Top Machine Learning Engineer Jobs in Los Angeles, CA

Build and maintain MLOps pipelines, deploy and monitor ML models as scalable services, transform and integrate healthcare data (FHIR/HL7), ensure reproducible feature management, and uphold HIPAA/HITRUST security for production ML in clinical systems.

As a Staff Machine Learning Engineer, optimize card pricing models, lead ML lifecycle, collaborate with experts, and enhance predictive features.

The Machine Learning Engineer will design and deploy computer vision models, build training pipelines, and enhance ML infrastructure to improve agricultural field operations.

Design and implement scalable machine learning pipelines, collaborate with cross-functional teams, ensure deployment standards, and champion best practices in observability and monitoring.

The role involves building ML systems, improving models across product surfaces, and leveraging data for personalization and user engagement.

The Research Engineer will collaborate with scientists to develop and validate machine learning models for speech technologies, manage scalable training systems, and design tools for accessibility to non-technical users.

Design and implement machine learning algorithms for robotic manipulation, focusing on RL and IL. Collaborate across disciplines to ensure integration and successful deployment.

As a Machine Learning Engineer, you will design and build AI capabilities, develop scalable ML infrastructure, and collaborate on production systems in the real estate domain.

Build and optimize machine learning models for 3D dental applications, research state-of-the-art methods, and implement MLOps best practices.

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

As a Machine Learning Engineer, you will own the full lifecycle of ML from model development to production deployment, collaborating with teams to drive ML processes.

As a Machine Learning Engineer, you will fine-tune transformer models, deploy machine learning solutions, and work with cross-functional teams on innovative projects.

As a Staff Machine Learning Engineer - AI Tech Lead, you will lead the design of AI systems for security operations, focusing on scalable architectures, AI safety, and mentoring. Responsibilities include overseeing technical evaluations, production workflows, LLM fine-tuning, and collaboration with teams to enhance AI capabilities.

The Senior Databricks AI/ML Engineer will design and deploy AI/ML solutions in the insurance sector, focusing on Databricks architecture, data pipelines, and MLOps workflows, while collaborating with various teams to operationalize models and optimize processes.

The Machine Learning Engineer will develop ML infrastructure, optimize models for anomaly detection, and manage technical projects to enhance space cybersecurity.

The Senior AI/ML Engineer will design, build, and deploy Generative AI and ML platforms, ensuring compliance and high performance. Responsibilities include developing foundational services, overseeing model training infrastructure, and mentoring junior engineers.

As a Sr. AI/ML Engineer III, you will design and implement reinforcement learning algorithms, integrate them into simulation environments, and evaluate their performance. Collaborating with engineering teams, you will ensure the maintainability and transparency of AI components while communicating results and recommendations clearly.

Lead technical direction and execution of Lime's CX automation platform, building scalable backend services, decision engines, and human-in-the-loop workflows to automate rider issue resolution while enforcing fraud and trust guardrails and improving operational metrics.

Design, build, and maintain scalable AI/ML architectures; collaborate with data scientists, engineers, product, and compliance to integrate models; evaluate tools and processes; monitor performance and ensure industry-standard compliance and ethical practices.

The Azure AI/ML Engineer will design and implement AI solutions on Azure, focusing on automation, security, and compliance in collaboration with various teams.

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 Machine Learning Engineer will fine-tune and deploy Large Language Models, optimize ML models, maintain data pipelines, and collaborate on AI features.

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.

The Staff AI/ML Engineer will lead AI product development, ensure system health, and collaborate with teams on product features while maintaining security and compliance.