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.… 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.
transformers jobs in San Diego
Build applied AI systems for Crucible, Firestorm's manufacturing operations software. You'll productionize ML and optimization models, integrate foundation models and LLMs into workflows, and design end-to-end AI capabilities—from model selection and evaluation through reliable production deployment across cloud, air-gapped, and edge environments.… This is a hands-on engineering role requiring 5+ years shipping production ML/AI systems, strong Python and software engineering fundamentals, and deep experience with LLMs, transformer models, and production ML monitoring.
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.… 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.
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.… 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.
Qualcomm seeks an ML/computer vision engineer to develop and optimize AI-accelerated vision algorithms for edge devices (mobile, automotive, robotics, AR/VR). You will design algorithms for depth estimation, optical flow, video super-resolution, 3D reconstruction, and SLAM, then optimize deep learning models for resource-constrained SoCs.… The role spans algorithm research, model architecture design, performance profiling across memory/compute/power/bandwidth, and cross-functional collaboration with hardware and systems teams to ship production models for key customer segments.
Applied AI Engineer
ExpiredThe Applied AI Engineer develops, deploys, and maintains generative AI solutions for insurance products and customer experiences. Responsibilities include implementing end-to-end AI/ML pipelines using AWS services (SageMaker, Lambda, ECS/EKS), feature engineering with Snowflake, model fine-tuning and testing, and monitoring production performance.… The role requires 3+ years of AI/ML experience with 1–2 years in generative AI or LLMs, hands-on cloud deployment experience, and proficiency in Python, PyTorch, TensorFlow, or Hugging Face Transformers.
Lead AI software strategy and architecture for Qualcomm's automotive platform, directing deployment of computer vision, perception systems, LLMs, and generative AI workloads. Drive architectural decisions across multiple products and customer programs while mentoring cross-functional teams.… Ensure solutions meet automotive safety, performance, and reliability standards. Requires 8+ years of software/systems engineering experience with deep expertise in AI/ML, C/C++, and automotive software environments.
Principal Software Engineer leading AI software strategy and architecture for Qualcomm's automotive platform. Responsibilities include architecting and deploying advanced AI workloads (computer vision, LLMs, multimodal models, generative AI) on automotive systems, driving cross-functional technical decisions across AI, automotive engineering, and platform teams, mentoring engineers organization-wide, and ensuring solutions meet automotive safety, performance, and reliability requirements.… Requires 8+ years of software/systems engineering experience (or equivalent with advanced degree); preferred qualifications include 15+ years in AI/ML, embedded systems, or automotive software, expert C/C++ proficiency, and demonstrated experience with automotive safety standards (ISO 26262, ASPICE), edge AI inference, and Qualcomm AI frameworks.
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.… 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.… 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.
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.… 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.
As a Senior Software Engineer focused on AI Tools, you will reauthor and optimize generative AI models (LLMs like Llama, Phi, Qwen, and multimodal models) for efficient execution on Qualcomm's on-device hardware. You'll translate hardware constraints into model-level transformations that preserve accuracy while enabling edge deployment, integrate inference acceleration techniques, and collaborate with compiler and quantization teams to move research prototypes into production.… The role requires deep implementation-level knowledge of generative AI architectures, strong Python proficiency in large typed codebases, and hands-on experience optimizing inference for resource-constrained environments.
As a Datacenter AI Systems and Solutions Engineer at Qualcomm, you will research, develop, and optimize end-to-end AI/ML solutions that integrate Qualcomm's AI inference accelerators with system software and ecosystem components. You will lead the design and deployment of production-ready Generative AI and LLM applications, perform model benchmarking and performance analysis, and serve as a technical lead for customer engagements on AI model optimization and inference tuning.… The role requires deep expertise in AI systems architecture, MLOps practices, and large-scale distributed systems, with hands-on proficiency in Python, ML frameworks, containerization, and orchestration platforms. You will drive system-level requirements, hardware/software co-design, and influence product direction through performance analysis and optimization strategies.
As a Senior Systems Engineer for Data Center AI at Qualcomm, you will research, develop, optimize, and validate AI/ML solutions that integrate Qualcomm's hardware accelerators with software and ecosystem to deliver high-performance inference in datacenter environments. You will design and deploy Gen AI and LLM applications, implement fine-tuning and distillation techniques, perform model benchmarking, and drive system-level architecture decisions.… You will collaborate across functional teams to meet system-level requirements while staying current with advances in AI/ML models and hardware. Required skills include strong Python proficiency, expertise in ML frameworks (PyTorch, TensorFlow), deep understanding of ML deployment and system performance profiling, and experience with parallel computing.
The Applied AI Engineer develops, deploys, and maintains generative AI solutions for insurance products and internal workflows. The role involves implementing end-to-end AI pipelines using AWS services (SageMaker, Lambda, ECS/EKS, S3), building feature engineering workflows in Snowflake, and collaborating with cloud and MLOps teams.… Candidates need 3+ years of AI/ML engineering experience with 1–2 years focused on generative AI or LLMs, proficiency in Python and frameworks like PyTorch or Hugging Face Transformers, and hands-on cloud deployment experience. The position requires monitoring model performance, ensuring security and compliance, and supporting AI architecture reviews.