Top Machine Learning Engineer Jobs

Design and deploy production-grade ML systems, integrate models into software pipelines, and develop features leveraging ML for optimization and prediction problems.

Develop and deploy machine learning solutions for autonomous vehicles, mentoring engineers and collaborating on model implementations.

Lead the design, implementation, and deployment of scalable ML infrastructure for autonomous driving. Drive technical projects, mentor others, and collaborate with teams to enhance ML workflows.

The role involves building machine learning systems for Radar's products, focusing on core ML infrastructure, anomaly detection, geolocation, and collaboration with customers.

As a Staff Machine Learning Engineer, you'll enhance credit products through advanced modeling techniques, data analysis, and ML operations, supporting robust decision-making processes.

As a Staff Machine Learning Engineer, you will enhance credit modeling, manage full credit modeling stacks, and support innovations within regulated banking frameworks.

Senior individual contributor building and maintaining underwriting and credit decisioning ML systems for Cash App Borrow and Afterpay. Responsibilities include feature engineering, model training, calibration, experimentation, deployment, monitoring, and portfolio-level analysis. Collaborate with cross-functional teams to align models with business and regulatory goals and develop AI-native engineering workflows and governance for reliable, auditable model development.

Own and architect the core ranking system end-to-end: model design, production reliability, automated retraining, bias mitigation, personalization, and cross-functional technical leadership. Mentor engineers, drive roadmap, and scale experimentation and ML infrastructure.

Lead design, implementation, and scaling of end-to-end ML systems including feature pipelines, model training, evaluation, deployment, and monitoring. Partner with cross-functional teams to productionize models, apply MLOps best practices (automated retraining, CI/CD, drift detection), and mentor engineers to maintain high code and system quality.

The Staff Machine Learning Engineer will develop machine learning models to enhance advertising strategies, improving relevance, ranking and customer engagement for Chewy's sponsored ads.

Design, build, and deploy production-grade AI/ML and LLM solutions for claims processing, eligibility, prior authorization, and payment integrity. Build scalable data pipelines, integrate models with core payer systems, ensure HIPAA/PHI-safe pipelines and Responsible AI governance, monitor and retrain models, and partner with cross-functional teams to deliver reliable, CI/CD-driven solutions.

As a Sr. Staff Machine Learning Engineer, you will drive the development of cloud security features, leveraging AI/ML to solve real-world challenges and optimize production systems.

As a Machine Learning Engineer, you will enhance internal libraries for deep learning, collaborate with researchers, and optimize workflows for cost savings.

Lead the development of production-grade ML systems, aligning technical roadmaps with company priorities, mentoring ML engineers, and ensuring ethical use of ML/AI.

Lead technical direction and delivery of ML platform infrastructure (feature store, model serving, experimentation, training pipelines). Drive architecture, resolve system-level issues, write production code, mentor engineers, and partner with ML, data, and product teams to enable scalable, reliable ML model development and deployment.

Own the research-to-production pipeline: harden training/evaluation workflows, build packaging/deployment tooling, design release gates, optimize inference and serving for latency/throughput, establish benchmarking and validation, and instrument feedback from production to accelerate research iteration.

Design and implement generative ML systems (image, video, audio, multimodal LLMs) and deliver on-device and server-side inference. Build GenAI pipelines and AR experiences, prototype with cross-functional teams, and optimize efficient models for real-time mobile and wearable applications.

Lead vision and roadmap for large-scale recommender systems across Spotlight, Discover, and Friend Stories. Technically lead engineering teams, design next‑generation recommender and retrieval architectures, incorporate SOTA research and foundation models, advance ML infrastructure for scalability and reliability, and partner cross-functionally to drive experimentation, operational excellence, and cost-effective production deployments.

The Staff Machine Learning Engineer will lead the development of search ranking systems, focusing on machine learning models for relevance, quality, and personalization through various advanced techniques and collaboration with cross-functional teams.

Design, build, and deploy scalable AI/ML models and pipelines for consumer healthcare. Develop production code (Python/Java/Scala), automate infrastructure (Terraform, Kubernetes), validate model performance, integrate cloud services (Azure/AWS), and collaborate cross-functionally to monitor and document enterprise-scale AI solutions.

As a Machine Learning Engineer, you will develop machine learning models, automate data engineering pipelines, and support customer-centric projects while collaborating with data scientists and engineers.

The Staff Machine Learning Engineer will design, build, and optimize machine learning models and scalable data pipelines while collaborating with cross-functional teams to enhance Micron's products using AI/ML techniques.

As a Staff Applied AI Scientist, you will design and deploy AI systems using LLMs, improve agent performance, and collaborate with engineering to enhance systems for customer impact.

As a Principal AI/ML Engineer, you will lead the development of machine learning solutions for advertising, focusing on optimization, personalization, and deploying models within a highly scalable infrastructure.

The Principal AI/ML Engineer will develop advanced ML models for the AdTech platform, lead system design, and collaborate across teams to optimize advertising strategies using AI.