data-science jobs in San Diego

The role seeks a Databricks & AWS Data Engineering Architect to lead enterprise-scale data migration and modernization programs for a banking client. The architect will design and implement data solutions using Databricks, PySpark, SQL, and AWS, with responsibility for CI/CD pipelines, data governance frameworks, and data quality monitoring.…See more Required skills include hands-on expertise in data engineering, data warehousing, and data architecture, along with leadership capabilities to manage stakeholders and drive engineering best practices across the organization.

Senior AI Engineer building AI-powered learning systems for Shield AI's Hivemind autonomy platform. The role involves developing an AI training coach for context-aware guidance, creating tooling to generate technical workshops and curricula from learning objectives, and partnering with autonomy experts to produce assessments and labs.…See more Success is measured by shipped learning products, reduced time to technical proficiency, and demonstrated improvement in customer capability and product adoption.

This System Analyst role supports technology operations for San Diego State University's Office of Housing Administration, overseeing help desk and residential technology services for 9,000+ students. The analyst manages software systems (StarRez, CBORD, Jamf, Intune, Azure, Active Directory), troubleshoots network and audiovisual infrastructure, and leads student technology staff through recruitment, training, and coordination.…See more Responsibilities include ServiceNow case management, device management across enterprise platforms, system integrations, and recommending hardware and process improvements. The position requires hands-on technical support, cross-campus collaboration, and leadership of support staff.

Design, create, and implement production-grade AI/ML systems for Defense and Intelligence clients. You'll architect scalable machine learning solutions handling fast-moving data, deploy models across multiple data modalities using frameworks like TensorFlow and PyTorch, and integrate solutions into mission environments.…See more The role requires 2+ years of ML engineering or data science experience, proficiency with ML frameworks and programming, and hands-on work in deep learning, computer vision, NLP, or signal processing.

Staff-level machine learning software engineer responsible for designing, implementing, and optimizing ML software for embedded systems including mobile, edge, auto, and IoT products running on ARM, DSP, and GPU processors. Primary responsibilities include developing and optimizing ML kernels and frameworks (TensorFlow, PyTorch) for efficient hardware execution, implementing performance-critical software in C++/Python, and collaborating with hardware teams on joint design and optimization.…See more Will lead complex projects involving integration, testing, and tool development for embedded ML subsystems, coordinate cross-team dependencies, and contribute to design reviews and technical planning.

Lead the design, build, and operation of enterprise-scale Databricks Lakehouse platforms at Qualcomm, driving AI-native development, MLOps practices, and cloud modernization. This hands-on Staff IT Engineer role requires 4–5 years of Databricks experience and 8–12 years total IT background, with responsibility for platform architecture (Delta Lake, Unity Catalog, Workflows), machine learning enablement (MLflow, Mosaic AI), AIOps automation, and technical mentoring of engineers.…See more You will establish engineering standards, optimize platform performance and cost, implement observability and self-healing automation, and drive adoption of generative AI tools and intelligent automation across development teams.

San Diego State University seeks a System Analyst to oversee customer support and technology operations for its Office of Housing Administration, managing help desk and RezCon operations including student staff recruitment and training. The role requires troubleshooting network and technology issues, managing ServiceNow and StarRez cases, and supporting residential technology infrastructure.…See more Responsibilities include managing housing-specific applications (StarRez, TMA, CBORD, RezLife), device management platforms (Jamf, Intune, Active Directory, Azure), audiovisual and networking components, and collaborating with campus IT on system integrations. The analyst will provide lead work direction to technology support staff and recommend hardware and software improvements.

As a Forward Deployed Engineer IV in Applied AI at Google Cloud, you will lead end-to-end engineering for production conversational AI systems, transforming prototypes into scalable agentic workflows deployed at customer sites. You'll architect multi-agent systems using frameworks like ReAct, optimize RAG implementations, debug agent logic across microservices, and connect AI systems to enterprise infrastructure.…See more The role requires 8+ years of software development (Python or similar), experience with infrastructure-as-code (Terraform), cloud platform deployment (GCP), and hands-on full-stack application development. You'll travel up to 50% and work directly with customers to establish production AI journeys while identifying patterns that feed back into product improvements.

Chief AI Subject Matter Expert leading the development of intelligent data processing pipelines, NLP systems, and AI-enabled dashboards for defense applications. The role requires 15+ years of experience with generative AI, LLMs, and agent-based development workflows, including hands-on use of tools like GitHub Copilot and Claude for code generation and automation.…See more Responsibilities include prototyping emerging AI tooling, mentoring engineering teams on AI integration, designing secure production AI solutions, and identifying opportunities to accelerate the software lifecycle through AI and automation. Must demonstrate expertise in LLM APIs, RAG architectures, vector databases, prompt engineering, and AI-specific security considerations in classified/sensitive environments.

Design and build AI agents and full-stack web applications that automate enterprise workflows, with expertise in agentic AI frameworks, LLM orchestration, and generative AI integration. Architect a multi-agent platform enabling PM and engineering agents to exchange plans and context, while developing backend services in C#/.NET/Python/TypeScript and modern Angular/React frontends that connect to enterprise systems like Jira, Microsoft 365, and SQL/NoSQL databases.…See more Define agentic engineering standards including tool contracts, prompt management, guardrails, and agent evaluation. Requires hands-on experience with LLM application development, RAG, tool calling, prompt engineering, agentic runtimes (LangGraph, AutoGen, n8n), and full-stack enterprise application development on AWS or Azure.

Build production inference systems that turn ML research prototypes into deployed, performant components under strict latency, throughput, memory, and accuracy constraints. Own the full pipeline from model optimization through deployment: profile and tune tensor execution, write Rust/C++/CUDA where necessary, build evaluation machinery tied to product metrics, and maintain reproducible deployment contracts.…See more You'll collaborate with research teams to surface shipping risks early and translate algorithmic work into engineering reality with explicit performance budgets and regression gates.

Develop and optimize AI sample applications for Windows on Snapdragon, covering diverse AI models and use cases while integrating Snapdragon-optimized libraries. Create performance and accuracy diagnostics, documentation, and features for the Qualcomm AI toolkit to support third-party application developers.…See more Analyze agentic AI platforms on Snapdragon and competing devices, develop hybrid local-cloud AI experiences, and provide technical guidance on customer issues and project planning.

The NPI Staff Program Analyst manages New Product Introduction operations across Qualcomm's business units, coordinating engineering, program management, and supplier activities from product conception through customer sampling. Responsibilities include generating build plans, tracking material procurement and BOM requirements, monitoring critical milestones, leading cross-functional operations meetings, and troubleshooting supplier issues to keep programs on schedule.…See more The role requires working cross-functionally with internal teams and external suppliers to execute a full range of NPI support activities. Candidates need a bachelor's degree in business, management, engineering, or related field (or equivalent work experience).

Design and build AI agents that automate workflows within a multi-agent platform, enabling PM and engineering agents to exchange plans and context over shared program data. Develop full-stack web applications with generative AI functionality—conversational interfaces, natural-language querying, automated summarization, and in-context recommendations—using C#, .NET, Python, TypeScript, Angular/React, and integrations with Jira, Microsoft 365, Confluence, and SQL/NoSQL stores.…See more Define agentic engineering standards including tool contracts, MCP servers, prompt management, memory, guardrails, human-in-the-loop approval, and evaluation harnesses. Requires hands-on experience with LLM application development, agentic runtimes like LangGraph or AutoGen, full-stack enterprise development, and cloud deployment on AWS or Azure.

As a Machine Learning Engineer at Qualcomm, you will develop and optimize machine learning frameworks, tools, and algorithms for deployment across mobile, edge, automotive, and IoT products. You will collaborate with cross-functional teams to design hardware-software co-optimized solutions, build efficient inference and training systems, and create ML kernels and compiler tools.…See more The role requires proficiency in ML frameworks (TensorFlow, PyTorch, Keras), embedded systems optimization, and programming languages like Python or C++, with experience in problem domains such as NLP or multimedia.

This role combines prompt engineering expertise with AI system governance and enterprise adoption strategy. The engineer will optimize LLM performance across platforms (OpenAI, Anthropic), design and configure AI agents and chatbots with knowledge grounding, and establish prompt governance frameworks and best practices.…See more Success requires 5+ years in AI/ML systems, 2+ years of hands-on prompt engineering, and demonstrated ability to evaluate AI performance, manage knowledge systems, and guide enterprise clients through AI tool adoption and deployment.

Design, implement, and verify machine learning software for embedded ARM processors, DSPs, and GPUs in mobile, edge, automotive, and IoT products. Optimize ML kernels, frameworks (TensorFlow, PyTorch), and compilers to leverage specific hardware capabilities; develop in C++, C, or Python with focus on performance tuning and integration testing.…See more Collaborate with hardware teams on joint design/development, coordinate dependencies across teams, and contribute to design reviews and project meetings.

Senior Data Engineer responsible for designing and implementing cloud data platforms (Databricks, Snowflake, BigQuery) and enterprise-scale data warehouses using Medallion Architecture. Will develop scalable ETL pipelines, optimize Spark jobs, integrate ML models into data workflows, and implement data governance and lineage tracking.…See more The role requires hands-on expertise in Python, PySpark, SQL, and AWS services, plus experience with AI/ML integration, DevOps practices (Terraform, CI/CD), and mentoring junior engineers and analysts.

Qualcomm seeks a Senior AI Performance Architect to design hardware accelerator architectures optimized for AI training at scale. The role involves analyzing GPU/accelerator architectures, defining computational blocks supporting multiple datatypes and precisions, architecting memory and scale-out systems, and codesigning hardware with software/LLM requirements.…See more Responsibilities include competitive analysis, performance modeling, and pre-silicon prediction for ML training workloads. The ideal candidate spans software architecture, algorithm development, kernel optimization, and hardware accelerator design.

Build and scale evaluation harnesses and automation for AI-powered software development tools, turning real engineering artifacts into repeatable benchmark tasks. Develop versioned, reproducible processes with containerized environments to measure AI tool performance across quality, productivity, and efficiency metrics.…See more Validate evaluation approaches against human judgment, analyze results for variance and failure patterns, and work with engineering and data teams to improve tooling and document findings.

Lead a Data Engineering team to establish modern DataOps and CI/CD practices, mentor engineers in PySpark, SQL, dbt, Fivetran, and cloud-native development, and design scalable data infrastructure across GCP, Azure, and AWS cloud data warehouses (BigQuery, Snowflake, Databricks). Manage technical delivery, collaborate across enterprise teams to develop end-to-end data solutions, and align data initiatives with business goals while remaining current on industry trends.See more

Senior architect responsible for designing and leading enterprise-scale data platforms on Databricks and AWS, including cloud modernization, data migration, and lakehouse architecture. Requires deep expertise in PySpark, advanced SQL, Delta Lake, and data warehousing patterns, with accountability for technical strategy, solution design, and mentoring engineering teams.…See more Will drive CI/CD practices, data governance frameworks, data quality standards, and technical decision-making across complex data infrastructure initiatives. Expected to engage senior stakeholders, manage client relationships, and champion AI-powered engineering tools for productivity and automation.

Sr Manager leading a team of Platform Engineers/DataOps analysts to architect, deploy, and manage enterprise-scale Databricks Unity Catalog across dev/test/production environments. Responsibilities span platform governance, fine-grained access control (RBAC/ABAC), workspace automation via Terraform, CI/CD pipeline design (GitHub Actions, Azure DevOps, GitLab CI), FinOps optimization, and incident management for critical data infrastructure.…See more Requires 10+ years in data operations/platform engineering with 5+ years as a lead Databricks administrator, deep expertise in Unity Catalog governance, cloud security (IAM, VPC/VNet, compliance), and proficiency in Python, PySpark, and SQL.

Design, build, and operate production ML systems across the full lifecycle—from data preparation and model training through deployment, monitoring, and continuous improvement. Partner with data scientists, software engineers, and platform teams to turn research prototypes into reliable, scalable services.…See more Work across recommendation, ranking, forecasting, classification, NLP, and generative AI depending on product priorities. Balance model quality, inference latency, scalability, and operational resilience as equally important outcomes.

The Senior BI Developer & Commercial Analyst owns and modernizes the Commercial Insights & Analytics team's Power BI environment, including semantic models, DAX, Power Query, and reporting infrastructure. The role involves migrating legacy Qlik dashboards and Excel reports to Power BI, rebuilding the commercial data layer in Databricks, and delivering ad hoc analysis, forecasting, and market insights for strategic commercial initiatives.…See more Strong technical skills in Power BI, SQL, Databricks, and DAX are required, along with the ability to translate business needs into reliable, fast, and accurate reporting solutions. The position demands comfort with ambiguity, accountability, and the ability to move quickly without sacrificing data integrity.