Top Remote Machine Learning Jobs in San Diego, CA

Conduct applied AI research focused on explainability, reinforcement learning, retrieval-augmented generation, and long-context retrieval. Design, train, and evaluate machine learning models using large-scale healthcare data and distributed infrastructure. Build research prototypes and experimentation frameworks, validate measurable impact, and collaborate with ML Engineering, MLOps, and Product teams to transition innovations into production.

Leads customer-facing development of AI agent systems, multi-agent workflows, BI and ML pipelines, and enterprise data governance solutions. Partners with Fortune 500 stakeholders to translate business and data challenges into production-grade technical solutions, develops reusable delivery patterns and internal tooling, influences product roadmaps, conducts competitive analysis, and mentors engineers and technical teams.

Serve as strategic commercial and technology legal advisor, drafting and negotiating software, SaaS, licensing, data, customer, and vendor agreements. Advise on AI products, governance, responsible AI, privacy, intellectual property, regulatory compliance, product launches, and legal risk mitigation. Partner with Sales, Product, Engineering, and executive teams while supporting international and broader legal initiatives. Use legal technology and AI tools to improve legal service delivery.

Develop and productize deep learning perception systems for autonomous driving, including traffic signal, sign, road marking, and construction object understanding. Lead end-to-end model development, data-driven improvement, simulation, augmentation, and deployment to embedded platforms. Optimize solutions for accuracy, safety, latency, robustness, and regional generalization while collaborating with data-labeling teams and contributing technical leadership.

Develop and productize machine learning models for autonomous vehicle perception, including LiDAR and camera perception, sensor fusion, detection, classification, segmentation, and tracking. Build scalable data, training, metrics, and performance workflows, and implement efficient C++ code for the NVIDIA DRIVE AV platform. Collaborate across engineering teams, track advances in machine learning, and optimize models for real-time embedded inference.

Develop GPU code generation and compiler optimizations for TensorRT to improve generative AI inference performance. Responsibilities include operator fusion, scheduling, specialization, profiling, debugging, numerical validation, and performance analysis. The role requires C++ software development and GPU architecture expertise, with collaboration across hardware, compiler, kernel, and deep learning teams. Preferred experience includes CUDA, MLIR, GPU kernels, Tensor Core optimization, inference frameworks, and low-level NVIDIA performance tools.

Develop and productize machine learning prediction systems for autonomous driving. Responsibilities include designing end-to-end prediction solutions, researching deep learning models, supporting diverse driving environments, prioritizing data collection and labeling, using simulation and augmentation, and meeting safety, latency, and software robustness requirements. The role also involves collaboration with data teams and deployment of real-time ML solutions to embedded platforms.

Develop algorithms and optimizations for inference and compiler stack, enhance performance metrics, collaborate with hardware teams, and publish work on novel approaches.

Build and ship production AI systems for enterprise portfolio and planning workflows. Develop anomaly and signal detection, LLM-powered insight synthesis, natural-language planning rule translation, evaluation frameworks, and MCP tools. Partner with external AI providers initially, then establish internal standards for prompt design, model selection, agent architecture, reliability, and evaluation. Collaborate closely with product, design, and domain engineering teams.

Own the end-to-end machine learning and LLM lifecycle, taking models and agentic AI workflows from experimentation into reliable, scalable production. Design MLOps infrastructure, serving, orchestration, CI/CD, evaluation, observability, and GPU optimization. Build self-service tooling and establish LLMOps standards while partnering with engineering and business teams. The role is fully remote and involves up to 10% travel.

Designs and delivers end-to-end AI/ML solutions on Google Cloud, including data ingestion, feature engineering, model training, deployment, and monitoring. The role leads client discovery, translates business needs into AI/ML strategies, develops roadmaps, provides technical leadership, and supports testing and user training. It requires hands-on Gemini and GCP expertise, customer-facing consulting experience, and collaboration across engineering and product teams.

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.

Develop technical employment-marketing content that showcases Socure’s engineering challenges, architecture, APIs, machine learning, identity, fraud, and infrastructure work. Interview engineers and technical leaders, write blogs, deep dives, whitepapers, and recruiting copy, and distribute content through developer communities, publications, social channels, and talent platforms. Partner with engineering, recruiting, employer brand, marketing, design, and subject matter experts while maintaining editorial quality and using AI tools thoughtfully.

IT Intern supporting employees with hardware, software, network, and device troubleshooting; assisting with installations, system maintenance, documentation, asset inventories, security monitoring, upgrades, cloud integrations, and process automation. The role also involves improving IT workflows, ensuring data security compliance, and collaborating on technology projects during a full-time summer internship.

Establish and lead the People Analytics function, building trusted workforce data foundations, governance, privacy standards, analytical products, workforce planning capabilities, and AI-enabled decision support. Partner across HR, Finance, IT, and business leadership to deliver executive insights, improve workforce decisions, and scale analytics operations. Recruit and develop the analytics team while ensuring responsible data use, global-local compliance, stakeholder adoption, and alignment with organizational priorities.

Founding Product Manager responsible for defining and launching Hightouch’s Agentic Personalization product. The role includes customer discovery, product strategy, agent workflow and approval design, roadmap sequencing, technical decision-making, revenue alignment, competitive positioning, customer calls, and go-to-market collaboration. The PM will work cross-functionally with engineering, design, sales, customer success, founders, and executives to establish product-market fit and scale a new enterprise SaaS offering.

Leads Hightouch’s machine learning organization, including product development, technical roadmapping, recruiting, reliability, and people management. The role focuses on personalization, product recommendations, probabilistic identity resolution, LLM-powered content generation, and scalable machine learning infrastructure for model training and inference.

Design and launch 0-to-1 AI-powered marketing tools for Hightouch’s Agents product suite. Responsibilities include rapid prototyping, customer research, synthesizing usage data and feedback, shaping product strategy, and collaborating with designers, engineers, and product managers. The role requires strong visual, UI, and interaction design skills, comfort with ambiguity, curiosity about AI, and rapid iteration in a remote-first environment.

Develop applied AI research prototypes and systems for agentic marketing applications, focusing on generative image and video, brand asset creation, data workflows, and autonomous evaluation. The role combines probabilistic and quantitative reasoning, backend system architecture, product intuition, experimentation, and customer-focused product development. Responsibilities include building proofs of concept, improving AI-generated media realism and brand alignment, and architecting agentic systems.

Manage complex customer issues, triage support activity, and coordinate escalations across Client Engagement, Product, Engineering, and project teams. Analyze tickets and feedback to identify trends, risks, process gaps, and product opportunities. Improve support operations through documentation, dashboards, workflows, routing logic, playbooks, and feedback loops. Serve as a customer advocate while supporting strategic initiatives and strengthening handoffs, prioritization, and operational decision-making.

Lead data engineering and machine learning initiatives by designing, architecting, developing, and supporting GCP data pipelines. Create information architecture documentation, estimate and plan technical work, collaborate with project teams and business analysts, and translate requirements into technical designs. Develop Python-based ELT pipelines, optimize BigQuery SQL, support CI/CD, and provide technical leadership to projects and teams.

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.

Leads the data science platform and machine learning strategy, building data marts, predictive models, MLOps infrastructure, and analytics capabilities. Analyzes healthcare claims, clinical, workflow, and operational data to risk-stratify patients, assess clinical program impact, support dashboards, and improve patient and provider engagement. Collaborates with clinical, operations, finance, product, executive, and technology teams while serving as a trusted analytics expert for a business workstream.

Generates and qualifies leads through outbound outreach, manages sales pipelines and CRM activity, conducts product demonstrations, guides prospects through the sales process, builds customer relationships, meets quotas, and collaborates with marketing, product, and customer success teams. The role requires inside sales experience, SaaS or technology familiarity, strong communication and negotiation skills, CRM proficiency, and up to 20% travel.

Delivers customer-facing training in AI, data, and software engineering; creates tailored courses, projects, certifications, and assessments on the DataCamp platform. Partners with Customer Success, Sales, Product, and Content teams to design blended learning paths, teach virtual and onsite sessions, tailor materials for varied audiences, and improve customer adoption, satisfaction, and measurable skills.