Applied AI ML Lead - AI Agents & Agentic Systems
Salary not listed • Palo Alto, CA, United States • Full-time
Posted 17d ago
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Job Location
Palo Alto, CA, United States
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Agent Engineer
About the job
Join a team where your work directly shapes how machine learning is applied at scale across the firm. You’ll partner with product, engineering, and data teams to take ideas from experimentation through production, improving outcomes through thoughtful model development, evaluation, and operational excellence. As an Applied AI and Machine Learning Lead, you will drive the design and delivery of machine learning and deep learning solutions that solve meaningful business problems. You will take ownership from problem framing and experimentation through productionization, ensuring solutions are robust, scalable, and measurable. You will also help raise the technical bar through mentorship, strong engineering practices, and a culture of continuous learning.
Responsibilities
- Serve as a subject matter expert on a wide range of ML techniques and optimizations.
- Provide in-depth knowledge of ML algorithms, frameworks, and techniques.
- Enhance ML workflows through advanced proficiency in large language models (LLMs) and related techniques.
- Conduct experiments to evaluate and benchmark latest AI and agentic techniques, analyzing results, tuning models and agentic systems.
- Write Python code to bring experimental results into production solutions, owning end-to-end code development for proof of concept and production-ready solutions.
- Optimize system accuracy and performance by identifying and resolving inefficiencies and bottlenecks.
- Integrate Generative AI within the ML Platform using state-of-the-art techniques.
- Drive decisions that influence product design, application functionality, and technical operations and processes.
Requirements
- MS and/or PhD in Computer Science, Machine Learning, or a related field.
- At least 5 years of applied machine learning experience.
- At least 5 years of experience in programming languages like Python, Java, C/C++ (intermediate Python required).
- At least 5 years of experience applying data science and ML techniques to solve business problems.
- Solid background in Large Language Models (LLMs) and agentic applied science such as multi-agent orchestration, reasoning, skills, and tools.
- Experience with applied research and experimentation on machine learning and deep learning methods (including LLMs/GenAI).
- Deep understanding and expertise in deep learning frameworks such as PyTorch or TensorFlow.
- Experience in advanced applied ML areas such as GPU optimization, finetuning, embedding models, inferencing, prompt engineering, evaluation, RAG (Similarity Search), reasoning, context management, and other advanced agentic capabilities.
- Ability to work on tasks and projects to completion with limited supervision.
- Demonstrated leadership in working effectively with engineers, product managers, and other ML practitioners.