows, extract information from documents, resolve entities, create feature pipelines and inference services, quantify uncertainty, monitor drift, and measure business impact in collaboration with engineers, actuaries, underwriters, and product teams.

Lead and grow a team of ML engineers building production ML systems for Fetch's Ad Platform. Translate product strategy into roadmaps, guide design and implementation of models for ranking, targeting, bidding and forecasting, set metrics and experimentation, enforce architectural and operational standards, manage trade-offs across performance and reliability, and drive cross-functional alignment to improve advertiser and member outcomes.

Design, implement, and optimize machine learning and deep learning models; preprocess and analyze large datasets; integrate models into production; monitor performance and troubleshoot; collaborate with engineers, data scientists, and stakeholders; stay current with ML/AI advances.

Design, implement, and optimize ML and deep learning models; preprocess and prepare large datasets; integrate models into production; monitor and maintain model performance; collaborate with engineers and stakeholders; stay current on ML/AI advances.

Develop and deploy end-to-end ML solutions for smart manufacturing: build data pipelines, feature engineering, CV and LLM-based models (RAG/agentic workflows), prototype and productionize models, implement monitoring/retraining, and collaborate with cross-functional teams using modern development and CI/CD practices.

Own and build end-to-end matching and ranking systems for out-of-home advertising: design candidate generation, re-ranking, geospatial scoring, data warehouse and feature pipelines, evaluation infrastructure, low-latency ranking APIs, and model monitoring with drift detection and retraining triggers.

Responsible for developing machine learning capabilities, partnering with Data Scientists, and enhancing customer experiences through AI solutions.

Own end-to-end matching and ranking systems for out-of-home advertising: design candidate generation and re-ranking models, build and manage data warehouse and pipelines, implement evaluation and monitoring, publish low-latency ranking APIs, and maintain model observability and retraining workflows.

Design, develop, and maintain real-time deep learning pipelines and production ML microservices on Kubernetes. Curate datasets, establish benchmarks, improve observability and monitoring, and scale ML workflows. Collaborate with product, backend, and systems teams, contribute to R&D for aerospace/defense use cases, and document operational best practices.

Design, train, test, deploy, and maintain ML models for national-security cyber applications. Collaborate with software engineers and data scientists to build LLM-based automation, fine-tune open-source models, containerize solutions, and define ML strategy for mission-critical systems while meeting security requirements.

Design, train, and deploy multimodal machine learning systems that fuse 3D/vision, simulation, tabular, and text data. Own end-to-end model lifecycle from architecture and training to evaluation, production deployment, and monitoring, and build agentic workflows and retrieval/embedding capabilities to support underwriting and mitigation decisions.

Seeking a Machine Learning Engineer to apply AI technologies in high frequency trading, focusing on automation and collaboration with AI research.

Work on training, evaluating, and deploying ML models and inference systems for low-payload robotic arms. Run experiments, analyze results, and support testing and deployment on real robotic hardware while collaborating with researchers, engineers, and hardware teams.

The Senior Machine Learning Engineer will automate healthcare compliance workflows using AI to process unstructured data, build multimodal AI pipelines, and develop extraction systems, ensuring high reliability and operational efficiency.

The Machine Learning Engineer will execute the full ML lifecycle, collaborating on model implementation and improving customer experiences through data-driven insights.

The Machine Learning Engineer will design, implement, and optimize reinforcement learning models for autonomous driving systems, enhancing data systems for scalable evaluation and performance assessment.

Develop, deploy, and integrate machine learning and deep learning models for scientific and industrial problems (materials, chemistry, process optimization). Build data pipelines, feature engineering, model evaluation, and scalable production integrations. Collaborate with scientists, engineers, product, and customer teams to translate domain problems into AI solutions, support deployments, and communicate results. Conduct strategic research and stay current with AI/ML methods; periodic customer travel.

Lead the development and deployment of large-scale machine learning models, optimize model performance, and enhance collaboration across teams while mentoring junior engineers.

The AI / Machine Learning Engineer will design, build, and deploy ML models for image classification, fraud detection, and data pipelines, while collaborating with product and engineering teams.

Design, build, and deploy machine learning solutions. Collaborate with teams to transform research into practical applications using large datasets.

Lead the end-to-end machine learning lifecycle for AI products, managing data pipelines and model development to optimize performance and accuracy in production.

The role involves designing de novo frameworks for molecular engineering, collaborating across teams to optimize data-driven biological experiments and integrating ML models with experimental systems.

As a Machine Learning Engineer, you will design and train perception models for robotics, focusing on 3D perception systems. You will tackle complex physical challenges, optimize models for embedded hardware, and collaborate with cross-functional teams.

Design, build, and deploy machine learning software and data pipelines for production government environments. Integrate and optimize distributed/cloud services, ensure code quality, lead reviews, mentor teammates, and engage directly with clients.