Top Machine Learning Engineer Jobs

Lead the design, development, and deployment of machine learning models, collaborating with teams and mentoring engineers. Focus on scalable ML workflows.

The role involves leading machine learning engineering efforts, developing models and software, optimizing data pipelines, and mentoring engineers while collaborating with various teams.

As a Senior Machine Learning Engineer at Capital One, you'll design, build, and deploy ML models, collaborate in Agile teams, and ensure the performance of ML applications. Responsibilities include model training, monitoring, and optimization in cloud-based environments.

As a Senior Software Engineer, you will tackle challenges in networking, autonomy, and systems integration, collaborate with teams, and ensure successful product deployment in military environments.

Lead robot learning and perception development for manufacturing systems, guiding engineering from prototype to production and advancing embodied AI.

The Senior Machine Learning Engineer at Chewy will develop and deploy ML models for sponsored ads, collaborating across teams to optimize advertising strategies. Responsibilities include model ideation, experimentation, and mentoring junior scientists while communicating insights to leadership.

The role involves developing machine learning models for sponsored ads, improving selection and ranking, and collaborating with product teams to optimize advertising solutions.

Lead the development of AI/ML systems in robotics and manufacturing, designing ML architectures, and collaborating with cross-functional teams.

Develop scalable ML platform infrastructure, support ML training and deployment, collaborate on software tools for scientists, and enhance workflows and automation.

As a Data Engineer with AI/ML expertise, you'll develop AI-driven solutions, optimize data workflows, and collaborate with teams in healthcare data management.

Design, implement, and deploy scalable ML training and evaluation platforms. Own end-to-end projects, make architectural decisions, drive prioritization, collaborate cross-functionally, and mentor engineers to accelerate autonomous driving model development.

Build and deploy scalable ML training and evaluation platforms, drive technical projects and architectural decisions, collaborate with partner teams, prioritize platform improvements, ensure reliability and performance, and mentor junior engineers.

The Data Engineer will build real-time data pipelines for pricing algorithms, collaborate with teams, and contribute to batch data workflows.

The Senior Data Engineer will develop real-time streaming data pipelines for pricing algorithms and machine learning models, ensuring low-latency data delivery and system reliability. Responsibilities include collaborating with other teams, defining architectural standards, and mentoring junior engineers.

The Senior Machine Learning Engineer will design, develop, and implement ML applications, collaborating with teams to solve business problems, and ensuring the models are maintained and optimized in production.

The Senior AI/ML Capacity Engineer will develop capacity planning models, design analytical tools, and collaborate with teams to optimize costs and efficiencies.

The Lead AI/ML Engineer will develop AI systems, optimize ML models, collaborate with teams, and mentor junior members while ensuring quality in software projects.

As a Sr. Machine Learning Engineer, you'll develop ML solutions for healthcare, manage data pipelines, write production-ready software, and own ML services end-to-end.

Design and build Go backend services on AWS to support scalable AI/ML workloads. Develop core platform components (feature store, orchestration, model serving), deploy GenAI apps, optimize infrastructure and CI/CD, and collaborate with data scientists, ML engineers, and product teams to deliver end-to-end ML solutions.

Lead the design and deployment of machine learning models to detect fraud, collaborating with teams to optimize performance and effectiveness while integrating solutions into existing systems.

Design, build, and productionize scalable ML systems for physiological time-series data. Collaborate with data scientists, engineers, and product teams to deploy reliable, low-latency inference services, improve ML pipelines, and maintain production uptime.

Design and scale ML platform infrastructure for large 3D datasets: build training pipelines, deploy generative models, optimize ML lifecycle, ensure cloud-native reliability and observability, and collaborate across engineering.

Lead development of advanced recommendation systems, driving ML innovation, maintaining ML pipelines, and collaborating across teams to enhance user engagement.

As a Senior Machine Learning Engineer, you will design and implement machine learning models, collaborate with Agile teams, and ensure the performance and scalability of solutions.

As a Machine Learning Engineer, you will develop, implement and deploy ML models, collaborate with teams, and ensure model performance while working with healthcare datasets.