Top Machine Learning Engineer Jobs

Design, train, deploy, and maintain machine learning models and pipelines for EO/IR image processing and computer vision applications. Build deep learning systems for object detection, segmentation, tracking, and video analysis; collaborate with AI and engineering teams; prototype solutions, troubleshoot systems, and evaluate emerging ML techniques for operational space systems.

Develop, train, validate, deploy, and maintain deep learning models and machine learning pipelines for electro-optical and infrared image processing. Responsibilities include data ingestion, feature engineering, computer vision, rapid prototyping, operational system integration, troubleshooting, and collaboration with AI and engineering teams. The role supports defense and intelligence space programs and requires U.S. citizenship and the ability to obtain and maintain a government security clearance.

Develop and deploy machine learning models and pipelines for electro-optical and infrared image processing applications. Responsibilities include designing, training, validating, and maintaining deep learning models; building data ingestion, feature engineering, training, and inference pipelines; prototyping solutions for operational systems; troubleshooting software; collaborating on AI and computer vision projects; and evaluating emerging ML tools and techniques.

Develop and deploy deep learning models for electro-optical and infrared image processing supporting space-based defense and intelligence missions. Responsibilities include building ML pipelines for data ingestion, feature engineering, training, and inference; collaborating on computer vision and AI solutions; prototyping, integrating, troubleshooting, and maintaining operational systems; and evaluating emerging ML research, tools, and frameworks.

Designs, trains, deploys, and maintains machine learning models and pipelines for electro-optical and infrared image processing. Develops deep learning solutions for computer vision, including object detection, segmentation, and tracking. Collaborates with AI and engineering teams, prototypes solutions for operational systems, troubleshoots software, and evaluates emerging ML tools and techniques.

Develop and deploy deep learning models for electro-optical and infrared image processing supporting space-based defense and intelligence missions. Build ML pipelines for data ingestion, feature engineering, training, and inference; collaborate on AI, machine learning, and computer vision solutions; prototype systems for operational integration; troubleshoot and maintain software; and evaluate emerging ML tools and techniques.

Build and operate production machine learning systems for Airbnb Payments, including LLM agents, real-time fraud detection, anomaly detection, personalization, and checkout optimization. Design, train, deploy, monitor, and continuously improve batch and streaming AI applications at global scale. Partner with product, engineering, operations, and data science teams, establish model governance and testing standards, and mentor engineers.

Develop and deploy models to understand technical drawings and specifications, perform multimodal reasoning across diagrams, text, and structured data, translate research into production within ~1 year, present prior research, and collaborate closely with founders to deliver customer-impacting applied research.

Build core, shared ML capabilities for a production platform: foundation models for documents, extraction agents, model routing, unified evaluation, and continuous improvement pipelines. Own end-to-end capability development, production deployment, and cross-team support to improve accuracy, latency, cost, and reliability across institutional workflows.

As a Machine Learning Engineer, you'll build and enhance features for a search stack, design ML/NLP solutions, and implement an experimentation framework while ensuring code quality.

Develop and deploy machine learning models for national security challenges. Responsibilities include algorithm development, model training, deployment, and collaboration with teams for effective ML solutions.

Build, train, fine-tune, evaluate, and deploy machine learning and LLM models for production. Create monitoring, evaluation, and feedback tooling, evaluate new techniques, and collaborate cross-functionally to ship ML-powered features.

Build and deploy agentic, full-stack AI systems using LLMs, embeddings, RAG, and agent orchestration for defense and intelligence customers. Collaborate with customers, operate in classified/air-gapped environments, codify reusable patterns, and support end-to-end delivery from prototype to production.

As a Machine Learning Engineer, design imaging algorithms, build acoustic simulations, and develop computer vision systems to enhance brain imaging technology.

The role involves training and fine-tuning vision and language models, building evaluation and learning pipelines, and optimizing model performance.

Designs, evaluates, and deploys applied machine learning systems across language, vision, recommendation, and structured-data domains. Responsibilities include developing scalable training and inference pipelines, conducting rigorous experiments, optimizing models, managing data quality, implementing safety and fairness evaluations, and translating research into production solutions. The role also involves collaborating with product and platform teams, documenting findings, mentoring engineers, and influencing AI strategy.

Develop and implement automation for ML technology integration, including data pipelines, AI/LLM integrations (Databricks, Bedrock), malware analysis workflows, feature engineering automation, API integrations, monitoring, and scaling automation from pilot to production while collaborating with analysts and maintaining documentation.

The Machine Learning Engineer will design and build scalable ML data pipelines, manipulate 3D data, collaborate with customers, and ensure reliable deployment of ML systems.

The Applied ML Engineer will research and build AI/ML systems, own model development, partner with teams to impact marketplace metrics, and establish best practices for AI/ML at Paraform.

Design and implement AI agents for mission planning and orchestration across autonomous systems, focusing on LLM frameworks and edge computing.

The Senior Staff Machine Learning Engineer will improve Coupang's search and discovery systems using advanced algorithms, addressing bottlenecks, proposing solutions, and leading projects involving personalization and recommendations.

As a ML Engineer at Apiphany, you will develop advanced machine learning models, focusing on engineering data, AI systems, and real-world performance.

Design and implement 3D machine learning models, process reality capture data, and integrate AI solutions in production environments for robotics applications.

The Staff Machine Learning Engineer will lead AI initiatives, architect LLM systems, design evaluation frameworks, and mentor engineers.

The Machine Learning Engineer role at Wayve focuses on leading initiatives in model-based autonomous driving, involving the development and delivery of ML-driven behaviors, collaboration across teams, and mentoring other engineers.