Top Machine Learning Jobs

Lead a Labs team as a hands-on engineer building hybrid AI/optimization systems: design ML-augmented optimization, prototype and productionize solutions, architect MLOps/CI-CD, benchmark solvers, mentor engineers, and collaborate with researchers and stakeholders to scale reusable components and APIs across Kroger.

Build and re-architect Shipt's LLM-native search stack including retrieval and ranking systems. Design multi-task and multi-objective models, integrate personalization signals, develop hybrid dense/sparse retrieval, and apply generative retrieval and query expansion. Analyze search data, report findings to leadership, and partner with senior scientists and ML engineers to improve relevance, revenue trade-offs, and operational metrics.

Design, develop, and deploy AI-native solutions for defense customers. Build and integrate ML/LLM models, agentic workflows, and full-stack applications, collaborating with engineers and mission experts while following Agile and DevSecOps practices. Support model development, data handling, and rapid iteration to deliver mission capabilities.

The Senior Machine Learning Engineer at Grailed will enhance personalization and recommendations, develop AI/ML solutions, and collaborate across departments for data-driven insights.

Lead end-to-end ML data programs for autonomous vehicle models: define dataset requirements, develop labeling policies, build evaluation frameworks and metrics, coordinate cross-functional teams, and drive data selection strategies to maximize labeling ROI and model performance.

The Senior Machine Learning Engineer will design, develop, and deploy machine learning solutions for Vitol, working across trading and operations with various stakeholders.

As a Machine Learning Engineer at Onyx, you will enhance agent and knowledge retrieval capabilities by implementing LLM-based graphs and advanced NLP algorithms, while collaborating with the team to improve user experience and product direction.

The Machine Learning Engineer role involves optimizing models for performance, utilizing CUDA, GPU scheduling, and collaborating on ML systems design.

The Senior Software Engineer will develop and optimize algorithms and ML models for mobile, embedded, and cloud environments. Responsibilities include collaborating with cross-functional teams, deploying algorithms, analyzing performance, and ensuring code quality.

As a Machine Learning Engineer at Yobi, you will design and optimize systems for real-time model serving and inference, ensuring performance and reliability.

Develop and deploy machine learning models for decision-making in autonomous trucks, focusing on learned behavior systems and model performance improvements.

Develop algorithms in machine learning and statistics to address complex challenges. Design data pipelines and deploy solutions using cloud infrastructure.

As an ML Engineer, develop and deploy advanced ML solutions for OCR, document processing, and voice technologies, collaborating with teams to optimize models for performance.

As an AI/ML Engineer, you will design and deploy models for real-world applications, optimize data pipelines, and engage with global leaders to enhance AI technology's impact across sectors like healthcare and government.

The ML Engineer will develop and deploy machine learning models, collaborate with teams, analyze datasets, and improve model performance.

Lead a team of data scientists developing ML-driven products, managing infrastructure, training models, and ensuring production quality while collaborating with senior leadership.

The Senior Machine Learning Engineer will design, train, and evaluate ML models to solve complex problems, mentor others, and optimize production systems.

As a Machine Learning Engineer, you will design, build, and deploy ML models for underwriting at Stripe Capital, ensuring performance while collaborating with multiple teams.

As a Senior Machine Learning Engineer, you'll design data pipelines, develop prediction systems, and optimize model deployment processes while collaborating with cross-functional teams.

The Senior Machine Learning Engineer will lead applied research projects, design and implement ML models, maintain data pipelines, and mentor junior members for defense-focused missions.

The role involves developing and maintaining behavioral models for road users to enhance autonomous vehicle decision-making, collaborating with other teams and optimizing outputs for safety and effectiveness.

The role involves designing, training, and evaluating ML models, optimizing performance, and collaborating with teams to implement AI technologies in products.

Design and implement backend and systems-level software for defense and intelligence, integrating signal-processing and machine-learning algorithms into real-time, field-ready systems. Collaborate in small teams to prototype, architect, and deploy extensible solutions that integrate with existing infrastructure while translating customer requirements into development priorities.

Design and deploy end-to-end machine learning solutions: gather/process large datasets, build predictive and topic-modeling systems, develop data pipelines, use AWS and NLP APIs, containerize and deploy models, lead technical teams, and manage project delivery and stakeholder communication.

Own and improve recommendation and search systems across feed, discovery, and search. Build retrieval and ranking (candidate generation, embeddings, two-tower models), run experiments, create user/content/session representations, and ship production ML systems with monitoring to improve retention, engagement, and content distribution.