Top Machine Learning Jobs in San Diego, CA

Lead Pearl's Enterprise AI product business end-to-end: define vision and GTM, build and scale AI+human offerings, partner with enterprise customers, and run a lean cross-functional team to deliver measurable commercial outcomes.

Senior individual-contributor role leading 3Cloud's enterprise AI strategy and Center of Excellence. Advise C-suite clients, define AI architectures and standards, drive adoption, develop offerings, and convert strategy into implementation while mentoring technical leaders and shaping commercial growth.

Lead enterprise AI and transformation engagements—own customer relationships, scope buildable solutions with FDE, drive commercial outcomes and expansion, advise C-suite on AI strategy, and create repeatable, scalable offerings to evolve Tive into an AI-powered intelligence platform.

Lead AI-focused internal audits and investigations to detect misuse, fraud, compliance violations, and insider threats in AI systems. Develop methodologies, analytics, continuous monitoring, and control assessments; supervise auditors; partner with Legal, Security, Privacy, and business stakeholders; and deliver risk-based findings and remediation recommendations.

Lead and manage complex financial, operational, and integrated audits; assess internal control design and effectiveness; use advanced data analytics and AI-enabled tools to identify risks, develop recommendations, report to leadership, and drive remediation and continuous improvement.

Design, build, and operate hyperscale Azure availability and control-plane services to achieve high VM SLAs. Lead architecture, author designs, implement reliable code, run livesite as DRI, and integrate predictive ML/AI models and generative AI for diagnostics and automated root-cause analysis.

Lead development and optimization of prompt engineering strategies and RAG frameworks. Build Python-based AI applications using Azure OpenAI and AWS, manage AI project delivery, optimize ML models, and collaborate with cross-functional teams to integrate cloud-based AI solutions following Agile methodologies.

Lead the development of AI applications and data products to enhance Immunology R&D. Manage a technical team and collaborate across departments.

Lead and build the Applications function to translate clinical/research lab workflows into validated, deployable robot capabilities. Own workflow validation, instrument onboarding, training data collection for ML, technical documentation, demos, customer technical leadership, and team hiring and development.

Lead enterprise AI strategy and engineering for the company: define AI roadmap, identify high-value use cases, oversee generative AI and ML delivery, set governance and responsible AI standards, evaluate vendors, build cross-functional adoption, and grow an AI engineering team to drive measurable business value.

Design, implement, and deliver user-facing enterprise software and GUI applications in an Agile environment. Develop Java/JEE microservices, integrate web services/JMS/XML, collaborate with cross-functional teams, follow SDLC, and support testing, DevSecOps and deployment. On-site role with occasional travel and strict security clearance requirements.

Build analytical frameworks, measurement methodologies, and decision support to drive enterprise decisions across marketing, loyalty, pricing, menu, media, and operations. Mine and integrate customer, transaction, digital, and operational data; develop segmentation, predictive models, and dashboards; lead test-and-learn, incrementality, and forecasting efforts; translate analysis into clear business recommendations and scalable decisioning tools.

Design and deploy machine learning models for financial document processing, optimize large language models, collaborate with cross-functional teams, and guide junior peers in a fast-paced environment.

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.

Design, develop, and deploy machine learning models and pipelines to optimize operations. Lead full ML project lifecycle, ensure model evaluation/monitoring, collaborate cross-functionally, mentor junior engineers, and drive continuous improvement in ML applications and processes.

The Product Marketing Manager will execute product launches and support go-to-market initiatives, collaborating with cross-functional teams to develop and deliver messaging and enablement materials targeting both technical and business stakeholders.

Lead end-to-end ML systems for identity verification, including document authenticity, face match, liveness and deepfake detection. Build GNN-based identity graphs, behavioral/device-intelligence models, vendor benchmarking/evaluation, and production enforcement. Mentor engineers and align ML architecture with Product, Compliance, Risk, and Security stakeholders.

Lead development of safety frameworks and V&V for end-to-end autonomous robotics, perform risk assessments and safety reviews, derive technical safety requirements, and coordinate cross-functional teams to monitor fleet performance and deploy scalable autonomy.

Lead strategy and execution for AI-powered Customer Success Services, overseeing Gainsight and related platforms, customer community strategy, customer intelligence, automation, digital engagement, platform governance, and a team to scale adoption, retention, and operational efficiency across the customer lifecycle.

Develop and implement AI solutions, optimize models, preprocess data, integrate AI into workflows, and collaborate with cross-functional teams.

Lead and execute statistical and geospatial analyses to quantify and map climate mitigation potential from forests and peatlands. Design analytical workflows, manage projects and partners, create datasets, tools, reports, and deliver trainings and technical support for global conservation initiatives. Communicate results via publications, visualizations, and capacity-building activities; occasional fieldwork and international travel possible.

Lead end-to-end delivery of strategic data science and AI solutions for AI infrastructure. Work with telemetry and experimentation at fleet scale to build, deploy, and measure predictive and prescriptive models. Partner with stakeholders, present insights, enable adoption, and promote responsible AI. Collaborate closely with data engineers and infrastructure teams to productionize scalable ML solutions.

Manage and grow NVIDIA partner relationships in Manufacturing and Automotive: develop business plans, drive ecosystem enablement, increase adoption of NVIDIA AI solutions, maintain executive relationships, and present results in QBRs.

Lead cross-functional compiler software programs from concept to delivery, coordinating global teams, tracking risks and schedules, and improving development processes. Present status to executives, drive Agile and Waterfall projects, resolve technical/resource conflicts, and implement process and tool automation to ensure timely product releases.

Own full-cycle recruiting for technical roles, partner with hiring managers to define roles, source and close candidates, build scalable systems and pipelines, optimize hiring with data, and support a global, remote people team while acting as a culture ambassador.