Top Machine Learning Jobs in Los Angeles, CA

Teach an intensive course on cinematic AI, generative design, and emerging creative technologies to students in creative industries, focusing on practical applications and ethical considerations.

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.

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.

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 technical strategy, architecture, and implementation for ML inference platform services. Design and scale distributed, high-throughput inference systems, collaborate across teams, drive availability, scalability, operational excellence, cost management, and provide company-wide technical direction and mentorship.

Design, build, and deploy large-scale machine learning models powering Snapchat features. Own full ML lifecycle from data analysis to production, prototype with cross-functional partners, apply modern ML techniques, and use AI tools while ensuring code correctness, security, and scalable system design.

Design, build, and deploy large-scale ML models powering core products; own full ML lifecycle from data analysis to production; partner cross-functionally to prototype and launch features; apply modern ML techniques and AI tooling while ensuring code quality, security, and scalable production services.

Design, train, and productionize machine learning models for fraud and identity risk across the full ML lifecycle. Research new fraud types, perform feature engineering and labeling, write production-ready code for real-time decisioning, monitor models, and provide analyses to inform product, sales, and data acquisition.

Lead research, development, and deployment of recommendation and personalization ML models. Design algorithms, build end-to-end pipelines, optimize for accuracy/latency/scale, integrate solutions into production, implement monitoring/bias detection/retraining, and collaborate on experimentation and product integration to improve user engagement and retention.

Lead the Accounting & Finance Reporting, Data & AI Center of Excellence: set strategy, governance, roadmap, and deliver analytics, automation, and AI solutions. Own intake, prioritization, implementation, adoption, and value realization across financial processes while partnering with IT and mentoring the team.

Build and productionize statistical and ML models to optimize advertiser performance and business goals in mobile ad tech. Tune optimization, model competition and dynamic environments, design experiments, develop budget retention/growth and bidding systems, and collaborate across engineering and business teams while ensuring explainable, well-tested solutions.

Lead development and production of underwriting and credit decisioning models across Cash App Borrow and Afterpay. Own full modeling lifecycle: problem formulation, feature engineering, training, calibration, experimentation, deployment, monitoring, and iteration. Build decision frameworks, agentic engineering workflows, and collaborate with cross-functional partners to align model behavior with business and regulatory goals.

Design, deploy, and maintain end-to-end ML risk solutions at scale to detect and prevent fraud, merchant risk, and credit loss. Partner with cross-functional teams, lead technical decisions, build ML tooling, monitor models in production, and investigate emerging abuse patterns to improve detection and decisioning.

The role involves leading technical initiatives in machine learning infrastructure, developing data pipelines, and collaborating across teams to enhance personalized news content delivery.

Join Capsule as an AI Engineer to develop ML models for video editing. Responsibilities include researching ML techniques, collaborating on feature development, and optimizing model performance.

The Director will lead and manage the firm's AI and data science initiatives, oversee a multidisciplinary team, and develop AI solutions that enhance operational efficiency and decision-making in legal contexts.

Lead strategy and delivery for an AI-powered claims decision-support and auto-adjudication platform. Define vision and roadmap, manage a team of product managers, partner with business, engineering, and data science, and drive adoption, impact measurement, and executive-level communication across a complex, matrixed enterprise.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

Independently validate and monitor machine learning models for credit underwriting, credit risk, and fraud detection. Identify model weaknesses, recommend improvements, and collaborate with model owners to remediate findings. Support and maintain the Model Risk Management framework and coordinate with Internal Audit, Internal Controls, and Compliance on audit and regulatory requests.

As a Machine Learning Engineer II, you will enhance AI systems for automating customer operations, develop evidence extraction pipelines, and collaborate with teams on model development and deployment.

Postdoctoral researcher to support P50 analyses using AI and machine learning applied to human brain MRI. Responsibilities include MRI data acquisition and analysis, statistical analyses, model development, and collaboration on projects; experience with stroke and federated learning is a plus.

Design, evaluate, and productionize decisioning systems that affect pricing, offers, and routing. Run experiments, build models/heuristics and optimization logic under operational constraints, create feedback loops linking model behavior to business outcomes, and partner with engineers to ship improvements. Use AI as an active tool and help the team adopt AI-native workflows.

Lead the development and implementation of machine learning solutions, managing a team to drive strategic decisions and innovative business outcomes.

Lead multi-year vision and roadmap for AI/ML recommendation and prediction products. Align executives, prioritize using data and research, and guide engineering to deliver scalable ML features. Evangelize AI product standards, mentor other PMs, and partner with design, data science, and engineering through the full delivery lifecycle.

Assist the AI engineering team with NLP research, language model development, data annotation, experiments, and model evaluation. Support multilingual translation, content moderation, analytics, and other language-related features for a football-focused social and messaging platform.