Top Senior Machine Learning Jobs in San Diego, CA

Build and ship production LLM-powered agents, workflows, and integrations using platform templates, pipelines, and guardrails. Develop comprehensive evaluation suites, integrate business systems and data sources, instrument cost and quality telemetry, and collaborate with business users to iterate within defined scopes. Requires extensive software engineering experience, production LLM application expertise, strong Python and TypeScript skills, API craftsmanship, prompt and context engineering, and a commitment to guardrails and evaluation.

Build and deploy LLM-powered agents, workflows, and integrations using production templates, pipelines, and guardrails. Develop comprehensive evaluation suites, integrate with business systems and data sources, and instrument solutions for cost and quality telemetry. Collaborate with business users to iterate rapidly within defined scopes. The role requires strong Python and TypeScript skills, production LLM application experience, API development, prompt and context engineering, and retrieval expertise.

Develops AI/ML prototypes, APIs, microservices, integrations, and lightweight user interfaces for federal and DoD-aligned mission workflows. The role integrates and optimizes machine learning models for dashboards and applications, supports data ingestion and preprocessing, validates performance, and helps transition models into production. Collaboration with data scientists, architects, developers, PMO leadership, and cybersecurity teams is required. The position requires five years of relevant experience, a bachelor’s degree, ITIL v4 Foundation certification, and Public Trust or active Secret clearance.

Author and verify rigorous multiple-choice computer science assessment items across many CS domains to create gold-standard benchmarks for AI research. Produce correct answers, nine plausible distractors, solution explanations, difficulty labels, and authoritative references. Review and edit questions for technical accuracy, clarity, and reproducibility. Contribute asynchronously as an independent contractor, ~10+ hours/week, fully remote.

Leads the architecture, development, deployment, and optimization of enterprise machine learning solutions. Responsibilities include designing scalable ML systems, developing predictive models, supporting MLOps and model lifecycle management, improving data quality and feature engineering, implementing governance and validation frameworks, and mentoring technical teams. The role also contributes to AI strategy, innovation initiatives, responsible AI practices, and organizational modernization.

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.

Develop optimized GPU algorithms and high-performance machine learning solutions for vector search, databases, and data processing. Responsibilities include designing, implementing, benchmarking, debugging, and optimizing C++, CUDA, and Python libraries; developing clustering and visualization algorithms; collaborating cross-functionally; and contributing to open-source projects such as cuML, cuVS, and RAFT.

Serve as primary client contact for a portfolio of loyalty-program clients. Scope and manage end-to-end actuarial analyses rooted in predictive modeling and machine learning, validate model outputs, translate results into clear recommendations and presentations, and partner with analysts and data scientists to deliver high-quality, client-facing work in a fully remote consulting environment.

Partner with a retained search firm to place software engineers and quant developers at top hedge funds. Provide candidate flow from your network; firm supplies clients, process, and fees. Remote, commission-only role with placement and pipeline incentives. Apply with placement examples, outreach metrics, and a candidate submission.

Lead and align ML, data, and engineering teams to define multi-year AI roadmaps, deliver production ML solutions, ensure robust data pipelines, set success metrics tied to business outcomes, and grow/mentor senior managers and engineers.

Lead and build a data science organization to create a prediction engine for vendor matching, order routing, and supply chain optimization. Anchor projects to P&L, design measurement and experiment frameworks, ship rapid wins, hire and coach data scientists, work hands-on in modeling and technical design, partner with product and engineering (Snowflake), and evolve systems toward agentic AI while reporting impact in dollar terms.

Build, ship, and own end-to-end ML models for vendor matching, order routing, and supply-chain optimization. Partner with data engineering to productionize models, quantify impact, document work, and implement decision logic components toward agentic AI in a fast-moving healthcare startup environment.

Own end-to-end modeling for vendor matching, order routing, and supply-chain optimization. Build predictive, causal, RL and OR solutions; design autonomous decision logic; quantify counterfactual impact; ship production models with data engineering; mentor senior data scientists; write technical design docs; partner on quarterly priorities and expand into revenue cycle and finance domains.

The Staff Product Manager will define product strategy, lead the product lifecycle, collaborate across teams, and drive innovation in claims processing software.

The Director of System Safety oversees safety functions for autonomous vehicles, managing safety cases, deployment plans, and regulatory relationships while leading a multi-disciplinary safety team.

Lead development of time-series and econometric models (ARIMA, VAR, state-space, WLS, panel data) and Bayesian probabilistic frameworks. Use causal inference and stochastic processes to produce actionable insights, work with large datasets on Databricks, communicate results to stakeholders, and mentor junior team members.

Own a product area of the Content Authoring Platform end-to-end: set vision and roadmap, run continuous discovery, define and measure outcomes, partner with engineering and design to deliver features, evaluate and apply AI capabilities prudently, mentor peers, and communicate strategy and trade-offs to stakeholders.

Lead client-facing full-stack Java development, mentor teams, design solutions, promote engineering best practices (Agile, DevOps, CI/CD, TDD), and deliver enterprise software using modern cloud, container, and JS frameworks.

Senior Business Systems Analyst to define requirements for agent-facing servicing applications, design integrations/APIs with core banking systems, translate needs into user stories and acceptance criteria, improve agent workflows and productivity, and identify AI/ML opportunities for fraud detection, automation, and operational analytics. Supports testing, validation, and releases.

Gather and document functional requirements for agent-facing servicing applications, define integrations/APIs with core banking systems, consult with stakeholders, identify AI/ML opportunities (fraud, KYC, automation), support testing and implementation, and act as SME while managing risks and compliance.

Lead strategic GTM and co-selling initiatives with Google Cloud to drive NVIDIA AI adoption. Develop and maintain technical enablement assets, run developer activations and events, collaborate with Google Cloud field and engineering teams, convert samples into demos and labs, and translate customer feedback into product and roadmap insights.

Lead go-to-market strategy for Magnet Forensics' security, incident response, and AI product portfolio. Influence executive, product, and sales stakeholders; translate technical AI/ML and forensic capabilities into messaging; develop buyer personas; create sales enablement and demand-generation content; evangelize products at events; partner with competitive intelligence and customer advocacy; mentor product marketing team members.

Design reusable software tools and subsystems, lead implementation and estimation, ensure systems integration and multi-platform compatibility, drive projects to completion, and perform feasibility analyses for future projects.

Own and set technical direction for the Everand backend, building scalable, reliable systems for discoverability, personalization, and core consumption journeys. Drive architecture, platform health (CI/CD, staging, DBs, queues, cost, observability), mentor engineers, lead cross-team planning, modernize legacy systems, and partner with product, design, analytics, web/mobile, and ML to support experimentation and telemetry-driven decisions.

Lead product vision and roadmap for data and analytics products (ML, generative AI, data pipelines, BI). Translate business needs into developer-ready features, maintain backlog, collaborate with engineering and stakeholders, track KPIs, and drive adoption and continuous improvement.