deep-learning jobs in San Diego

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.

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.

Design and implement computer vision features and on-device prototyping using the Snapdragon Vision API for mobile, autonomous vehicles, IoT, and AR/VR platforms. Lead CV feature development from algorithm through commercialization, collaborating with hardware, software, and product teams.…See more Develop technical documentation and sample materials for developer enablement. Requires 3–5 years of hands-on computer vision application development with strong C/C++ and Python proficiency and deep understanding of CV algorithms and deep-learning pipelines.

Design and optimize video analysis, quality assessment, and encoding algorithms for hardware-accelerated video codec solutions (FPGA/ASIC). Develop C-models and firmware implementing deep learning techniques (CNNs, Transformers, MLLMs) for video processing, ROI detection, and frame-level rate control.…See more Collaborate with infrastructure teams to integrate algorithms into production VOD and live-streaming pipelines, validate performance through A/B testing, and participate in objective video quality evaluation using metrics like VMAF, PSNR, and SSIM.

Lead the scientific vision and execution of a generative AI platform for protein foundation models, starting with antibody and VHH design. You will build and manage a team of AI researchers and ML infrastructure engineers, define pretraining and post-training strategies across self-supervised learning, reinforcement learning, and transfer learning, and design confidence heads with out-of-distribution detection.…See more This is a founding role requiring deep expertise in structure-based generative modeling, multi-node GPU training, and the ability to shape cutting-edge computational approaches for therapeutic molecule discovery.

As an AI/ML advisor for biotherapeutics at Eli Lilly, you will lead training and fine-tuning experiments on proprietary infrastructure (LillyPod), curate and process biological data (sequences, structures, assays), and build evaluations that connect model outputs to experimental results. You will diagnose model failures, collaborate cross-functionally with protein scientists and wet-lab teams, and communicate findings to both computational and experimental audiences.…See more The role requires a Ph.D. in a quantitative field (or M.S. with 3+ years experience) and strong hands-on expertise in Python, PyTorch, and deep learning on GPUs, with preference for experience in geometric deep learning, protein language models, diffusion/flow-matching, and published ML applications to molecular data.

Senior AI/ML Engineer responsible for shipping end-to-end production ML systems that enable autonomous medical coding in a SaaS platform. Will design robust ML architectures with low-latency inference, build reliable data and model pipelines using modern MLOps practices (CI/CD, model registries, experiment tracking), establish evaluation strategies with statistical rigor, and implement model observability and governance including drift detection and bias assessments.…See more Requires 5+ years of industry experience building and operating ML systems in production, 3+ years with C# or Python, 3+ years on Azure, and 1+ years of LLMOps expertise including prompt engineering and RAG.

As an ML engineer at Booz Allen Hamilton, you'll design, build, and deploy production-grade AI/ML systems for Defense and Intelligence clients. You'll work across the full ML lifecycle—from model development in deep learning, computer vision, NLP, and signal processing through MLOps, containerization, and cloud deployment.…See more The role requires 2+ years of ML engineering or data science experience, proficiency with frameworks like TensorFlow and PyTorch, and the ability to obtain a Secret clearance.

Design, develop, and optimize machine learning systems for production AI platforms, focusing on model development, inference optimization, and scalable ML infrastructure. Responsibilities include building ML pipelines and frameworks, optimizing model inference for latency and cost, integrating LLMs into APIs and microservices, and designing data pipelines for preprocessing and feature engineering.…See more The role requires strong software engineering fundamentals combined with deep ML expertise, working across PyTorch/TensorFlow, model-serving systems, distributed computing, and GPU environments.

Design, develop, and optimize production machine learning systems including model development, inference optimization, and scalable ML infrastructure. Build end-to-end ML pipelines from training through deployment, optimize model inference for latency and cost, integrate LLM/ML models into APIs and microservices, and engineer data pipelines for preprocessing and validation.…See more Requires strong software engineering fundamentals with deep ML expertise, proficiency in Python and systems languages, and experience with ML frameworks, model serving, and distributed computing.

Build and ship production ML systems end-to-end for autonomous medical coding in a SaaS platform, from problem framing through deployment and monitoring. Own the full lifecycle—data discovery, feature engineering, training, evaluation, and iteration—working with LLMs, deep learning, and modern MLOps tooling to handle millions of medical charts daily.…See more Design robust, low-latency architectures, establish rigorous evaluation strategies, and implement model observability, drift detection, and bias assessments. Collaborate across product, data, and platform teams to translate business goals into measurable ML outcomes.

Senior Staff Engineer to develop end-to-end embedded AI software for deploying generative AI models on Qualcomm's edge AI accelerators. You will design and optimize ML/AI software stacks, kernels, and runtime software for power and memory efficiency, collaborate with hardware teams on new ML operators, and build debugging/profiling tools and SDKs.…See more Requires 6+ years of hardware, software, or systems engineering experience (or equivalent with advanced degree) and strong expertise in machine learning frameworks, neural network training/quantization, and languages like Python or C++.

Lead a machine learning engineering team designing Visual Language Action Models, Vision Language Models, and Large Language Models for autonomous driving and infotainment on Qualcomm's Snapdragon Ride platform. Optimize deep networks for accuracy-latency trade-offs on resource-constrained edge devices, focusing on low-level perception, end-to-end autonomous driving (L2/L3 ADAS), and multi-modal sensor fusion.…See more Drive cross-functional collaboration with automotive OEMs and internal Qualcomm teams while building a world-class AI/deep learning engineering organization. Requires 6–8+ years of systems engineering or machine learning experience (depending on degree level), with hands-on expertise in deep learning network design, quantization, and deployment on edge AI accelerators.

Design, train, and optimize machine learning models for 5G, wireless, and multimedia telecommunications products. Explore novel deep learning and signal processing techniques, conduct large-scale experiments, and translate research into production-ready solutions.…See more Requires strong background in machine learning, deep learning, and signal processing, with experience developing models for edge devices and chipsets.

Design and develop advanced machine learning models for automotive radar signal processing, including end-to-end ML pipelines from data preprocessing through model training, validation, and performance optimization. Evaluate novel deep learning architectures (CNNs, RNNs, Transformers) for radar data analysis and optimize models for real-time embedded deployment under latency, memory, and power constraints.…See more Bridge research and production by translating state-of-the-art ML techniques into scalable algorithms for radar-based detection, classification, and tracking, with strong requirements in signal processing, statistical analysis, and Python/PyTorch/TensorFlow proficiency.

Qualcomm seeks a Computer Vision Engineer to develop machine learning algorithms for optical flow, depth estimation, visual tracking, SLAM, and 3D reconstruction on Snapdragon platforms. You will own end-to-end algorithm development—from training state-of-the-art neural networks and managing large datasets to optimizing and deploying models on-device for real-time performance.…See more The role requires deep expertise in ML model architecture, hardware/software optimization, and the ability to analyze performance bottlenecks across Qualcomm's hardware/software stack. You will serve as a technical leader, influencing system architecture, working with hardware teams on silicon design, and driving solutions from research through production.

Design and develop machine learning models for computer vision domains including optical flow, depth estimation, visual tracking, SLAM, and 3D reconstruction on Qualcomm Snapdragon platforms. Own end-to-end algorithm implementation from research through production deployment, including training pipeline development, dataset creation, model optimization, and on-device performance tuning.…See more Lead technical direction across projects, influence system-level architecture, and partner with hardware engineers on silicon design. Requires 6+ years of software/hardware/systems engineering experience (or equivalent with Master's/PhD) and demonstrated expertise in on-device ML deployment, neural network optimization, and computer vision algorithm development.

Senior Machine Learning Engineer to design and ship production voice and conversational AI agents within AppFolio's Realm-X platform. You will architect real-time, multi-turn agent pipelines that balance reasoning depth against latency, lead a small pod of ML and platform engineers, and define quality metrics and evaluation harnesses.…See more Required expertise includes shipped production experience with agent frameworks (LangChain, LangGraph), voice stacks (STT/TTS/Voice-to-Voice models), LLM reasoning and tool use, Twilio, AWS, expert Python with async and WebSocket streaming, and demonstrated team leadership.

Develop, optimize, and validate AI/ML solutions that leverage Qualcomm's AI inference accelerators for data center and hybrid applications. Design and implement GenAI and LLM applications, perform model benchmarking, optimize deployment strategies, and drive system-level architecture decisions.…See more Apply deep expertise in ML frameworks, system performance profiling, and parallel computing to ensure best-in-class inference performance, power efficiency, and scalability across heterogeneous hardware.

Senior Staff engineer responsible for automotive software testing, focusing on functional safety and AI infrastructure for Snapdragon Digital Chassis platforms (telematics, digital cockpit, ADAS, autonomy). Will design and execute manual and automated test plans across embedded systems, multimedia, computer vision, and AI/neural network components using HIL/SIL methodologies.…See more Requires 6+ years of systems test engineering with deep expertise in test automation (C/C++, Python), Linux/QNX/Android kernels, and preferably automotive domain experience with AUTOSAR fundamentals.

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).

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, 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.

Senior staff engineer responsible for designing, developing, and debugging platform software drivers and modules for next-generation automotive SoCs. Will lead development efforts across multiple domains including Linux/QNX kernels, bootloaders, device drivers, multimedia systems, and low-power management frameworks.…See more Requires 6+ years of software engineering experience with deep hands-on expertise in embedded systems, ARM architecture, C/C++ programming, and SoC hardware debugging. Will collaborate with hardware, systems, and test teams to deliver automotive infotainment, telematics, and autonomous driving solutions.