Top Machine Learning Jobs in Los Angeles, CA

Lead the development of fraud prediction models using machine learning, collaborating across teams to build, scale, and monitor models in production.

The role involves deploying and supporting CrowdStrike's AI capabilities in cybersecurity, optimizing threat detection, and mentoring teams on AI solutions.

Lead a team of ML engineers to develop fraud detection models, defining strategies, driving model evolution, and ensuring effective integration with cross-functional teams.

The role involves designing and operating real-time AI systems for sports analysis, integrating various data signals under tight constraints and mentoring other engineers.

As a Staff Applied AI Scientist, you will design and deploy AI systems using LLMs, improve agent performance, and collaborate with engineering to enhance systems for customer impact.

Lead vision and roadmap for large-scale recommender systems across Spotlight, Discover, and Friend Stories. Technically lead engineering teams, design next‑generation recommender and retrieval architectures, incorporate SOTA research and foundation models, advance ML infrastructure for scalability and reliability, and partner cross-functionally to drive experimentation, operational excellence, and cost-effective production deployments.

Design and implement generative ML systems (image, video, audio, multimodal LLMs) and deliver on-device and server-side inference. Build GenAI pipelines and AR experiences, prototype with cross-functional teams, and optimize efficient models for real-time mobile and wearable applications.

The Staff Machine Learning Engineer will lead the development of search ranking systems, focusing on machine learning models for relevance, quality, and personalization through various advanced techniques and collaboration with cross-functional teams.

Lead the SDL and Cash Line ML teams, developing innovative machine learning models to improve lending solutions and expand credit access. Collaborate with cross-functional teams to drive product strategy and enhance model performance, while mentoring a team of ML scientists.

As a Data Scientist, you will develop algorithms, collaborate on product requirements, and communicate data-driven insights, while enhancing product offerings and delivering actionable insights.

As an AI/ML Data Contributor, you will perform data labeling, evaluation, and testing for machine learning projects. Responsibilities include following guidelines, providing feedback, and completing tasks on time. Remote and in-person opportunities are available.

The role involves performing tasks to support AI/ML projects, including data labeling and content evaluation, with flexible work opportunities.

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

Build, deploy, and optimize production AI/ML and LLM-driven decisioning systems for claim offer generation and negotiation. Own end-to-end model development, evaluation, experimentation, and operational reliability while balancing fairness, business objectives, and product requirements.

Lead design and productionization of decisioning systems that impact pricing, offers, routing, and economics. Build models, heuristics, optimization logic, and evaluation frameworks. Design and run production experiments, translate business objectives into measurable decision systems, create feedback loops linking model and product outcomes, and partner with engineers to ship model-backed logic and configurable rules. Use AI to accelerate work and balance rigor with rapid iteration.

The role involves advising clients on AI strategy, designing AI solutions, and leading change management efforts. This includes governance, training, and client engagement while mentoring junior team members.

The Machine Learning Engineer will design, develop, and implement advanced recommendation systems, collaborating with cross-functional teams to enhance personalization for a global audience.

Own the full analytics lifecycle: define problems, extract data, build and deploy models, design experiments, and create Power BI dashboards. Track business metrics, apply statistics and AI/LLM tooling, partner with cross-functional teams, and present findings to stakeholders to inform decisions.

Part-time consultant evaluates and defines standards for AI-driven performance transfer, curates benchmark content, designs human evaluation frameworks, and collaborates with creative and technical teams to improve fidelity of AI-generated acting and animation.

The Producer will manage financial and operational aspects of hybrid, VFX, and animation projects, ensuring timely and budget-compliant deliveries while integrating AI methodologies.

Supervise and integrate Animation and Generative AI technologies into workflow, ensuring project quality, leading teams, and advancing animation methodologies.

The AI Adoption & Change Manager drives AI transformation within the IT organization, ensuring user adoption, training, communication, and integration of AI tools into workflows. They build change management plans, conduct assessments, facilitate training, and measure adoption metrics to improve AI initiatives.

The Machine Learning Engineer will develop advanced Deep Learning technologies for Computer Vision and SAR, focusing on object detection and model generalization. Responsibilities include researching algorithms, applying signal pre-processing, and optimizing model performance.

As a Principal Applied Scientist, you'll define the technical vision for offer optimization and conversion modeling systems, ensuring alignment across teams while overseeing large technical initiatives and contributing to real-world machine learning solutions.

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