machine-learning jobs in San Diego

Qualcomm's Location Technology team seeks a Senior Engineer to validate and commercialize next-generation positioning solutions (GNSS, Assisted GNSS, cellular, Wi-Fi, sensor fusion) across mobile, automotive, wearables, XR, and IoT platforms. The role focuses on system-level test strategy development, log/trace analysis, and root-cause debugging of complex multi-sensor location systems.…See more A key expectation is building automation tools, data-analysis pipelines, and AI-assisted workflows to accelerate test development, log analysis, KPI evaluation, and reporting. The candidate will collaborate with systems, software, algorithms, and product teams to drive feature commercialization and continuous engineering productivity improvements.

Design and architect AI/ML platforms optimized for Qualcomm's hardware (GPU/NPU) and software stack, with focus on end-to-end performance analysis, algorithm tuning, and system bottleneck reduction. Analyze ML workloads across Computer Vision, Audio, Generative AI, and Agentic AI domains; correlate device performance against pre-silicon predictions; and develop reference implementations and tools for third-party developers.…See more Requires 15+ years in high-performance computing systems engineering or software with 5+ years in AI system optimization, strong expertise in AI frameworks and performance profiling, and ability to lead cross-functional teams and articulate complex technical concepts.

As a Multimedia Engineering Intern at Qualcomm, you will work on system-level architecture, analysis, and optimization of multimedia technologies including camera, video encoding/decoding, audio, speech, GPU, and computer vision across Snapdragon devices. The role focuses on HW/SW co-design and power/performance optimization for billions of devices globally.…See more You'll contribute to projects in graphics, computer vision, imaging, speech/audio, video processing, or software tools, depending on your background and interests. The internship requires 11–14 weeks availability (May–September 2027) and a strong foundation in C/C++, Python, and domain-specific knowledge (signal processing, deep learning, or GPU/graphics experience preferred).

Senior Embedded Software Engineer at Qualcomm's Data Center Business Unit designing and developing firmware and software solutions for cloud edge and data center ML workloads on high-performance silicon. The role requires deep expertise in embedded software (BSP, device drivers, RTOS, secure boot, TrustZone) and low-level C programming, with hands-on experience in board bring-up, debug tools (JTAG/SWD), and SoC architecture.…See more The candidate will work on critical technologies including ML acceleration, memory management, virtualization, and DMA-based data movement, collaborating across internal and cross-functional teams.

Qualcomm seeks a Machine Learning Engineer to design, develop, and deploy generative AI solutions focused on Large Language Models, Retrieval-Augmented Generation (RAG), and intelligent agent systems. The role involves implementing RAG-based solutions, optimizing LLM fine-tuning strategies, building evaluation frameworks, and maintaining agentic workflows for autonomous AI systems.…See more The candidate must have strong Python programming skills, practical LLM deployment experience, and familiarity with ML frameworks like PyTorch and TensorFlow, alongside knowledge of vector databases, cloud platforms (AWS, GCP, Azure), and modern MLOps infrastructure.

Join Booz Allen's competitive Summer Games internship program as a software developer, working in teams to solve complex, real-world problems for government and commercial customers. You'll apply programming skills (Java, JavaScript, C, C++, Python, etc.) and experience with machine learning, data mining, or algorithms to develop breakthrough solutions, produce technical documentation, and present your work to senior leadership.…See more The program simulates a startup accelerator environment with mentorship, collaboration, and culminates in a Challenge Cup competition.

Design and implement secure, scalable cloud infrastructure supporting enterprise data platforms, analytics workloads, and AI/ML environments. Lead cloud architecture strategy including service provider selection, deployment models, and migration techniques.…See more Evaluate emerging cloud and virtualization technologies, collaborate with data engineering and data science teams on enterprise data strategy alignment, and maintain expertise in cloud service delivery models, containers, automation, and infrastructure management.

Software engineer developing oncology applications that integrate laboratory systems, data pipelines, and enterprise platforms. The role requires building AI-enabled capabilities (information retrieval, NLP extraction, summarization), deploying on Lilly cloud infrastructure, and owning application reliability and lifecycle.…See more Requires 4+ years of software engineering experience with BS/MS in computer science or related field; strong Python or modern server-side language skills, web frameworks (Django, Flask, Rails), front-end development, cloud deployment (AWS preferred), CI/CD, containerization, and familiarity with LLM APIs and agentic patterns are preferred.

Entry-level systems engineer role supporting intelligence and defense customers in C4ISR, geospatial intelligence, and mission management domains. Responsibilities include requirements analysis, technical documentation, agile capabilities and user story generation, interface mock-ups, and hands-on testing in a rapid development environment.…See more The role requires a BS in engineering/technical discipline with exposure to MBSE, digital engineering, requirements tracking, and testing methodologies; business travel for product demos and system testing is expected.

As an AI Performance Engineer at Qualcomm, you will create and implement machine learning techniques, frameworks, and tools for efficient discovery and deployment of ML solutions across mobile, edge, auto, and IoT products. You will model, architect, and develop advanced ML hardware co-designed with software, optimize software for AI model deployment on hardware (kernels, compilers, model efficiency tools), and develop ML techniques into products.…See more You will conduct experiments to train and evaluate ML models, work independently with minimal supervision, and provide technical guidance to team members. The role requires 4+ years of hardware/software/systems engineering experience, proficiency with ML frameworks (TensorFlow, PyTorch, Keras), embedded systems optimization, and programming languages suited for ML (Python, C++, R).

As an LLM Engineer at Qualcomm, you will create and implement machine learning techniques, frameworks, and tools for efficient discovery and deployment of ML solutions across mobile, edge, auto, and IoT products. You will model, architect, and develop advanced ML hardware co-designed with software, develop optimized software for AI model deployment (kernels, compilers, model efficiency tools), and lead ML technique application into products.…See more You will work independently with minimal supervision while providing technical guidance to team members and collaborating across cross-functional teams on joint hardware-software design.

Lead engineering and data science roadmap for Teradata's AI Platform, overseeing architecture, LLM integrations, RAG pipelines, vector store implementations, and data science experimentation frameworks. Partner with product, research, and engineering teams to define requirements for predictive modeling, multi-agent collaboration, and tool orchestration.…See more Manage and mentor a team of backend engineers, data scientists, and AI platform specialists while driving technical excellence, cloud-native practices, and platform scalability.

An AI Solutions Architect role focused on designing and developing analytics solutions using Palantir Foundry for U.S. Defense clients.…See more The role requires 3+ years of Python or TypeScript experience, hands-on expertise with Palantir Foundry AIP, Ontology Manager, data ingestion/transformation tools, and CI/CD workflows. You'll work within Agile teams to translate stakeholder requirements into technical solutions integrating data engineering, data science modeling, and AI/ML capabilities.

Senior Manager leading R&D strategy for digital health and AI/ML solutions in neuropsychiatry at a major pharmaceutical company. The role spans developing and validating digital endpoints, patient stratification approaches, and clinical trial optimization using advanced statistical modeling, multimodal data integration (digital phenotyping, speech/language analytics, imaging, biomarkers, omics), and longitudinal analysis.…See more Requires 6+ years in pharma/biotech analytics with demonstrated expertise in clinical development, digital health technologies, biostatistics, and machine learning; PhD or MD in a quantitative or clinical field preferred. Reports to senior leadership, partnering cross-functionally with clinical operations, regulatory affairs, and external collaborators to advance digital health standards and support regulatory qualification of novel endpoints.

Senior Full-Stack Software Engineer responsible for designing and maintaining end-to-end web applications powering Clairyon's clinical AI platform. The role requires building production-grade machine learning integrations, secure APIs for real-time clinical and sensor data ingestion, and optimized data pipelines and model-serving infrastructure.…See more The engineer will collaborate with data scientists, clinicians, and product teams to translate research models into scalable software solutions, with daily tasks including code reviews, testing, documentation, and architectural contributions. Required expertise spans full-stack development (Python, TypeScript, JavaScript), cloud platforms (AWS), containerization (Docker, Kubernetes), AI agents and RAG architectures (LangChain, DSPy), healthcare data standards (HL7 FHIR), and healthcare compliance (HIPAA).

Sr. SQA Engineer responsible for designing, developing, and executing comprehensive test plans for Pyxa™ Instrument software, including thick-client C# applications, web and cloud applications, and bioinformatics pipelines.…See more The role involves functional, regression, integration, and performance testing of software interfacing with hardware systems, test automation using tools like Selenium and NUnit, defect tracking in Azure DevOps, and collaboration across software, mechanical, electrical, systems, and bioinformatics teams. Requires 6–8 years of SQA experience, ideally with genomics pipelines and cloud applications, proficiency in Windows/Linux/Azure environments, and strong automation and problem-solving skills.

Build and deploy production-grade AI models that power Petco's e-commerce platform, including personalized recommendations, demand forecasting, and price optimization. Design and maintain robust MLOps pipelines for automated model retraining, monitoring, and 24/7 reliability across web and mobile.…See more Partner with Software Engineering and Mobile teams to integrate AI features into production systems, and mentor junior engineers on ML engineering best practices. Experiment with emerging technologies like Generative AI and LLMs to drive business impact.

Senior Engineer, Software role focused on building and improving internal developer platforms, tools, and workflows at Shield AI. Responsibilities include bringing agentic AI into developer tooling, partnering with engineering teams to reduce friction, enabling collaboration through accessible tools and standards, and driving adoption through feedback and metrics.…See more The role requires 4+ years of software engineering experience with demonstrated expertise in developer tools, backend services, APIs, and distributed systems, plus strong systems thinking and cross-team collaboration skills. At the Staff level, the role expands to leading cross-team initiatives and shaping organizational approach to developer productivity.

AppFolio is hiring a Staff Machine Learning Engineer to design, build, and operate their ML platform on AWS, supporting training, fine-tuning, inference, RAG, and cost optimization across the organization's AI initiatives. You'll partner with applied AI and research teams to productionize prototypes, maintain multi-provider LLM reliability (OpenAI, Google, Anthropic), and operate AI safety guardrails and authorization layers.…See more The role requires production-scale ML infrastructure experience on AWS (ECS, SageMaker, GPU fleets), deep knowledge of model serving and inference optimization, hands-on language model training, and demonstrated cost discipline across AI workloads.

Engineering Lead responsible for hands-on ML research, model development, and production AI system deployment in a live trading environment. You will work closely with quantitative research leadership to shape and execute the research agenda, design and train models, lead day-to-day technical execution across the engineering team, and mentor engineers to raise overall technical standards.…See more The role requires 4–6 years of applied ML/AI experience with 1–2 years of technical leadership, strong proficiency in Python and PyTorch, and a track record of shipping production ML systems where model performance directly impacts real-world outcomes.

Design, build, and operate enterprise-scale Databricks lakehouse platforms for a global semiconductor company. Lead AI-native development practices, machine learning enablement, and AIOps automation while mentoring engineering teams and establishing technical standards.…See more Drive platform modernization, cloud-native practices, and intelligent data/AI infrastructure at scale. Requires 4–5 years of hands-on Databricks experience, strong Python/SQL/Spark skills, MLOps expertise, and proven technical leadership.

Staff-level ML software engineer responsible for designing, implementing, and optimizing machine learning software for embedded systems including mobile, edge, automotive, and IoT products. Will develop and optimize ML kernels, frameworks (TensorFlow, PyTorch), and compilers in C++/Python to leverage specific hardware features on ARM, DSP, and GPU processors.…See more Responsibilities include performance optimization, integration, testing, tool development, and close collaboration with hardware teams. Requires a Master's degree in EE/CS or related field plus 3+ years of relevant experience.

Design, develop, and test Mission Systems software for defense applications, collaborating with cross-functional teams (IPT Leads, Integration/Software Requirements Engineers, developers) in a team-oriented environment. The role requires proficiency in C++ and Java, hands-on experience with container tools (Docker, Podman, Kubernetes), Linux/Windows server administration, and cross-platform software integration.…See more Additional responsibilities include post-flight data analysis for system validation and continuous improvement, with a preferred background in machine learning for sensor fusion and autonomous sensor management.

Sr. SQA Engineer will design, develop, and execute comprehensive test plans for thick-client C# applications, web applications, cloud applications, and bioinformatics pipelines.…See more Responsibilities include functional, regression, integration, and performance testing on software interfacing with hardware systems; automating test cases using tools like Selenium and NUnit; identifying and tracking defects in Azure DevOps; and collaborating with software, mechanical, electrical, and bioinformatics engineers. Requires 6–8 years of SQA experience, preferably with genomics pipelines and cloud applications; strong proficiency in Windows, Linux, and Azure; and expertise with test automation frameworks.

Software engineer with 6+ years of backend development experience (or 4+ with a Master's degree) designing and optimizing high-performance algorithms for radar, optical, and infrared sensor systems. You'll work with a cross-disciplinary team to engineer scalable distributed systems, accelerate code on GPUs using CUDA, and integrate scientific codebases in Linux/Unix environments.…See more Strong expertise in C/C++, high-performance computing, MPI, parallel/distributed processing, and AI/ML algorithms is required, along with advanced mathematics or physics foundations and proven system-level problem-solving ability.