machine-learning jobs in San Diego

As a Staff Software Engineer on Qualcomm's Camera Software team, you will design, develop, and optimize camera software for smartphones, AR/VR, automotive, and IoT platforms. Responsibilities include architecting camera Image Signal Processor (ISP) modules, implementing imaging algorithms, tuning image quality, and collaborating with cross-functional teams and OEMs.…See more You will work on system architecture, device drivers, HAL layers, performance optimization, and AI/ML-based imaging features, with opportunities to mentor junior engineers and influence technical direction.

The AI Enablement Specialist will contribute to hands-on development of AI-powered tools and applications while maintaining platforms and infrastructure that support AI deployment. The role bridges technical and business functions, coordinating new AI initiatives from intake through delivery, managing governance and compliance, and providing ongoing support and monitoring.…See more You'll work with business leaders and technical teams to scale AI capabilities across Consumer Banking, requiring proficiency in at least one programming or scripting language and ability to move between technical problem-solving and stakeholder communication.

Staff Machine Learning Engineer role focused on designing and maintaining Qualcomm AI Hub's end-to-end ML compilation pipeline, from PyTorch and ONNX model ingestion through graph optimization to deployable artifacts on Snapdragon SoCs. Responsibilities span compiler infrastructure (graph transformation, op validation, backend dispatch across CPU/GPU/NPU), model catalog automation and CI/CD, and developer tooling for profiling and debugging.…See more Requires 4+ years of software/systems engineering experience (or 3+ with a master's, or 2+ with a PhD), with preferred expertise in ML compiler concepts, ONNX/PyTorch export workflows, and on-device deployment frameworks.

Deloitte seeks a Forward Deployed Engineer to design, build, and deploy AI-enabled solutions and agentic platforms for government clients using Palantir technologies. The role requires hands-on experience building and operating GenAI/LLM-powered systems in production, contributing production-quality code with strong testing and CI/CD practices, and leading project workstreams to translate business problems into scalable AI solutions.…See more The engineer will prototype and deliver working solutions independently within a pod structure while mentoring teammates, balancing quality, safety, latency, cost, and model risk in architecture decisions.

Senior Forward Deployed Engineer at Deloitte GPS building AI-enabled solutions and agentic platforms on Databricks for enterprise government clients. Requires 7+ years software/data engineering experience, 5+ years deploying GenAI/LLM solutions in production, and 5+ years hands-on Databricks expertise across Lakehouse, Agent Bricks, Model Serving, and Genie.…See more Mentors junior engineers, designs scalable AI patterns with human-in-the-loop controls, delivers production-quality code with strong CI/CD and testing practices, and translates complex business problems into deployable AI solutions.

Design, build, and maintain scalable data pipelines and platforms that power high-volume, data-driven applications. Develop and optimize ETL/ELT processes for large, complex datasets using Databricks and Spark, and build backend data services in C# / .NET.…See more Lead technical design decisions, mentor engineers, and leverage AI-assisted coding tools to improve engineering efficiency. Requires 5+ years of data engineering experience, strong expertise with data pipelines and ETL frameworks, and hands-on experience with AWS-based data platforms.

Lead machine learning strategy and development for AppFolio's Leasing products, owning the ML roadmap and autonomous leasing agent architecture. Build evaluation frameworks, model quality infrastructure, and establish ML standards across the Leasing Engineering team while ensuring production-grade reliability, SLOs, and observability.…See more Translate research into shipped features by evaluating fine-tuning approaches, RAG patterns, and agentic systems; operate with production discipline on a SaaS platform serving real customer workflows.

Staff Data Engineer at Illumina seeking a senior individual contributor with 10+ years building and scaling data products on Databricks and Snowflake. The role spans end-to-end ownership of data pipelines across Supply Chain, Manufacturing, and Quality domains, requiring advanced Python, SQL, and data modeling skills with hands-on expertise in Spark, Delta Lake, dbt, and distributed systems design.…See more Responsibilities include designing medallion-architecture data products, embedding governance and data quality, adopting AI in analytics workflows, and mentoring a global engineering team. The candidate will set technical standards, lead architecture decisions, and communicate trade-offs across business, AI, and platform stakeholders.

Lead ML research and production model development for a quantitative trading firm, working hands-on to design, train, and deploy ML systems that directly impact live trading environments. You will drive technical execution across the engineering team, mentor engineers to raise the bar, and translate ambiguous research problems into executable modeling work with measurable real-world impact.…See more The role requires 4–6 years of applied ML experience with 1–2 years of technical leadership, strong fluency in Python and PyTorch, and a track record of shipping production systems in high-stakes contexts.

As a Senior Platform Engineer at ReflexAI, you will design and maintain multi-cloud infrastructure across GCP and AWS using Terraform, Kubernetes, and GitHub, while building golden paths and guardrails that improve developer velocity. You'll own observability and monitoring with Datadog, strengthen security posture through IAM and container security best practices, and establish compliance workflows for SOC 2, HIPAA, and other industry standards.…See more This is a hands-on role requiring 5–7+ years of DevOps/SRE/platform engineering experience, deep cloud expertise, and CI/CD pipeline proficiency. You'll work cross-functionally to reduce operational toil and support an AI-driven product serving crisis support, healthcare, and enterprise customers.

Join Booz Allen Hamilton as an AI Software Developer Intern supporting U.S. Navy missions in San Diego.…See more You'll write and debug code (primarily Python), contribute to AI/ML-enabled automation projects, and work on software integration tasks alongside experienced engineers and cybersecurity specialists. The role is structured to support your academic commitments while you pursue a bachelor's degree in computer science, cybersecurity, or a related STEM field by Summer 2027.

Lead the design, development, and operation of Qualcomm's enterprise AI platform, supporting agentic AI, model lifecycle management, and multi-cloud ML/inference infrastructure. Own core platform services including identity/RBAC, secrets, service meshes, observability, vector stores, and model gateways across on-prem GPU clusters and managed cloud services.…See more Manage a ~10-engineer global team (platform, SRE, MLOps/LLMOps), drive incident response and continuous improvement, and partner with product and security teams on AI governance and high-impact use cases.

Design, build, and maintain scalable batch and streaming data pipelines on AWS and Databricks, developing reusable data engineering frameworks and standardized patterns for ingestion, transformation, and validation. Leverage AI-based techniques to automate data quality checks, anomaly detection, and pipeline self-healing.…See more Define SLIs/SLOs, participate in on-call rotations, and mentor junior engineers while driving adoption of data frameworks and best practices across analytics, reporting, and AI/ML teams.

Staff Analytics Engineer responsible for designing and operationalizing agentic AI workflows, ML models, and Databricks applications at scale. Will build multi-step agent pipelines combining rules, ML models, and reasoning to solve complex business problems, then productionize them with monitoring, drift detection, and retraining strategies.…See more Requires 5+ years of hands-on ML engineering or data science with production system ownership, deep Python proficiency, strong traditional ML foundations, and proven Databricks expertise including notebook apps, dashboards, and ML pipelines. Will serve as technical authority, mentor peers, and influence architectural decisions across teams.

As an Applied AI & Optimization Engineer, you will own optimization algorithms and ML systems powering Firestorm's manufacturing intelligence platform, including scheduling, resource allocation, and constraint satisfaction for a planning workbench and simulation engine. You'll design analytics layers for defect trends and operational intelligence, lead integration of open-source and custom LLMs for cloud and edge deployment in DoD contexts, and productionize algorithmic systems alongside full-stack and infrastructure teams.…See more The role requires 5+ years of applied optimization, operations research, or ML systems experience with deep Python proficiency, fluency in optimization frameworks (MILP solvers, OR-Tools), and a proven track record shipping production systems—not prototypes—to real users. You'll partner with manufacturing domain experts to translate operational constraints into model formulations.

Develop and optimize machine learning software for Qualcomm's AI Stack SDKs (QAIRT, Genie), enabling efficient execution of generative AI models and large language models on low-power Snapdragon platforms. Design core runtime components for resource-constrained AI systems, validate performance/accuracy across use cases, and debug complex issues in embedded AI environments.…See more Requires C/C++ proficiency, Linux development experience, and strong software engineering fundamentals; 2+ years experience for senior roles, project/internship experience for entry-level. Preferred: embedded systems background, generative AI model familiarity, hardware acceleration knowledge, and experience with Qualcomm AI Stack products.

Senior Windows audio software engineer responsible for end-to-end feature development of Voice AI capabilities on Windows, including wake-on-voice, on-device ASR, translation, transcription, and TTS. The role requires designing and implementing Windows audio and driver stack solutions that leverage Qualcomm SoC CPU/DSP/NPU capabilities while meeting strict latency and power targets, with work spanning user-mode and kernel-mode boundaries (UMDF/KMDF).…See more Responsibilities include gathering technical requirements, optimizing low-power audio architecture for always-on use cases, and debugging complex multi-threaded and multi-processor issues across hardware/software boundaries. The engineer will collaborate with cross-functional teams (hardware, DSP, systems, ML, product) and communicate status, risks, and roadmap contributions to technical leads.

As an IC5 Senior Staff Engineer, you will architect and deliver large-scale distributed data platform components centered on Kafka, Apache Iceberg, and Apache Spark. You will lead complex technical initiatives, design high-performance data ingestion pipelines, and define engineering best practices across the organization.…See more The role demands deep expertise in distributed systems, JVM performance tuning, stream processing, and full-stack Data Lake solutions, with hands-on delivery of production systems and mentorship of engineering teams.

As a Data Engineer at Booz Allen Hamilton, you will develop and deploy data pipelines and platforms that organize disparate data sources to yield actionable insights for mission-critical applications. You'll work with Python, SQL, or similar languages to build ETL operations, manage relational and non-relational databases, and support analytics workloads on cloud platforms.…See more The role requires 1+ years of data engineering, ETL, or pipeline development experience, proficiency with source control (GitHub/Atlassian), and Linux/Windows scripting. You'll collaborate with analysts, developers, and data scientists in an agile environment to design, develop, and maintain scalable data solutions.

A junior software developer role focused on designing, implementing, and integrating AI/LLM-enabled automation and analytics for Navy cybersecurity and mission workflows. You will participate in technical discussions with cybersecurity specialists and mission partners, contribute to solution architecture and tradeoff analysis, and deliver hands-on work including scripts, APIs, and AI-assisted workflows.…See more The role requires hands-on coding in Python, API integration (REST/HTTP), version control (Git), and the ability to communicate technical concepts to non-specialists while respecting RMF, security controls, and responsible AI practices in classified or controlled environments.

Senior software engineer developing embedded real-time operating systems (QuRT OS, Zephyr) for high-performance microprocessors. Independently designs, develops, and tests well-defined blocks and complex features while meeting quality, functionality, power, and performance standards.…See more Requires 2+ years of microprocessor design experience, proficiency in C/C++ or Python, and knowledge of embedded systems and computer architecture. Collaborate with cross-functional teams on design reviews, troubleshoot multi-system issues, and stay current with industry trends in DSP, machine learning, and modem technologies.

Principal-level AI/ML Platform Architect responsible for designing and optimizing AI/ML systems across Qualcomm's hardware and software stacks, particularly for Windows PC/Laptop platforms. The role requires deep expertise in performance optimization, bottleneck analysis, and end-to-end system characterization across GPUs, NPUs, and multiple AI domains (computer vision, audio, generative AI, agentic AI).…See more Candidates must demonstrate 15+ years in high-performance computing systems engineering with 5+ years specifically in AI system optimization, and will interface with cross-functional teams to deliver reference implementations, tools, and documentation for third-party developers.

Senior AI Software Engineer responsible for designing, developing, and deploying LLM-powered applications and AI-assisted development workflows within a large-scale enterprise Linux environment (~6M+ LOC, primarily C/C++). Build high-performance GPU-based inference pipelines using vLLM and modern frameworks, develop agentic AI workflows with RAG and tool calling, and integrate LLMs with vector databases and enterprise systems into production.…See more Collaborate across software engineers, AI researchers, and platform teams to productionize AI services while optimizing for performance, latency, scalability, and operational efficiency. Requires 4+ years software development, strong Linux/Red Hat experience, advanced C/C++, Python, LLM/RAG expertise, and GitLab CI/CD workflows.

Senior engineer at Deloitte GPS delivering production-quality code for GenAI/LLM-powered solutions, with 7+ years in software/data engineering and 1+ years hands-on experience building and deploying Claude-based applications. Responsibilities include designing extensible functionality, leading project workstreams, translating business problems into AI solutions, and contributing reusable assets (code, prompt libraries, runbooks).…See more Strong emphasis on testing, CI/CD, logging, documentation, and mentoring junior team members in fast-paced, ambiguous client delivery environments.

This Technical Program Manager role manages the integration of Agentic AI into Qualcomm's engineering infrastructure, focusing on governance, security, and platform enablement. You will coordinate across GSOC, Qualcomm AI Foundations, Cybersecurity, and engineering teams to define requirements, track milestones, and align roadmaps for AI asset management and deployment.…See more The position requires driving cross-functional initiatives that bridge AI platform capabilities with security, compliance, and operational readiness while communicating progress to technical and executive stakeholders.