Top Machine Learning Engineer Jobs in Los Angeles, CA

Interns will design, build, and deploy machine learning models that enhance Netflix's services, collaborating with various teams to translate business needs into ML solutions.

Assist in designing, developing, and deploying machine learning models for creating high-quality 3D assets while collaborating with cross-functional teams.

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.

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.

Lead the modeling strategy for ML Bots, developing predictive features, designing ML systems, mentoring engineers, and collaborating cross-discipline to enhance player experiences within games.

Define and lead modeling architecture for personalization, matchmaking, recommendations, and social discovery. Build large-scale real-time inference systems, develop models for skill, behavior, trust & safety, and multi-objective optimization. Drive Responsible AI, experimentation, observability, and cross-functional standards while mentoring senior engineers and influencing ML strategy.

Design and maintain scalable machine learning infrastructure, collaborating with data scientists, ensuring performance, security, and compliance of AI systems.

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

As a Senior Machine Learning Engineer, you will design ML infrastructure, lead zero-to-one initiatives, collaborate on projects, and enhance scalability in the development of ML applications.

The Machine Learning Engineer will develop software solutions, optimize data pipelines, and deploy machine learning models using cloud platforms and best practices.

The role involves building AI technologies for customer service, developing ML systems, and collaborating with cross-functional teams to enhance user experiences.

The Forward Deployed ML Engineer will integrate AI/ML models into clinical software, assist in model fine-tuning, and engage with clients to ensure success in healthcare deployments.

Join a team focusing on end-to-end ML Ops for the insurance sector. Develop and deploy ML solutions, build infrastructure, and solve business challenges using advanced technologies.

As a Machine Learning Engineer at Shipwell, you'll build and scale AI-powered logistics solutions, maintaining data pipelines and ML infrastructure across the organization.

Work on Wayfinding projects using LLMs and agentic workflows, collaborate with engineering/product/research teams, receive mentorship, and gain hands-on experience with model evaluation, prompt engineering, and shipping code in a real engineering environment.

The Machine Learning Engineer will design, train, deploy, and maintain ML systems for automation, forecasting, and analytics in music and entertainment. Responsibilities include ML model development, MLOps tooling, and collaboration with other teams.

The AI/Machine Learning Engineer will develop systems for automating health benefits decisions, integrating large language models with rule-driven patterns, and ensuring compliance with regulations.

Lead the advancement of embedding-based retrieval systems, focusing on multimodal models, model performance, and extensibility for various use cases.

The role involves designing, optimizing, and deploying machine learning models for edge environments, focusing on computer vision. The engineer will collaborate with teams to integrate models and improve inference efficiency while mentoring peers and upholding company values.

Lead the ML and AI engineering team, strategizing and implementing AI solutions for business growth, mentoring staff, and collaborating across departments.

As a ML Engineer focused on inference, you'll design and optimize deep learning models for real-time communication AI applications, collaborating with cross-functional teams and ensuring production readiness.

Lead definition and implementation of the companys ML strategy and infrastructure. Build end-to-end production ML systems (data pipelines, training, evaluation, serving), own data strategy and feedback loops, integrate ML with product/backend, write production-quality code, and recruit/mentor the ML team as it scales.

Design, architect, and deploy generative AI/LLM solutions from prototype to production; work directly with clients to translate business needs into technical plans; write production-quality code integrating LLMs and ML models; collaborate with cloud, DevOps, and frontend teams; support proposals, sales, and evaluation/observability of models.

The Machine Learning Engineer will develop and maintain scalable ML systems, collaborate across teams, and innovate solutions for real-time applications to enhance customer experiences.

Lead modeling strategies for AI Bots in League of Legends by developing and implementing ML systems, collaborating with teams, and ensuring player experience enhancement through advanced ML methods.