Top Machine Learning Jobs in San Diego, CA

Architects and operates enterprise cryptographic services for a regulated, multi-tenant SaaS platform. Responsibilities include building FIPS-compliant key management, PKI, secrets, and workload identity systems; running Kubernetes services; threat modeling; evaluating AI/ML for security applications; collaborating on compliance requirements; mentoring engineers; and advancing post-quantum readiness.

Leads the Safety AI organization and architecture for on-device and cloud-based computer vision and machine learning systems. Oversees sensor fusion, model lifecycle management, platform architecture, experimentation, deployment, monitoring, and continuous improvement across more than two million dashcams. Partners with product, firmware, full-stack, and platform teams to deliver reliable, low-latency safety features. Builds and develops teams of applied scientists and engineers while driving measurable improvements in driver safety and customer outcomes.

Lead the design and implementation of AI initiatives for edge devices. Develop and optimize machine learning solutions using large-scale sensor, video, text, diagnostic, transaction, and location data. Partner with engineering and business teams to prototype AI experiences, ship production systems, adopt research advances, and improve edge model performance. Mentor ML engineers and communicate technical concepts to varied audiences.

Own the full B2B sales cycle across EMEA and the US, from outbound prospecting and opportunity creation through negotiation, closing, and account expansion. Sell content syndication, qualified leads, and intent-led demand-generation programs to senior marketing and sales decision-makers. Build pipeline, meet revenue targets, maintain accurate CRM forecasts, grow existing accounts, and collaborate with delivery, data, media, and client success teams.

Own the full sales cycle for enterprise B2B demand-generation clients across EMEA and the US. Responsibilities include prospecting, building outbound pipelines, developing account strategies, engaging executive buyers, negotiating complex contracts, closing net-new business, expanding accounts, forecasting accurately, and collaborating with delivery, data, media, marketing, and client success teams.

Leads a multidisciplinary data science and data engineering team supporting Finance. Sets strategy, prioritizes initiatives, guides analytical models and data architecture, advances AI and machine learning applications, improves data quality and reliability, establishes scalable operating processes, and communicates technical recommendations to Finance and executive stakeholders. The role also manages talent, oversees forecasting and decision-support outcomes, and drives measurable business impact.

Leads GitLab’s Product, Sales, and Finance Data Science teams, managing managers and a 12-person organization. Sets data science standards, prioritizes investments, partners with executives, drives product adoption and revenue growth, and oversees experimentation, causal inference, predictive modeling, and AI initiatives. Develops talent, builds succession, and collaborates with Analytics Engineering and Data Engineering on a shared data and AI roadmap.

Architects and operates enterprise outbound security services for a multi-tenant SaaS platform. Responsibilities include egress filtering, proxying, SSRF protection, exfiltration prevention, Kubernetes operations, threat modeling, incident response, compliance, and evaluating AI/ML for anomaly detection and risk scoring. The role also mentors engineers and advances secure connectivity, TLS, and post-quantum readiness.

Provide computational chemistry and molecular modeling support for drug discovery projects, develop modeling approaches, troubleshoot computational issues, share expertise, and collaborate with software developers to improve therapeutic discovery technologies. The role focuses on structure-based drug design, lead optimization, molecular dynamics, free-energy methods, virtual screening, cheminformatics, and ADMET modeling.

Owns quality assurance for cryptocurrency and sanctions compliance programs, including sampling, decision reviews, metrics, risk reporting, corrective actions, and continuous improvement. Partners with BSA/CFT and Sanctions program owners and leadership to ensure compliance standards align with regulatory requirements and product growth. Requires deep AML, KYC, sanctions, and fintech compliance expertise, strong analytical and communication skills, executive influence, and AI fluency.

Leads AI and automation product strategy for disability and absence claims operations. Responsibilities include prioritizing AI opportunities, owning roadmaps, designing human-in-the-loop workflows, defining safeguards and success metrics, partnering with engineering, coaching Product Owners, managing delivery increments, and communicating operational impact to senior leadership.

Owns strategic planning, governance, prioritization, risk management, and execution across a portfolio of Superintelligence Lab programs. The role establishes phase-gate standards, manages change, tracks portfolio health through dashboards and metrics, resolves blockers, advises cross-functional teams, and communicates progress to executives. It requires strong technical program management experience, Jira proficiency, Agile and SDLC knowledge, and the ability to apply AI technologies to improve business outcomes.

Leads the development and deployment of data solutions using Palantir Foundry and AIP. Manages engineering teams, coaches team members, oversees project planning and execution, analyzes system interactions, manages client relationships, and drives innovation. The role applies software engineering, data engineering, analytics, and AI/ML techniques to deliver scalable client solutions while maintaining technical and professional standards.

Leads the development and deployment of software and data solutions using Palantir Foundry and AI/ML technologies. Responsibilities include data engineering, analytics, system improvement, client account management, project ownership, team leadership, coaching, stakeholder engagement, and continuous improvement. The role requires building scalable applications with large datasets and delivering customer-focused solutions.

Own and grow strategic enterprise customer relationships, driving retention, renewals, expansion, and seven-figure software transactions. Develop multi-year account plans, build executive and technical stakeholder relationships, identify expansion opportunities, lead negotiations, maintain forecasts and pipeline visibility, and coordinate cross-functional teams. Engage with data scientists and AI/ML engineers to understand adoption, customer outcomes, and opportunities to expand platform usage across business units and use cases.

Own the strategic vision and roadmap for Coursera’s AI-driven search experience. Lead conversational search, personalization, semantic and multilingual search, ranking, and discovery improvements. Partner with engineering, design, research, data science, ML, marketing, and partnerships teams to deliver scalable platform capabilities. Use experimentation, market analysis, KPIs, and customer insights to improve conversion, merchandising, learner experience, and revenue.

Leads GitLab’s Product Data Science team, setting its strategy, roadmap, analytical standards, and priorities. Partners with Product and Engineering leaders on experimentation, causal inference, analytics, and production modeling. Manages, hires, coaches, and retains data scientists while building a high-performing function. Provides hands-on technical review of models, analyses, and queries, and communicates insights and risks to senior leaders.

The Data Scientist will partner with Sales, Revenue Operations, and Finance to analyze GTM performance, build and productionize machine learning models, conduct experiments, forecast outcomes, and identify growth opportunities. Responsibilities include statistical analysis, causal inference, Python and SQL development, MLOps, agentic workflow automation, semantic-layer contributions, executive reporting, and communicating insights to nontechnical stakeholders in a fully remote environment.

Leads an analytics team supporting commercial aviation aftermarket strategy. Oversees enterprise dashboards, forecasts, analytical models, data governance, KPI development, market intelligence, business cases, and strategic opportunity analysis. Manages request prioritization, quality assurance, delivery timelines, team capacity, hiring, coaching, and performance. Partners with business development and program teams to translate aerospace data and market trends into regional growth strategies and executive recommendations.

Leads SailPoint’s global corporate communications function, including corporate narrative, media relations, PR campaigns, crisis communications, executive coaching, podcast strategy, partner communications, and measurement. The role manages internal and agency teams, translates complex cybersecurity and AI concepts into compelling stories, supports product launches and company milestones, builds rapid-response capabilities, and advises executives on reputation and communications strategy.

Own Secret Detection and Vulnerability Research as a product: define strategy across prevention, detection, validation, revocation, and reporting; ship detection content and intelligence with measurable quality; drive adoption, retention, and revenue; partner with engineering, research, and Field; use AI to accelerate research and productization.

Analyzes the Security for AI competitive landscape, including AI detection and response, generative AI security, autonomous agents, prompt injection, and data leakage. Partners with Product, Sales, Marketing, Strategy, and senior leaders to guide product roadmaps, go-to-market strategy, deal support, sales tactics, and competitive positioning. Conducts win/loss analysis and translates complex AI and cybersecurity concepts into executive and field-actionable guidance.

Leads enterprise AI strategy, governance, architecture, platform management, and delivery across manufacturing and corporate functions. Establishes and operates an AI and Automation Center of Excellence; oversees Copilot, agent, intelligent automation, and AI-enabled solutions. Develops roadmaps, governance standards, adoption programs, value measurement, licensing strategy, and delivery pipelines. Advises senior leaders, manages technical teams, evaluates emerging technologies, and partners with business, security, legal, compliance, and external providers to deliver secure, scalable, supportable solutions.

Leads Brain Corp’s autonomy organization, setting technical strategy and overseeing perception, SLAM, motion planning, and robotics engineering teams. Owns architecture, roadmap, talent development, production delivery, fleet performance, safety, and customer outcomes. Requires extensive experience taking learned autonomy models from research into real-world fleets, managing engineering leaders, and partnering cross-functionally on infrastructure, hardware, data, and deployment.

Lead Responsible AI consulting engagements involving AI policy, standards, regulation, governance, operating models, and controls. Advise clients and senior leaders, support sales and proposals, manage project delivery, monitor regulatory developments, engage policy stakeholders, and shape Accenture’s Responsible AI perspective. The role requires substantial consulting, AI regulation, data science, machine learning, and business analytics experience.