Top Senior Machine Learning Jobs in San Diego, CA

Drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, machine learning, NLP, LLM applications, and classifier implementation. Build growth metrics, monitoring pipelines, evaluation datasets, and AI trigger systems across search and Duck.ai. Analyze privacy-constrained data, deploy production-grade models, optimize SQL queries, and lead complex projects from scoping through production with minimal direction.

Own the strategy, roadmap, requirements, launch, adoption, and success metrics for a technical platform. Partner with engineering, data, product, and business teams; evaluate architecture, APIs, and system tradeoffs; prioritize foundational investments against customer and revenue outcomes; and apply AI to improve platform capabilities. The role requires strong product management experience, technical depth, analytical skills, and production experience with LLM-based or ML-adjacent products.

Provides senior-level presales technical consulting for complex networking and security solutions. Partners with sales teams and customers to design WAN, data center, cloud, and security architectures; develops proposals, bills of materials, and implementation specifications; delivers technical presentations, demonstrations, proofs of concept, and training; and influences executive technology decisions. Requires extensive Juniper and networking expertise, customer-facing sales experience, and the ability to travel as business demands require.

Designs and implements security controls, threat models, and incident response capabilities for AI and machine learning systems. The role addresses LLM and model API vulnerabilities, prompt injection, model abuse, data exfiltration, training data risks, and AI supply chain threats. Responsibilities include securing AI-powered applications and infrastructure, performing architecture reviews, applying application security and cryptography principles, and developing defenses against adversarial machine learning attacks.

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.

Designs, builds, and scales enterprise AI applications using classical machine learning, generative AI, RAG, and agentic architectures. Develops intelligent workflows, autonomous agents, knowledge systems, chatbots, copilots, and decision-support solutions integrated with enterprise platforms and APIs. Leads AI governance, evaluation, observability, security, and human-in-the-loop controls while advising clients on enterprise AI transformation. Requires extensive experience with Claude, OpenAI, LLMs, cloud platforms, vector databases, semantic search, and production-grade AI implementations.

Leads wind energy assessments, SCADA and performance analysis, advanced data processing, automation, and technical consulting for utility-scale renewable projects. Develops analytical tools and workflows, evaluates energy production, uncertainty, losses, and risks, and provides technical oversight, peer review, mentoring, and customer-facing expertise. The role also advances AI-enabled analytics, data management, visualization, and renewable energy assessment methodologies.

Performs wind resource and energy production assessments for utility-scale projects, analyzing meteorological, SCADA, LiDAR, and operational data. Supports technical due diligence, project performance and risk evaluations, remote sensing, uncertainty analysis, and customer deliverables. Collaborates with multidisciplinary teams, mentors colleagues, contributes to AI-enabled automation and analytical workflows, and participates in technical consulting projects across the renewable energy lifecycle.

Design and build software tooling, firmware, and infrastructure supporting semiconductor design, verification, manufacturing, and post-silicon validation. Collaborate with hardware and EDA teams, develop scalable compute infrastructure and data pipelines, automate workflows, debug complex systems, and translate ambiguous requirements into production-quality solutions. The role also involves code and design reviews, cross-functional communication, documentation, and mentoring junior engineers.

Develop and implement AI solutions and machine learning systems that enhance products and solve complex client problems. Responsibilities include advanced analytics, LLM production deployment, prompt engineering, RAG pipeline optimization, cross-functional collaboration, technical discovery, responsible AI advocacy, client relationship building, and mentoring junior team members.

Analyze and optimize the end-to-end sales funnel by developing KPIs, dashboards, diagnostic analyses, and operational measurement frameworks. Partner with Sales, Operations, Data Engineering, and Data Science teams to improve conversion, revenue, capacity planning, and pipeline prioritization. Lead AI-native automation initiatives, including LLM analytics assistants, automated reporting, prompt engineering, and machine learning model validation.

Develops algorithms, predictive models, and data systems to analyze complex structured and unstructured datasets. Partners with clients to define analytical needs, performs data exploration, cleaning, mining, visualization, and modeling, and translates findings into actionable insights. The role uses statistical programming, machine learning, AI, and distributed computing tools to support decision-making across public and private sector challenges.

Leads pricing and revenue data science initiatives for consumer markets clients. Develops predictive models, forecasts trends and customer behavior, manages dashboards and visualizations, ensures data quality, and translates complex analytics into strategic decisions. Oversees client engagements, validates outcomes, directs complex projects, and coaches diverse, high-performing teams.

Leads the scientific direction and technical roadmap for a permanent magnet research vertical. Responsibilities include guiding computational materials discovery and AI modeling, developing manufacturable magnet formulations, building and mentoring multidisciplinary teams, managing intellectual property, coordinating national laboratory and industry partnerships, and connecting simulation with experimental validation. The role also supports commercial licensing, external scientific communications, publications, and federally funded research programs.

Own the strategy, roadmap, and success metrics for AI security capabilities across the Pathfinder platform. Serve as the internal expert on agentic AI threats, identity security, and emerging attack techniques. Define requirements for securing AI agents, MCP servers, and orchestration frameworks; conduct market and competitive research; lead design partner programs; coordinate cross-portfolio product work; and support analyst, customer, marketing, and pre-sales engagements.

Owns a portfolio of NovaOS capabilities from concept through delivery, adoption, and continuous improvement. Manages backlogs, roadmaps, prioritization, requirements, user stories, release planning, and product metrics. Partners with stakeholders, Engineering, AI, UX, Data Science, and Architecture teams to deliver enterprise AI-enabled products aligned with governance, Responsible AI, and business objectives.

Own and improve ClickUp’s voice AI systems, including real-time speech-to-text, audio processing, context-aware transcription, LLM post-processing, mention resolution, formatting, and voice-to-action workflows. Evaluate and integrate ASR models for accuracy, latency, and cost, while collaborating across product and platform teams to deliver voice and multimodal assistant features across desktop, mobile, web, and browser extension products.

Leads enterprise CrowdStrike deployments, architecture, compromise assessments, threat hunting, SOC modernization, detection engineering, cyber analytics, Purple Team exercises, and incident response. Advises CISOs and executives, manages cross-functional teams, designs global 24/7 SOCs, and coordinates breach containment and recovery. Requires deep CrowdStrike expertise, cybersecurity leadership, scripting, network and detection engineering, and executive communication skills.

Designs and maintains scalable data models, semantic layers, ETL/ELT workflows, data-quality frameworks, and governed analytics products for commercial operations. Owns data solutions from requirements through deployment, monitoring, documentation, and support. Partners with technical and business stakeholders to deliver trusted reporting, dashboards, scorecards, productivity measurements, and AI-enabled decision support.

Build, productionize, and govern clinical machine learning products using large-scale healthcare data. Responsibilities include developing predictive models, monitoring ML research, supporting MLOps, implementing model governance, integrating analytics into products and dashboards, curating datasets, partnering with clinicians and product teams, mentoring engineers, and communicating findings to technical and executive stakeholders.

Designs, builds, and operates observability and SRE systems that improve IT service visibility, reliability, performance, and resilience. Responsibilities include metrics collection, monitoring, alerting, APM, RUM, synthetic transactions, SLOs, incident response, capacity planning, infrastructure automation, self-healing systems, and production readiness reviews. The role also applies AI-enabled operations, supports on-call rotations, reduces operational toil, and partners with development teams on architecture and chaos testing.

Leads enterprise security reviews, threat modeling, architecture assessments, governance, and control development for AI, generative AI, machine learning, LLM, RAG, and AI-agent solutions. Defines security standards and guardrails, evaluates platforms and vendors, advises cross-functional stakeholders, and supports responsible AI adoption while managing cybersecurity, privacy, regulatory, and operational risks.

Drive new business revenue across the Western Territory by selling complex healthcare technology and services, including AI-enabled EHR and revenue cycle management solutions. Manage the complete enterprise sales cycle from prospecting, discovery, demonstrations, proposals, negotiations, and closing through accurate forecasting and CRM updates. Build relationships with healthcare decision-makers, manage RFPs, develop territory plans, and travel 50–75% of the time.

Own cloud security across AWS and Azure, including identity, network, application, container, data, and AI security. Build policy and infrastructure controls as code, integrate security into CI/CD, protect regulated health data, and manage detection, incident response, vulnerability remediation, and compliance. The role also develops AI security guardrails and coaches engineering teams while operating production security controls and supporting on-call responsibilities.

Leads enterprise AI solution strategy, architecture, pre-sales, and implementation delivery for customers across the Americas. Defines AI use cases, validates feasibility, designs scalable architectures, guides Professional Services teams, and resolves complex technical challenges. Develops AI service offerings, methodologies, reusable assets, and enablement programs while mentoring architects, consultants, and project leaders. Requires deep experience with enterprise transformations, LLMs, multi-agent systems, generative AI, data architecture, cloud platforms, and production AI deployments.