Top Machine Learning Jobs in Los Angeles, CA

The Program Director for Aerostructures provides strategic leadership for defense aerostructure programs, ensuring performance and alignment with customer needs while overseeing business growth and mentoring program managers.

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

Design, build, and operate production ML decision systems to detect and prevent payment fraud, account takeover, scams, and other abuse. Integrate diverse signals into low-latency serving and batch scoring, own feature pipelines and model lifecycle, develop AI-assisted triage and feedback loops, and partner cross-functionally to balance fraud reduction with legitimate customer access.

Design, build, and operate production ML systems that generate trusted signals for ranking, retrieval, recommendations, propensity/churn/LTV, and next-best-action decisioning. Define signal/data contracts, own feature and candidate generation through serving, experimentation, monitoring, and feedback loops, and evaluate long-term business impact, trust, fairness, and compliance. Partner across product, data, modeling, risk, and compliance and apply AI/agents to accelerate engineering and operations.

Design, build, and operate production ML decision systems to detect and prevent payment fraud, account takeover, identity abuse, merchant/marketplace risk, scams, and other adversarial activity. Own end-to-end production lifecycle: data contracts, low-latency inference, batch scoring, feature quality, deployment, monitoring, incident response, rollback, and feedback loops. Develop AI-assisted workflows and reusable decision capabilities while partnering with modelers, product, compliance, and operations.

Design, build, and operate production ML signal systems—ranking, retrieval, recommendations, propensity, and next-best-action—covering feature/candidate generation, serving, experimentation, monitoring, and feedback. Define signal contracts (freshness, provenance, confidence), evaluate long-term impact (trust, fairness, compliance), and partner across product, data, and risk teams to deliver reusable customer-intelligence capabilities.

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.

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 Senior Staff Machine Learning Scientist will lead research initiatives in computer vision and multimodal understanding, develop novel models, and translate research into practical applications while mentoring team members.

As an ML Ops Infrastructure Engineer, you will design CI/CD pipelines for ML, maintain deployment systems, and implement monitoring while collaborating with research teams to ensure model quality and performance.

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

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.

The Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.

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 Senior Gen AI Developer will design, develop, and deploy generative AI applications, focusing on LLMs and retrieval-augmented generation pipelines, while collaborating in a dynamic team environment.

Design and implement scalable data pipelines and ML algorithms to optimize StackAdapt's digital advertising platform. Collaborate with teams to solve complex problems.

As an Applied Machine Learning Scientist, you will innovate and develop machine learning algorithms, write production code, and collaborate to implement and test these solutions based on historical data.

As a Machine Learning Engineer, you'll design, build, and maintain models to detect security threats, ensuring model efficiency and aligning initiatives with business goals.

The Junior-Midlevel Developer will build and enhance Dumroo.ai's AI-powered education platform, collaborating on software components, data pipelines, and machine learning features.

The Senior Data Scientist will manage data collection, design study protocols, train juniors, lead report development, and support innovative analytics tools.

Co-found and lead a stealth startup building an agentic AI platform embedded in CAD tools to automate geometry updates, feature-tree edits, and cross-tool workflows. Drive product, engineering, and commercial strategy, hire the founding team, and develop a defensible data capture and automation stack for industrial CAD workflows.

This role leads the ML Acceleration team, focusing on enhancing ML model training efficiency and team management, while driving technical strategy and collaboration.

The Senior AI Engineer role involves deploying AI solutions to extract structured data from medical charts, improving efficiency and ensuring compliance. Responsibilities include developing AI extraction pipelines, maintaining AI model production, and collaborating with cross-functional teams to integrate AI solutions into healthcare systems.