deep-learning jobs in San Diego

Shield AI seeks software engineering interns for a 10–12 week paid program working on autonomous systems across applications, embedded firmware, machine learning, and systems platforms. Interns will analyze requirements, write production-quality code, and ship real features alongside full-time engineers using Agile practices.…See more Candidates should have proficiency in modern programming languages (C, C++, Python, Java, or JavaScript), solid foundations in data structures and algorithms, version control experience, and strong problem-solving skills. The role offers hands-on mentorship and potential for a full-time offer upon completion.

Engineering Lead responsible for designing, developing, and deploying production ML models for live trading environments while leading day-to-day technical execution across the engineering team. You will work with leadership to shape the research agenda, mentor engineers, drive adoption of AI tools to accelerate engineering workflows, and build/improve core ML infrastructure including data pipelines, training workflows, and inference systems.…See more The role requires 4–6 years of applied ML/AI experience with 1–2 years leading technical projects or teams, strong proficiency in Python and PyTorch, and a track record of shipping ML systems where model performance directly impacts business outcomes.

Design, architect, and deploy on-device AI prototype software for edge computing applications at Qualcomm's AI Research division. You will work with modern deep learning frameworks (PyTorch), optimize neural network models for embedded deployment, and integrate cutting-edge AI technologies into mobile, IoT, and autonomous systems.…See more The role requires strong Python and C/C++ skills, deep learning expertise, embedded software development experience, and solid software engineering fundamentals.

Develop high-performance GPU kernels and runtimes for accelerating machine learning and image processing on Qualcomm Adreno GPUs. Optimize drivers for OpenCL, OpenGL ES, Vulkan, and DirectX APIs, working closely with hardware designers to understand and improve hardware/software interfaces.…See more Implement machine learning inference and training acceleration, write unit tests and documentation, and collaborate with partners and OEMs. Requires strong C/C++ skills, familiarity with GPGPU APIs like CUDA or OpenCL, and understanding of data structures, algorithms, and object-oriented programming.

Senior ML engineer role focused on architecting, designing, and deploying on-device AI prototype software at the edge. Requires strong Python and C/C++ skills, deep learning expertise (PyTorch), and embedded software development experience.…See more The role involves model fine-tuning, quantization, hardware acceleration, and inference optimization for deployment on smartphones, autonomous vehicles, IoT, and robotics platforms. Must have 3+ years relevant experience and a strong theoretical ML background combined with modern software engineering practices.

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.

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.

Qualcomm seeks a Staff-level automotive software test engineer with 4+ years of systems test engineering experience to develop and execute test strategies for ADAS, autonomous driving, and AI/multimedia technologies. The role requires expertise in functional safety testing, HIL/SIL methodologies, test automation (C/C++, Python), and validation across embedded Linux, QNX, and Android platforms.…See more You will design and execute manual and automated test cases, debug complex issues, and collaborate cross-functionally on fast-paced automotive connectivity and autonomy programs.

Senior staff-level test engineer for automotive software systems, focusing on ADAS, autonomous driving, and AI infrastructure. Role requires designing and executing manual and automated test plans, with expertise in HIL/SIL methodologies, multimedia/computer vision/AI technologies, and automotive functional safety.…See more Candidate should have 10+ years of systems test engineering, test automation (C/C++, Python), and embedded systems experience across Linux, QNX, Android, and kernel/driver domains.

The Senior Machine Learning Engineer will design and develop advanced ML models for automotive radar signal processing, including end-to-end pipelines from data preprocessing through model training and optimization. The role requires expertise in deep learning architectures (CNNs, RNNs, Transformers), radar signal analysis, and deploying models for real-time embedded systems with constraints on latency, memory, and power.…See more Responsibilities include evaluating state-of-the-art ML techniques, optimizing models for production, and translating research into scalable algorithms. The position demands a Master's or PhD in a quantitative field, 3+ years of ML research experience, strong proficiency in Python and frameworks like PyTorch or TensorFlow, and foundational knowledge of radar fundamentals.

Design and develop advanced machine learning models for automotive radar signal processing, including end-to-end ML pipelines from data preprocessing through model training and optimization. Evaluate novel deep learning architectures (CNNs, RNNs, Transformers) applied to radar data in time-domain, frequency-domain, and range–Doppler representations.…See more Optimize models for real-time embedded deployment under latency, memory, and power constraints, and translate research outcomes into scalable, production-ready algorithms. Requires a Master's or PhD in a quantitative field, 3+ years of ML research experience, strong radar and signal processing fundamentals, and proficiency in Python, PyTorch/TensorFlow, and cloud platforms.

Staff/Sr. Staff Software Engineer role focused on AI inference optimization on Snapdragon platforms, including model optimization, quantization, graph transformations, and runtime execution for LLMs, LVMs, and LMMs.…See more You will design and implement graph lowering and optimization techniques within ONNX Runtime, ExecuTorch, and Qualcomm AI Stack SDK, working across ML algorithms, inference systems, and hardware integration. The role requires 6–8+ years of software development experience, 3+ years in AI/ML inference or model optimization, deep expertise in Python and C/C++, PyTorch/ONNX, and transformer architectures. You will mentor junior engineers, drive features end-to-end, and collaborate across ML Research, hardware, product, and QA teams.

As a Senior SoC Platform Software Engineer at Qualcomm, you will lead development, debugging, and customer interactions for platform software drivers and modules targeting next-generation automotive solutions. You'll comprehend software product requirements and their relationships to hardware blocks, delivering embedded software for ARM-based SoCs supporting infotainment, telematics, ADAS, and autonomous driving.…See more The role requires 6+ years of software engineering experience with proficiency in C/C++, and preferred expertise across Linux kernel, bootloaders, device drivers, SoC architecture, real-time operating systems, multimedia systems, and automotive safety standards (ASPICE, ISO26262, ISO21434).

Qualcomm AI Research seeks a Senior AI Research Quantization Engineer to develop algorithms for efficient generative AI, LLMs, and multimodal models optimized for on-device deployment. The role focuses on advanced quantization techniques, model compression, inference optimization (batching, KV caching, speculative decoding), and system prototyping using Python and PyTorch.…See more You will collaborate across hardware, software, and systems teams to enable state-of-the-art models to run on power- and memory-constrained devices including smartphones, autonomous vehicles, robotics, and IoT platforms. A Bachelor's degree plus 2+ years of related engineering experience (or Master's with 1+ year, or PhD) is required.

Develop software for the Qualcomm AI Stack SDKs (QAIRT and Genie) to enable execution of generative AI models and large language models on Snapdragon platforms. You will validate, optimize, and debug machine learning inference solutions, collaborating with cross-functional teams on feature development, performance analysis, and system reliability.…See more The role requires expertise in machine learning frameworks, embedded systems optimization, programming languages like Python or C++, and low-level OS/hardware interactions.

Build and optimize scalable LLM inference platforms at Qualcomm's Cloud AI team, implementing advanced serving techniques like KV-cache management, speculative algorithms, and model optimization. Contribute to production serving frameworks (vLLM, SGLang, Triton, TGI) and work with customers on deployment solutions.…See more Collaborate with compiler, firmware, and platform teams to drive efficient serving through autoscaling, load balancing, and routing. Requires deep understanding of transformer architectures, strong PyTorch and Python skills, computer architecture knowledge, and hands-on experience profiling and optimizing deep learning workloads.

Senior Machine Learning Engineer responsible for architecting, designing, developing, and deploying on-device AI prototype software for edge computing applications. The role requires expert-level proficiency in C++ and Python, deep knowledge of ML frameworks like PyTorch, and hands-on experience with low-level system debugging, performance tuning, and native inference driver development.…See more You will work in a multi-disciplinary research team advancing generative AI technology for the edge, including model fine-tuning, hardware acceleration, model quantization, and edge inference. A strong theoretical background in deep learning combined with embedded software development experience and modern software engineering best practices is essential.

Design, implement, and optimize video processing and computer vision algorithms for mobile and embedded platforms at scale, from concept through production deployment. Profile and optimize algorithm performance across memory, compute, power, and bandwidth constraints on SoCs with embedded accelerators.…See more Lead system and algorithm-level architecture, collaborate with cross-functional hardware and software teams, and provide technical mentorship to engineers across experience levels.

Senior Engineer, Machine Learning at Element Biosciences will design, develop, and optimize deep learning models (CNNs, Vision Transformers, U-Net) for biological image analysis and deploy them to production on AWS or imaging instruments. Responsibilities include building end-to-end ML pipelines from data ingestion through inference, applying advanced image processing and computer vision techniques to multimodal biological images, and analyzing single-cell and multiomic data.…See more The role requires 5–7 years of experience with a Master's degree (or 0–3 years with a PhD) and hands-on proficiency in PyTorch, Python, and cloud deployment, with strong preference for experience in biomedical image modalities.

Lead research projects in AI/ML across areas including decision-focused AI, probabilistic modeling, causal inference, agentic systems, neuro-symbolic AI, and LLM-based reasoning. Define technical direction, mentor junior researchers, and translate research innovations into Intuit's products.…See more Requires a PhD, 8+ years of post-PhD research experience with top-tier publications, and deep expertise in one or more focus areas. Proficiency in Python, PyTorch, or TensorFlow, and strong fundamentals in deep learning, optimization, and statistical machine learning are essential.

Principal Machine Learning Engineer at AppFolio to architect and lead mission-critical AI systems across the Realm-X property management platform. You'll design advanced AI agentic systems combining reasoning, planning, and execution; establish ML platform primitives for end-to-end production workflows; and drive the transition toward autonomous property management using LLMs, fine-tuning, and reinforcement learning.…See more Requires 10+ years building software systems with deep expertise in traditional ML, deep learning, generative AI, LLM post-training (SFT, RLHF, DPO, RL), and production ML at scale—plus a Master's or Ph.D. in Computer Science or related field.

Lead the design and implementation of computer vision features and on-device prototyping using Snapdragon Vision API. Support engineering teams in building, integrating, and deploying CV APIs for commercial products across mobile, autonomous vehicles, IoT, and AR/VR platforms.…See more Develop technical documentation and sample materials showcasing CV capabilities to end-application developers. Requires 3–5 years of hands-on CV application development, strong understanding of CV algorithms and deep-learning pipelines, and proficiency in C/C++ and Python for rapid on-device prototyping.

Join Qualcomm AI Research as a Machine Learning Engineer to architect, design, develop, and deploy on-device AI prototype software for edge devices. You will work with a multi-disciplinary team using cutting-edge AI frameworks, focusing on model fine-tuning, quantization, and edge inference.…See more Strong Python, deep learning frameworks (PyTorch), object-oriented design, and software engineering best practices are required. Preferred qualifications include generative AI knowledge, neural network optimization, NPU/ML accelerator experience, Android programming, C/C++, and embedded software skills.

As a Platform Software Engineer in Qualcomm's Automotive group, you will design, develop, and validate embedded software, drivers, and firmware for next-generation automotive solutions including infotainment, telematics, and autonomous driving systems. You will lead development and debugging of platform software modules, collaborate with hardware and systems engineers, and interact with automotive customers to deliver requirements-compliant solutions.…See more The role requires understanding of hardware-software integration across CPU, accelerators, and standard hardware blocks, with expertise in embedded software layers such as boot, drivers, firmware, security, and safety kernels. You will work with automotive industry standards, embedded systems on ARM-based SoCs, and tools such as JTAG debugging and C programming.

Design, develop, and optimize machine learning systems and models for production AI platforms, with focus on inference optimization, scalable ML infrastructure, and deployment. Responsibilities include building ML pipelines, optimizing model inference across hardware environments, integrating LLMs and models into APIs and microservices, designing data pipelines for ingestion and feature engineering, and collaborating cross-functionally on end-to-end ML solutions.…See more Requires strong software engineering fundamentals combined with deep ML expertise, proficiency in Python and at least one systems language (C++, Rust, or Go), and solid understanding of ML frameworks, transformer architectures, and model deployment systems.