fine-tuning jobs in San Diego

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.

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.

Zensar is seeking an experienced AI Architect to design, develop, and deploy enterprise-scale AI and Generative AI solutions. The role requires deep expertise in Large Language Models (Claude, Gemini, OpenAI), multi-cloud platforms (Azure, AWS), and enterprise architecture, with 10+ years in software/cloud architecture and 5+ years designing AI/ML solutions.…See more Responsibilities include defining AI strategy and architecture standards, designing end-to-end GenAI systems (RAG, agentic AI, multi-agent systems), architecting secure infrastructure across Azure and AWS, establishing governance and responsible AI frameworks, and leading adoption programs. The ideal candidate will mentor teams, evaluate emerging technologies, and translate business requirements into scalable, production-grade AI systems.

Conduct cutting-edge research in efficient generative AI, including LLMs, multi-modal foundation models, LLM reasoning, reinforcement learning, and agentic AI. Lead high-impact research initiatives and develop production-ready solutions with real-world commercial impact, with a focus on on-device deployment challenges.…See more Implement and evaluate solutions in both simulation and on-device environments, and publish findings in top-tier AI/ML conferences. Requires a Master's degree and 2+ years of experience (or PhD), with proven research excellence, deep expertise in generative AI and reinforcement learning, and hands-on experience with model development pipelines including training, fine-tuning, evaluation, and optimization.

Lead a specialized team of software engineers developing innovative Pixel sensor experiences at the intersection of hardware, software, and AI. You will drive the design and implementation of real-time embedded systems that process sensor signals efficiently while applying machine-learning and signal-processing algorithms in a power-optimized manner.…See more Required: 8 years software development experience, 5 years in computer vision or signal processing, 5 years leading ML design and infrastructure optimization, and 3 years technical leadership. This role demands deep expertise in embedded software, AI/ML algorithms, sensor fusion, and the ability to independently architect systems while managing a team.

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.…See more 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.

Design, build, and ship LLM-powered capabilities end to end—from prototyping and fine-tuning models to deploying production agents and retrieval systems. Own the full stack: prompt and context engineering, multi-step agent design with tool calling, RAG systems (embeddings, chunking, hybrid search, reranking), fine-tuning on multi-GPU with LoRA/QLoRA, evaluation and tracing infrastructure, and clean APIs for other engineers.…See more Work in a secure, distributed environment where the platform runs on customer compute, cloud, or hybrid setups, requiring expertise with both commercial and self-hosted models.

As Principal Software Engineer for AI & Data Platform, you will architect the data foundation for scientific and engineering R&D platforms, designing scalable data processing patterns, ML training pipelines, and intelligent workflow interfaces. You will own end-to-end responsibilities including data modeling for multi-use analytics and ML, building production training and fine-tuning pipelines, model evaluation and benchmarking, and setting engineering standards for the team.…See more The role requires 10+ years shipping production software, expert-level Python, deep experience with large-scale data systems (object storage, analytical processing, training formats), hands-on ML pipeline development, and the ability to set technical direction in early-stage environments while implementing it yourself.