Top Remote Machine Learning Jobs in San Diego, CA

Design, build, and deploy novel sensor hardware and data acquisition systems; curate geoscientific datasets; develop statistical, physics-based, and ML models (2D/3D) to predict mineralization; create visualizations and evaluation tools; collaborate with geoscientists, engineers, and vendors; deploy sensors in the field and integrate results to guide exploration programs.

Lead end-to-end supply chain transformation engagements, advising executives and directing multidisciplinary teams to improve planning, procurement, logistics, inventory, and supplier performance. Design future-state architectures, build business cases, drive implementation, grow client relationships, and scale practice capabilities while delivering measurable operational and financial impact.

Lead end-to-end supply chain transformation engagements for commercial and utility clients. Advise executives, design future-state supply chain architectures, oversee implementation across planning, procurement, logistics, and analytics, build financial value cases, and manage multidisciplinary teams to deliver measurable operational and financial results.

The Enrollment Advisor helps prospective patients through the onboarding process, providing information and support throughout their enrollment in Revero's program.

As a Software Engineer, you will design solutions, write quality code, collaborate with teams, and ensure efficient data delivery for client applications.

SoftSnow is seeking an AI Ethicist to define ethical guidelines, assess risks, and ensure compliance in AI implementations across various industries.

The Senior Principal Product Manager will lead Rockerbox's measurement and modeling products, ensuring accurate methodologies and partnering with Data Science and Engineering to drive product strategy and execution.

Lead machine learning initiatives, oversee product development, improve execution pace, enhance team reliability, and foster team growth at Hightouch.

Lead vision, strategy, and roadmap for data products powering catalog, taxonomy, recommendations, ads, and AI/ML systems. Partner with data engineering to build data platform, governance, identifiers, and quality metrics. Ship data-driven experiences for retailers, partners, and internal teams and translate data quality into measurable business outcomes.

Provide technical advisory and solution feasibility analysis for enterprise AI initiatives. Evaluate AI engineering approaches, integration complexity, reusable components, and architectural tradeoffs. Support prototyping guidance, vendor capability evaluation, and surface governance, risk, and technical constraints to inform enterprise decisions.

Lead product vision and roadmaps across multiple initiatives for Sift's fraud-prevention platform. Partner with engineering, data science, sales, and marketing to define requirements, write specs, run customer discovery and beta programs, and drive go-to-market and adoption. Balance technical execution with strategic portfolio-level product strategy.

Remote technical recruiter responsible for sourcing and hiring software engineers and niche technical talent for startups. Tasks include sourcing via LinkedIn and job boards, shortlisting, verifying technical fit, researching companies and market trends, developing and executing recruitment strategies, and communicating with candidates and stakeholders. Immediate joiners preferred.

Apply machine learning to large datasets to build predictive models, perform data mining, and develop algorithms. Analyze results, create visualizations, and provide insights to inform business decisions.

Lead architecture, design, development, deployment, and optimization of an agentic AI platform. Partner with product, data, security, and business teams to productionize AI solutions, establish engineering best practices, mentor teams, and drive reusable AI services, automation, and operational improvements to deliver business impact.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

Build and operate ML training and serving infrastructure by designing, developing, and launching backend systems. Collaborate across teams to decompose projects, support operations and on-call, create monitoring and metrics, perform code reviews, and contribute to developer velocity and platform reliability.

Own Cash Application and Deduction Resolution Management products end-to-end. Lead discovery, define requirements, prioritize roadmap, partner with engineering/design/sales, ensure financial accuracy, build ERP integrations, drive launches, and maintain product quality and customer-focused outcomes.

The Director of AI & Automation leads GT's enterprise-wide AI and automation strategy, driving initiatives to enhance operational efficiency and improve service delivery in a regulated environment.

The Director of Product Management will oversee the product lifecycle for AI products, focusing on customer collaboration, rapid prototyping, and product strategy. The role involves leading product teams, driving execution, and shaping the product culture.

The VP of Marketing will lead the marketing ecosystem to drive growth, define competitive advantages, influence product design, and mentor a diverse team towards a mission-driven culture.

The SAP Innovation Architect will design SAP automations, mentor engineers, and drive innovation in AI-driven SAP operations, while ensuring scalability and security in integrations.

As a GTM Engineering Intern, you will automate workflows, design demos, and develop AI-powered tools for market outreach while collaborating with sales and engineering teams.

The Senior Data Scientist will develop scalable ML models, analyze large datasets for insights, and collaborate with teams to enhance business performance through data-driven solutions.

The Customer Success Manager drives the adoption of AI solutions in life sciences by managing implementations, developing customer satisfaction strategies, and serving as a trusted advisor.

Two research fellows will receive a stipend and compute credits to pursue projects in legal AI and automated negotiation. Fellows get expert access, private contract data, and are expected to produce a publishable paper, benchmark, or open-source artifact. Research topics include reward modeling under expert disagreement, negotiation simulation, minimal-diff editing benchmarks, uncertainty/hand-off strategies, or related legal AI problems.