Top Machine Learning Engineer Jobs

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 AI/ML initiatives, design and implement AI-powered solutions, mentor team members, and ensure compliance in healthcare projects.

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.

The Principal Machine Learning Engineer will lead AI/ML product development, drive innovation, and collaborate across teams to enhance machine learning frameworks.

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 role involves designing, developing, and deploying machine learning models and systems, collaborating with engineers and product teams to ensure reliable and scalable solutions while mentoring junior engineers.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

Lead the design and delivery of scalable voice and chat solutions using Amazon Connect, focusing on integrations, reliability, and performance optimization.

The Staff Machine Learning Engineer will design and build scalable ML systems for health insights, collaborating with cross-functional teams to ensure compliance and quality in production-ready services.

Develop and implement machine learning solutions using LLMs and the LangChain framework. Ensure production quality code and utilize various ML techniques and containerization tools.

As a Lead AI/ML Engineer, you will design and implement AI solutions in clinical workflows, mentor junior engineers, and drive full stack application development and operationalization in a healthcare environment.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

As a Machine Learning Engineer in Fraud Risk, you'll build and maintain ML systems for fraud detection and anomaly analysis, ensuring robust performance and real-time decision making.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

The role involves designing and operating AI systems, building data pipelines, fine-tuning models, and mentoring team members while collaborating with product and data science teams.

The Machine Learning Engineer will design, build, and deploy ML applications at scale, collaborating with cross-functional teams and applying best practices in ML engineering and cloud technologies.

The role involves designing and building production systems for AI agents, implementing algorithms, mentoring engineers, and collaborating with experts on enhancing AI products.

The role involves building and optimizing ML infrastructure for large language models, collaborating with cross-functional teams, and driving ML best practices.

Develop large-scale Foundation Models for Autonomous Driving & Robotics, collaborating with teams, optimizing model performance, and mentoring junior members.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

The Principal Machine Learning Engineer will lead ML initiatives, integrate ML services, mentor engineers, and drive ML strategy within Ibotta, ensuring scalable solutions are implemented effectively across teams.

Develop and deploy Generative AI solutions, partner with teams to integrate systems, optimize AI models, and stay current with AI advancements.

The Machine Learning Engineer will design, implement, and manage complex ML algorithms, focusing on computer vision and data analysis while collaborating with team members to transition algorithms to production.

The Machine Learning Engineer will design, implement, and manage complex ML algorithms, focusing on computer vision, testing algorithms, and transitioning them to production. Responsibilities include tracking advancements in ML, conducting experiments, and writing maintainable code.

Design, implement, and manage complex machine learning algorithms with a focus on computer vision. Experience in MLOps, cloud platforms, and testing AI technologies is essential.