Top Machine Learning Jobs in San Diego, CA

Leads data science and digital strategy for Novartis’s Biologics Research Center. Builds partnerships with scientific and digital stakeholders, drives adoption of data governance and enterprise platforms, translates research needs into scalable solutions, and leads global cross-functional initiatives. The role enables scientific data capture, visualization, automation, analytics, and AI capabilities while aligning stakeholders and delivering measurable business and research impact.

Own the strategy, architecture, development, deployment, monitoring, and continuous improvement of production personalization and recommendation systems. Build custom embeddings, ranking models, and shared representations across feeds, search, and recommendations. Lead ambiguous problems from concept to measurable customer impact, establish AI evaluation standards, partner with product and data teams, make cross-team technical decisions, and coach senior engineers.

Engineer AI-powered threat detections, automated response playbooks, and continuous adversary emulation. Apply machine learning and LLMs to security operations, conduct threat hunting and AI red teaming, map coverage to MITRE ATT&CK, and develop detection-as-code through CI/CD. Build production-grade Python integrations, measurable containment capabilities, and safe autonomous defenses with guardrails. Mentor security professionals and collaborate across threat response, cyber defense engineering, and platform teams.

Design, build, and operate high-throughput, low-latency ad-serving infrastructure processing millions of requests per second. Optimize GPU-powered TensorRT inference, feature stores, model serving, benchmarking, experimentation tooling, and system reliability. Partner with machine learning engineers to productionize models and own systems through design, deployment, observability, capacity planning, incident response, and optimization.

The Principal leads AI platform initiatives, driving strategy and technical execution. This role includes product management, cross-functional program leadership, and governance in AI adoption across the organization.

Supports the NAVWAR Front Office Chief of Staff with DoD acquisition program management, strategic planning, process improvement, documentation, dashboards, and milestone tracking. Provides IT systems analysis through data integration, cleansing, workflow automation, cybersecurity baseline tracking, architecture development, and analytics solutions using government IT platforms such as Microsoft 365 and FlankSpeed. The role also supports briefings, policy guidance, executive communications, special projects, and process modernization.

Provides deep technical sales support for Red Hat AI, helping enterprise customers design, deploy, and adopt AI platforms. Architects Kubernetes-based AI systems, GPU-enabled workloads, data and ML pipelines, and model training and serving environments. Leads technical workshops, proofs of concept, presentations, business-value discussions, and customer advocacy. Collaborates with engineering, sales, consulting, customer success, and partners to validate solutions, provide product feedback, and drive AI adoption.

Support analytics by cleaning, validating, and transforming data; build dashboards and KPI reports; perform trend, cohort, and A/B testing analyses; improve data pipelines and forecasting; present insights to cross-functional teams.

Develop and implement production-grade bioinformatics algorithms for NGS secondary analysis, focusing on structural variant detection, pangenome references, graph algorithms, and assembly methods. Collaborate with software, FPGA, quality, testing, and clinical genomics teams while communicating technical findings to diverse audiences. The role requires strong genomics, algorithms, statistics, C++, and software development expertise.

Leads lab-in-the-loop biology programs that connect experimental design with machine learning model development. Oversees closed-loop experiments, model-output verification, perturbation studies, data generation, assay and model-system development, automation, metadata standards, CRO and vendor relationships, budgets, and cross-functional collaboration. Builds and mentors technical teams while aligning experimental and computational groups across a matrixed biotech organization.

Analyze complex datasets, develop predictive models, identify trends, create data visualizations, validate data quality, and collaborate with business stakeholders to support data-driven growth and decisions.

Develops algorithms, predictive models, quantitative analyses, and visualizations from structured and unstructured data. The role involves data exploration, cleaning, mining, and statistical analysis using R or Python, with applications of machine learning, artificial intelligence, and natural language processing. Candidates support sustainment analysis using reliability engineering metrics and methods, potentially across naval and defense platforms, while maintaining or obtaining Secret clearance.

Develop and deploy autonomy software for unmanned surface, underwater, and aerial vehicles in maritime missions. Responsibilities include motion planning, localization and tracking, safety assurance, COLREGS adherence, multi-agent coordination, distributed optimization, rigorous software testing, platform integration, deployment support, mission-log analysis, and autonomy R&D. The role also involves cross-functional collaboration, customer and demonstration support, roadmap development, and mentoring junior engineers. Travel is typically approximately 25% annually.

Lead technical direction for maritime autonomy capabilities across multiple programs. Develop motion planning, localization, tracking, safe maritime behaviors, COLREGS-compliant operations, and heterogeneous multi-agent collaboration for USVs, UUVs, and UAVs. Build and integrate high-performance, rigorously tested software; support deployment, vehicle testing, demonstrations, and mission-log analysis. Mentor engineers, guide architecture and roadmaps, research new algorithms, and collaborate across perception, planning, simulation, hardware, and operational test teams. Travel is typically about 25%.

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.

Leads a portfolio of DoD autonomous systems programs from research and prototyping through integration, testing, and fielding. Manages schedules, budgets, contracts, risks, deliverables, technical oversight, and cross-functional teams while engaging government customers and developing new business opportunities. The role emphasizes Navy and multi-service autonomous systems, AI-enabled capabilities, acquisition strategy, customer relationship development, and portfolio growth. Daily on-site presence in San Diego is required, with travel up to 25%.

Design and deploy production-ready LLM pipelines and agentic workflows, automate large-scale multimodal dataset pipelines, monitor and improve agent performance, and integrate AI agents with 3D scene composition. The role also involves process documentation, incident response, and continuous improvement, with collaboration across the engine team and company founders.

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.

Leads and builds NVIDIA’s AI Safety and Security Engineering team, hiring engineers across platform, security research, evaluation, and vulnerability tooling. Owns the Find, Validate, and Patch roadmap; guides architecture and evaluation trade-offs; partners with security, platform, and evaluation leaders; and communicates engineering progress clearly. The role requires extensive software engineering and engineering management experience, with expertise in complex systems, ML infrastructure, security tooling, or distributed platforms.

Lead NVIDIA’s AI for Quantum product strategy, roadmap, and go-to-market initiatives. Translate AI and quantum research into scalable platforms, developer tools, APIs, libraries, and workflows. Partner with researchers, engineers, quantum hardware companies, institutions, and developers to identify applications across quantum design, control, calibration, error correction, and algorithms. Evangelize the platform through technical communications, identify new AI, HPC, and quantum opportunities, and present product strategy to executives.

Develop and deploy LLM and machine learning models for Airbnb Community Support. Responsibilities include automating LLM evaluation, curating synthetic datasets, analyzing customer issues, identifying model failure modes, building personalization models, exploring data, prototyping solutions, and communicating insights to cross-functional stakeholders. The role focuses on scalable, production-ready AI products and operational optimization.

Own end-to-end technical delivery for wellness clients, from pre-sales demonstrations and requirements gathering through production deployment. Build AI agents, insight products, data ingestion and ETL pipelines, and customer-facing software. Design system architectures, integrate complex client data sources, lead technical working sessions, communicate tradeoffs, and influence product direction through customer deployment learnings.

Leads the AI product strategy and roadmap, extending governed Alteryx workflows and business logic into enterprise AI agents and LLM ecosystems. Owns the Faster, Better, Cheaper ROI narrative, benchmarks product performance, quantifies customer value, champions trustworthy AI through the VURA framework, and represents the product vision with customers, analysts, and external audiences.

Own the enterprise architecture vision for scalable, high-performance, cost-efficient multi-tenant SaaS systems. Lead AWS cloud optimization, distributed data and AI infrastructure, architectural governance, and Architecture Review Council activities. Guide engineering teams on microservices, event-driven systems, automation, and cloud-native practices while driving GenAI adoption across the software lifecycle. Build prototypes, establish architectural standards, optimize total cost of ownership, and mentor technical leaders.

Leads Dandelion Health’s AI developer business by building pipeline, closing clinical AI data and validation partnerships, recruiting developers into its marketplace, and achieving revenue targets. Develops commercial strategy, manages executive relationships, structures agreements, and collaborates with marketing, product, data, engineering, and clinical informatics teams. Represents the company at industry events and advises on clinical AI validation, regulatory, payer, and competitive dynamics.