model-training jobs in San Diego

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 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.

Staff Machine Learning Engineer to drive AI/ML-based automation across Qualcomm's Automotive SoC Cybersecurity and Safety engineering. The role focuses on building intelligent, scalable solutions using LLMs, GenAI, and agentic AI systems to streamline cybersecurity workflows, functional safety processes, and silicon verification.…See more Responsibilities include designing end-to-end ML pipelines, developing document-understanding and review-automation systems, and applying AI to security analysis and compliance monitoring across the product development lifecycle. Required: strong ML/AI background, Python or C++ proficiency, production ML experience; preferred: knowledge of automotive standards (ISO/SAE 21434, ISO 26262), hardware security, or RTL/verification workflows.

As an AI Performance Engineer at Qualcomm, you will create and implement machine learning techniques, frameworks, and tools for efficient discovery and deployment of ML solutions across mobile, edge, auto, and IoT products. You will model, architect, and develop advanced ML hardware co-designed with software, optimize software for AI model deployment on hardware (kernels, compilers, model efficiency tools), and develop ML techniques into products.…See more You will conduct experiments to train and evaluate ML models, work independently with minimal supervision, and provide technical guidance to team members. The role requires 4+ years of hardware/software/systems engineering experience, proficiency with ML frameworks (TensorFlow, PyTorch, Keras), embedded systems optimization, and programming languages suited for ML (Python, C++, R).

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 and improve autonomous AI trading systems deployed in financial markets, with core work on model architectures, training frameworks, and performance evaluation. You'll integrate novel data sources, optimize models for measurable accuracy gains and reduced training time, and build monitoring systems to detect anomalies in live trading strategies.…See more Requires strong ML fundamentals with hands-on experience in PyTorch, TensorFlow, or JAX, feature engineering, and model optimization; minimum 2 years of ML development experience preferred.

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.

Qualcomm seeks a Staff Machine Learning Engineer to design and deploy AI/ML-based automation solutions for automotive cybersecurity and functional safety engineering workflows. The role involves building intelligent systems for document understanding, compliance automation, and engineering productivity, leveraging LLMs, GenAI, and agentic AI frameworks.…See more You will develop scalable end-to-end automation pipelines, contribute to knowledge systems and RAG platforms, and apply ML to security analysis and process optimization across the full product development lifecycle. The ideal candidate has 5+ years of ML/AI experience, strong programming skills in Python or C++, and familiarity with automotive cybersecurity standards such as ISO/SAE 21434.

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.

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.

Senior Associate AI Engineer will develop GenAI/LLM applications and integrations using foundational models, build and test AI models and conversational agents, and configure AI solutions into enterprise applications on cloud platforms. The role requires assisting with data preparation for model training, documenting technical workflows, and staying current on emerging AI tools.…See more Requires minimum three years of professional or academic experience in AI/ML, data science, or software engineering, proficiency in Python or similar languages, and hands-on experience with a major cloud AI platform (Azure AI, AWS Bedrock, or Google Cloud Vertex AI).

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.

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.

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.

Ignite Digital seeks an AI Engineer to own the end-to-end machine learning lifecycle—from data preparation and model training through production deployment and monitoring. You will integrate AI models into frontend and backend systems, optimize performance for latency and cost, and collaborate with technical leads and customers to deliver Data and AI solutions.…See more The role requires strong Python and cloud platform expertise (AWS, Azure, or GCP), software engineering fundamentals, and the ability to communicate technical opportunities and limitations across varying levels of technical experience.

Lead the entire engineering team at a VC-backed AI trading firm, combining hands-on ML research and model development with technical leadership. Own the end-to-end development of production AI systems deployed in live financial markets, including model design, training, evaluation, and infrastructure.…See more Set technical direction across ML and software engineers, drive hiring and team development, and translate research into measurable real-world trading performance. Require 5–8 years of applied ML/AI experience with 3+ years managing full engineering teams.