pytorch jobs in San Diego

Join XiFin's Advanced Data Analytics team as an Associate Machine Learning Engineer to design, develop, and deploy machine learning models with a focus on LLMs, Generative AI, and Agentic AI in healthcare and revenue cycle domains. You will contribute to MLOps pipelines, perform data preparation and prompt engineering, collaborate with cross-functional teams, and validate models for production use.…See more The role requires a Bachelor's degree in Computer Science, Data Science, or related field, with proficiency in Python, ML libraries (scikit-learn, TensorFlow, PyTorch), and foundational knowledge of GenAI architectures, vector databases, and LLM orchestration frameworks.

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, develop, and optimize algorithms for image and video compression across multiple formats (2D, multiview, 360-degree, point cloud, light field). Develop novel algorithms for file formats, system architectures, and transport protocols, and contribute to multimedia standardization forums (MPEG, DASH, 3GPP, JVET, AVS).…See more Research image/video processing techniques and quality evaluation metrics, with responsibilities including drafting standard contributions, patent applications, and academic papers. Requires a PhD in computer science or related field, strong fundamentals in algorithms and data structures, published conference/journal papers, and experience with multimedia standards and C/C++.

Design and optimize modem software for embedded systems, focusing on performance analysis, architectural trade-offs, and real-world workload optimization. Conduct pre-silicon evaluations, profile silicon behavior, and develop debugging and validation tools.…See more Apply data-driven analysis and machine-learning techniques to identify bottlenecks across multiple chipset generations and implement solutions through software optimization, cache tuning, and memory management.

Senior Embedded Software Engineer at Qualcomm's Data Center Business Unit, developing software and firmware for cloud edge and data center ML acceleration on high-performance silicon. The role requires deep embedded systems expertise including BSP, device driver development, RTOS, secure boot, TrustZone, and low-level peripheral interfaces (I2C/SPI/UART), combined with knowledge of ML frameworks and data movement optimization.…See more You will work on critical technologies like ML acceleration, in-memory processing, memory management, and virtualization across cross-functional international teams. Requires 2+ years of low-level C programming, proficiency with GNU/LLVM tools, embedded Linux, JTAG/SWD debugging, and multi-threaded SoC architecture understanding.

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.

Senior Embedded Software Engineer role focused on designing and developing software/firmware for cloud edge and data center ML accelerators on Qualcomm silicon. The engineer will work on ML acceleration, memory management, virtualization, and board support packages (BSP), device drivers, RTOS, secure boot, and peripheral interfaces (PCIe, I2C/SPI/UART, DMA).…See more Requires 2+ years of low-level C programming on embedded platforms with proficiency in BSP development, device driver work, Embedded Linux, RTOS, and debugging tools (JTAG/SWD). Preferred experience includes ML frameworks (PyTorch, JAX), QuRT RTOS, and Qualcomm-specific middleware.

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.

Design, develop, and optimize algorithms for image and video compression (2D, multiview, 360-degree, point cloud, light field) across multiple formats and codecs. Research novel approaches to file formats, transport protocols, and quality evaluation metrics.…See more Participate in standardization bodies (MPEG, JVET, AVS, 3GPP) and publish findings in top-tier venues. Requires a PhD in computer science or related discipline, strong fundamentals in algorithms and data structures, published research record, and hands-on experience with video coding standards.

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.

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++.

Senior technical leader responsible for integrating AI/ML systems into secure, scalable DoD-compliant environments. Will architect AI system deployments, establish DevSecOps practices, ensure compliance with RMF/NIST 800-53/DISA STIG standards, and provide technical guidance across engineering teams.…See more Requires deep expertise in AI/ML production systems, containerization, CI/CD, and cybersecurity controls, with hands-on experience in Python, Kubernetes, and modern infrastructure tooling.

Research Scientist Graduate role focused on image/video coding and processing standards. The position requires a PhD and expects familiarity with Python and PyTorch for multimedia research and development.…See more This is an entry-level research position within ByteDance's Global Frontier Tech Recruitment Program, targeting recent PhD graduates in related fields.

Staff Engineer responsible for designing and building scalable test automation frameworks and CI/CD infrastructure for machine-learning systems at scale. The role requires expertise validating ML quality across the full lifecycle (data, training, evaluation, packaging, deployment, monitoring), GPU-accelerated workloads in Kubernetes, and integrated hardware-software systems.…See more You will develop automated evaluation suites, performance baselines, release thresholds, and observability solutions while mentoring teams on ML testing best practices and dependency/reproducibility standards.

Staff Engineer responsible for designing and implementing scalable test automation frameworks and infrastructure for machine learning systems across multiple engineering teams. The role requires expertise in validating ML pipelines across data, training, evaluation, deployment, and monitoring; testing GPU-accelerated workloads in Kubernetes; qualifying integrated hardware and software systems; and developing comprehensive integration and regression strategies.…See more Deep experience with Python automation, distributed systems testing, performance profiling, and observability is essential, along with strong system-design skills for complex, multi-tenant environments.

Lead product strategy and roadmap for AI-centric data center platforms and rack-level systems, including compute nodes, interconnect fabrics, power delivery, and cooling. Define system-level requirements by collaborating with silicon architects, systems engineers, and software teams while engaging directly with hyperscale and enterprise customers to gather feedback and drive early deployments.…See more Track product performance post-launch across system metrics like power efficiency and thermal headroom, and mentor a high-performing product management team.

As a Staff Machine Learning Engineer focused on model optimization, you will create and implement ML techniques, frameworks, and tools enabling efficient discovery and deployment of state-of-the-art ML solutions across mobile, edge, auto, and IoT products. You will model, architect, and develop advanced ML hardware co-designed with software, develop optimized inference/training software and compiler tools, and collaborate with cross-functional teams on joint hardware-software design.…See more The role requires 4+ years of hardware/software/systems engineering experience (or equivalent with advanced degree), deep expertise in ML frameworks (TensorFlow, PyTorch, Keras, Caffe), embedded systems optimization, and programming languages like Python or C++. You will work independently with minimal supervision, provide technical guidance to team members, and influence key organizational decisions through consultation with senior leadership.

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.

Design and develop performance modeling platforms and tools for Qualcomm's AI/ML hardware accelerators targeting cloud data server applications. Analyze and optimize LLM and AI workloads on SoC architectures, working across hardware architecture, DDR memory controllers, NoC design, and compiler frameworks.…See more Collaborate with multi-disciplinary hardware and systems engineers to find optimal architecture tradeoffs and improve performance and power efficiency. Apply deep expertise in AI workloads, ML frameworks, computer architecture, and RTL design/verification to build systems that validate LLMs and complex ML networks.

Design and develop the end-to-end compilation pipeline for Qualcomm AI Hub Workbench, enabling PyTorch and ONNX models to compile into deployable artifacts targeting LiteRT, ONNXRuntime, and QAIRT across Snapdragon SoCs. Own graph optimization, backend dispatch across CPU/GPU/NPU, model catalog validation, and automated CI/CD pipelines for on-device ML deployment.…See more Requires 4+ years of software/hardware/systems engineering experience and proficiency in Python and C++, with preferred expertise in ML compiler infrastructure, MLIR/ONNX/TVM, torch.export, and on-device frameworks.

Principal Software Engineer role on Qualcomm's Cloud AI team focused on LLM serving and inference acceleration. The engineer will design, optimize, and deploy high-performance software across the product lifecycle, from R&D through commercial deployment, with expertise in serving frameworks (vLLM), PyTorch, neural network optimization, and multi-core/SoC architecture performance modeling.…See more Strong C++/Python development skills, deep LLM/multi-modal model understanding, and experience with machine learning accelerators are required; experience with compiler technology, performance analysis, and commercial software delivery at scale is essential.