machine-learning jobs in San Diego

Advanced manager and technical consultant designing and implementing enterprise-scale AI solutions spanning classical ML, generative AI, and agentic AI systems. Responsibilities include architecting AI-powered applications for business transformation (customer service, supply chain, finance, HR, operations), building RAG and autonomous agent workflows, developing ML pipelines, and establishing governance and observability frameworks.…See more Requires 8+ years in AI/ML/data science with 5+ years hands-on experience with Claude, GPT, LLMs, agentic frameworks, and RAG systems, plus deep expertise in prompt engineering, vector databases, and multi-agent architectures.

Lead complex cybersecurity engagements for Chemicals & Natural Resources clients, managing workstreams across cyber defense, risk management, compliance, and operational technology security. Develop and deliver cybersecurity strategies tailored to chemical, oil & gas, mining, and agricultural enterprises, with deep expertise in both IT and OT environments.…See more Coordinate cross-functional project teams, manage budgets and deliverables, and serve as primary stakeholder contact for translating client security priorities into actionable solutions. Guide clients through secure adoption of AI/ML, OT modernization, supply chain digitization, and IT/OT convergence while maintaining regulatory compliance and operational resilience.

Serve as a forward-deployed technical engineer for banking clients, acting as the primary technical point of contact and architect advisor. Design and prototype scalable microservices and cloud-native solutions, conduct discovery sessions and deep-dive technical workshops, and build production-ready POCs that demonstrate platform value.…See more Translate complex architectures and emerging AI/ML patterns into clear guidance for both technical and non-technical stakeholders, while gathering customer feedback to inform product strategy. Requires 5+ years of software engineering with significant client-facing experience, deep expertise in Java, Spring Boot, microservices architecture, multi-cloud deployment (AWS primary), Kafka-based event-driven systems, and hands-on knowledge of LLM integration and agentic AI frameworks.

Design and engineer novel enzymes using AI/ML and computational biology approaches. Apply protein language models, generative design methods, and structure-based machine learning to predict and optimize enzyme function.…See more Develop bioinformatics pipelines, analyze high-throughput screening and sequencing data, and create reusable tools and dashboards for cross-functional protein engineering teams. Requires 5+ years of related experience (or equivalent with advanced degree) and practical expertise in AI/ML applied to protein engineering.

Senior manager role leading OSS (Operations Support Systems) reinvention and modernization for telecommunications service providers. Combines telecom and OSS architecture expertise with AI, automation, and consulting leadership to help clients transition toward autonomous network operations.…See more Responsibilities span strategy, solution architecture, and implementation across service inventory, fulfillment, provisioning, assurance, fault management, and network automation. Requires 10+ years in telecommunications or technology consulting with deep hands-on experience in OSS platforms (Amdocs, Netcracker, Ericsson, Nokia, etc.) and strong knowledge of AI/ML, cloud-native architectures, and TM Forum frameworks.

Lead data engineering and governance initiatives for enterprise clients, architecting AI-integrated data fabric solutions on cloud platforms like Snowflake, Databricks, and Azure Synapse. Design and deliver ETL/ELT pipelines, data integration strategies, streaming architectures, and metadata governance frameworks.…See more Requires 5+ years in data architecture, enterprise data engineering, or AI platform delivery, with hands-on expertise in cloud data platforms, data modeling, API/streaming design, and enterprise system integration (especially Salesforce). Contribute thought leadership and drive client engagements around enterprise data strategy and AI-ready platforms.

Staff Data Scientist leading analytics strategy for Intuit's Connected Accounts product, responsible for owning the analytics agenda end-to-end from account linking through engagement. The role requires applying ML and causal inference techniques to solve connected-accounts-specific problems, designing and running A/B tests and quasi-experimental designs, building member segmentation, and identifying AI/ML opportunities.…See more You will partner closely with Product, Engineering, and Design leadership on roadmap prioritization, mentor other data scientists, and use AI-native tools to synthesize analyses ranging from experiment readouts to churn deep dives.

Design, build, and deploy production agentic AI solutions powered by Claude for enterprise clients, from proof-of-concept through production. Implement multi-agent systems that automate business processes, integrate with enterprise tools, and operate within defined autonomy and guardrails.…See more Modernize existing AI/ML platforms with generative AI capabilities including RAG and agent-based orchestration. Advise clients on generative AI adoption strategy, responsible AI practices, and model selection while partnering with technology, data, and business stakeholders to scope and deliver solutions.

Build and deploy AI/ML solutions for cybersecurity as a senior consulting engineer at EY. You will design frontier AI models, LLMs, and agentic architectures tailored to client security workflows, integrating them with SIEM, SOAR, EDR, and other security platforms.…See more You'll translate client use cases into engineering tasks, develop evaluation harnesses, build secure AI deployment pipelines, and deliver production-ready solutions with clear documentation and testing. The role requires 3–5 years of hands-on software engineering experience, proficiency in Python and cloud platforms (AWS/Azure/GCP), and demonstrated expertise in building or deploying AI/ML systems within security contexts.

Lead a specialized engineering team at the intersection of hardware, software, and AI, responsible for developing innovative Pixel sensor-based features. You'll manage software engineers building real-time embedded systems that leverage sensor signals for on-device AI experiences, requiring deep expertise in embedded software development, computer vision, signal processing, and ML infrastructure optimization.…See more The role demands 8 years of software development experience, 5 years in computer vision or signal processing with ML optimization, and 3 years in technical leadership with 2 years managing teams.

This role is a technical cloud architect for AWS Professional Services focused on Life Sciences and Manufacturing/Supply Chain customers. You will design and implement complex cloud solutions involving AI/ML, IoT, digital twins, supply chain optimization, and manufacturing data platforms — including CMC orchestration, MES/MOM modernization, and agentic supply chain deployments.…See more You'll drive solution architecture from prospecting through sales closure, translating regulatory and compliance requirements (cGMP, GxP, 21 CFR Part 11, FDA/EMA) into technical designs using AWS services like IoT SiteWise, IoT TwinMaker, Bedrock, SageMaker, and Supply Chain tools. The role requires 8+ years of cloud architecture, 7+ years in Healthcare/Life Sciences or Manufacturing industries, and deep expertise in Data & AI technologies, with a bachelor's degree in computer science, engineering, or a quantitative field.

Lead enterprise generative AI architecture and solution design on Oracle Cloud Infrastructure (OCI), focusing on agentic workflows, retrieval-augmented generation pipelines, and Oracle application integrations. Define governance, security, and compliance standards for AI/ML initiatives across the enterprise.…See more Mentor delivery teams on prompt engineering, model selection, and optimization; identify high-value AI use cases and guide pilot deployments that drive business outcomes.

As an AI Science Intern, you will work alongside AI Scientists and Machine Learning Engineers to build, train, and evaluate machine learning and deep learning models on real-world datasets. Responsibilities include data gathering and ETL, feature engineering, model development using techniques like classification, regression, clustering, and neural networks, and designing experiments to measure impact.…See more You'll explore current AI/ML research including generative AI and LLMs, develop proofs-of-concept, and partner with cross-functional teams to translate insights into product features. The role requires strong Python and SQL skills, familiarity with core ML techniques and their mathematical foundations, and the ability to communicate findings to both technical and non-technical audiences.

As an AI and Data Science Engineer III, you will translate business goals into machine learning use cases and develop predictive models for marketing and advertising applications. You'll perform exploratory data analysis, apply clustering and feature transformation techniques, build proofs of concept, and validate solutions.…See more The role requires 5+ years of industry experience applying data science or machine learning methods, with a strong foundation in translating business requirements into model design approaches and collaborating across analytics and data engineering teams.

Design and build large-scale access management systems that enforce least-privilege security across Amazon's infrastructure. Apply AI/ML techniques to automatically detect unused permissions, recommend access decisions, and reduce security risk at company scale.…See more Collaborate with leadership and stakeholders to define access experiences for Amazon's developer community. Contribute across the full software development lifecycle—design, implementation, testing, deployment, and operations—with on-call responsibilities for critical access management services.

As an Autonomy Engineer focused on VLA (Vision-Language-Action) pre-training, you will train capable robotic policies using deep learning, including pre-training base models on multi-embodiment trajectory data, fine-tuning for specific tasks, and optimizing for real-time edge inference. You'll own the full loop from data collection and curation through deployment, partnering with data and MLOps teams to build continuous training pipelines that ingest synthetic data and teleop logs.…See more The role requires 3+ years building production deep-learning systems with hands-on experience in LLMs, VLMs, or generative models, plus strong Python and PyTorch/JAX skills to profile, debug, and write maintainable research code.

Develop Python solutions for natural language processing and machine learning, including text analytics, topic modeling, embedding-based classification, and entity extraction. Build network-analysis capabilities such as knowledge graphs and GraphRAG-like systems, deploy APIs, integrate data feeds, and adapt to new technical environments with limited supervision.…See more Requires 4+ years of Python development experience, an active Secret clearance, and active Security+ certification. Experience with TypeScript front-end development and API deployment is required.

Join XiFin's Advanced Data Analytics team as an Associate Machine Learning Engineer to design, develop, and deploy machine learning models with a focus on LLMs, Generative AI, and Agentic AI in healthcare and revenue cycle domains. You will contribute to MLOps pipelines, perform data preparation and prompt engineering, collaborate with cross-functional teams, and validate models for production use.…See more The role requires a Bachelor's degree in Computer Science, Data Science, or related field, with proficiency in Python, ML libraries (scikit-learn, TensorFlow, PyTorch), and foundational knowledge of GenAI architectures, vector databases, and LLM orchestration frameworks.

As an Autonomy Engineer focused on VLA (Vision-Language-Action) pre-training, you will develop and train deep learning policies for humanoid robots, owning the full pipeline from data collection and curation to model deployment. You'll pre-train base models on diverse multi-embodiment trajectory corpora, fine-tune policies for specific tasks, work with MLOps teams to scale distributed training, and build continuous pipelines that ingest synthetic data and teleop logs.…See more This is primarily a deep learning role requiring 3+ years of experience shipping neural network models, hands-on expertise with LLMs, VLMs, or generative models, and strong proficiency in Python and PyTorch or JAX.

Senior AI Engineer role focused on designing and leading scalable, high-performance data architecture solutions that support AI/GenAI use cases. The role involves building and optimizing data pipelines, defining database schemas (Graph, SQL, NoSQL), and leading infrastructure for AI model deployment across cloud and on-premises environments.…See more Requires 4+ years in data engineering/MLOps with hands-on AWS/Azure/GCP experience, 2+ years managing technical teams, and expertise in DevOps, CI/CD, containerization (Kubernetes, Docker), and ML deployment frameworks. The position includes mentoring junior engineers and driving technology modernization initiatives.

Senior forward-deployed engineer at Deloitte GPS responsible for developing scalable AI engineering patterns and production-quality GenAI/LLM solutions for government clients. Must have 7+ years software/data engineering experience, 1+ years hands-on with Palantir (Foundry, AIP, or Maven), and 1+ years building and deploying LLM-powered solutions in production.…See more Role emphasizes architecture balancing quality, safety, latency, cost, and model risk; delivering well-tested, documented code with strong CI/CD practices; and translating business problems into AI solutions while leading technical workstreams.

This is a hands-on Solution Architect role for an AI-enabled Managed Services team, requiring deep technical expertise in designing end-to-end application architectures spanning UI, APIs, services, data, and AI components. The role combines hands-on coding and prototyping with architecture ownership, emphasizing active participation in codebases, AI tool evaluation, and guiding engineering teams through complex technical decisions.…See more Key responsibilities include designing reference architectures for AI patterns (RAG, vector search, prompt orchestration), defining non-functional requirements (performance, reliability, security), architecting CI/CD pipelines, and ensuring production readiness. The ideal candidate has 8+ years of software engineering experience, strong cloud-native and modern application architecture knowledge, practical AI feature development, and comfort working directly in code and infrastructure.

AfterQuery seeks software engineers with 2+ years of real-world experience to complete AI model training and evaluation projects on a remote, asynchronous basis. Responsibilities include code review, model output evaluation, and original task creation across a range of AI training initiatives.…See more Work is fully independent and project-based, with hourly rates ranging from $50–$100 depending on project qualification.

AfterQuery seeks experienced software engineers to complete remote, project-based work training and evaluating AI models. Responsibilities include code review, model output evaluation, and task creation across various AI training projects.…See more Candidates must have 2+ years of software engineering experience, strong programming fundamentals, and the ability to work independently and deliver well-documented work.

AfterQuery seeks experienced full-stack engineers to participate in remote, project-based AI model training and evaluation work. Responsibilities include completing software engineering tasks, reviewing code and model outputs for correctness, and delivering well-documented work independently.…See more Requires 2+ years of real-world software engineering experience and strong fundamentals in at least one major programming language.