Top Machine Learning Jobs

The Staff Machine Learning Engineer leads the design and implementation of machine learning solutions, collaborating with product teams, and ensuring robust product performance and support.

The role involves developing and deploying machine learning models, conducting analytical studies, and integrating solutions into software. Responsibilities include mentoring team members and improving decision-making using data insights.

The Machine Learning Engineer Intern will build and operate AI-driven application pipelines, working with Data Scientists and Engineers to support cloud-based ML solutions.

As a Senior Machine Learning Engineer in the Health team, you'll design and productionize ML systems for personalized health metrics, collaborating with data scientists and engineers to optimize performance and ensure service reliability.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

As a Senior Machine Learning Engineer, you will develop machine learning models, manage their lifecycle, build infrastructure, and collaborate with teams to enhance our capabilities in various ML areas.

The Machine Learning Engineer will develop and optimize large-scale ML models, build low-latency inference pipelines, and collaborate with teams to enhance performance and automate ML processes.

As a Senior AI/ML Scientist, you'll integrate AI/ML into engineering tools, develop predictive models, analyze data, collaborate with teams, and establish best practices in a hybrid role.

As a Senior ML Engineer, you'll design and deploy advanced machine learning systems for autonomous vehicles, ensuring real-time performance and robustness in diverse conditions. You'll lead technical projects, mentor engineers, and collaborate across teams to enhance onboard capabilities.

As an Applied Machine Learning Engineer, you will develop AI and ML models to improve healthcare outcomes. Collaborate with teams to implement and optimize machine learning techniques and algorithms.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

As a Machine Learning Engineer Intern, you will develop an AI assistant, implement RAG architecture, create data pipelines, and fine-tune LLMs to handle internal queries about autonomous driving data.

Lead and grow the Machine Learning Engineering team, set technical direction, define team roadmap, and collaborate across product and engineering teams.

The Lead Machine Learning Engineer at Capital One will design and implement ML applications, collaborate with teams, and optimize data pipelines.

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

Develop and scale machine learning training systems for robotics data, optimize training pipelines, and collaborate with ML researchers to enhance autonomy models.

The Machine Learning & AI Engineer develops and deploys ML and AI systems for the Energy Industry, focusing on data quality and interpretability. Responsibilities include model design, pipeline development, AI agent systems, and collaborating with cross-functional teams.

As a Senior Developer, you will build and evolve ML/AI applications on AWS, collaborating with teams to deliver effective solutions and ensure model accuracy.

The Machine Learning Engineer at Lyft will design, build, and deploy ML models across various domains, collaborating with data scientists and product managers to solve complex business problems at scale.

The Software Engineer will develop scalable, high-quality AI applications for environmental conservation, working on projects utilizing ML models and cloud technology.

As an AI/ML Engineer, you will develop machine learning models, collaborate across teams, and support innovative data solutions for clients.

Design, build, and deploy scalable AI and ML solutions, translate business challenges into technical solutions, and collaborate with teams on model performance optimization.

Lead applied machine learning research to improve validation of ML components in autonomous vehicles, focusing on simulation-led strategies and automating validation processes.

Design, train, optimize, and deploy efficient on-device ML models (audio and vision) for resource-constrained products; maintain Ambiq ADKs; port and optimize customer models; apply model-efficiency techniques; produce customer-facing demos, docs, and benchmarks.

As a Lead Machine Learning Engineer, you'll design, develop, and implement ML applications, collaborating with teams to ensure high performance and scalability of ML systems.