Job Description

Locations

• San Diego, California, United States 92128

Salary

Skills Required

• machine learning strategy designintermediate
• machine learning implementationintermediate
• supply chain optimizationintermediate
• manufacturing systems developmentintermediate
• smarter factories buildingintermediate
• collaboration with multi-functional teamsintermediate
• algorithm application to large-scale dataintermediate
• end-to-end project deliveryintermediate
• problem statement and conceptualizationintermediate
• proof-of-concept developmentintermediate
• final deployment participationintermediate
• ad-hoc statistical analysesintermediate
• business intelligence solutions generationintermediate
• data engineering collaborationintermediate
• analysis presentations to executivesintermediate

Required Qualifications

• 3+ years of experience in machine learning algorithms, statistics, and data mining models, with an emphasis on large language models (LLM) or large multimodal models (LMM). (experience, 3 years)
• Master’s degree in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Operations Research, Physics, Mechanical Engineering, Electrical Engineering, or a related field. (degree in machine learning)

Preferred Qualifications

• Proven experience in LLM and LMM development, fine-tuning, and application building. Experience with agents and agentic workflows is a major plus. (experience)
• Experience with modern LLM serving and inference frameworks, including vLLM for efficient model inference and serving. (experience)
• Hands-on experience with LangChain and LlamaIndex, enabling RAG applications and LLM orchestration. (experience)
• Strong software development skills with proficiency in Python. Experienced user of ML and data science libraries such as PyTorch, TensorFlow, Hugging Face Transformers, and scikit-learn. (experience)
• Familiarity with distributed computing, cloud infrastructure, and orchestration tools, such as Kubernetes, Apache Airflow (DAG), Docker, Conductor, Ray for LLM training and inference at scale is a plus. (experience)
• Deep understanding of transformer-based architectures (e.g., BERT, GPT, LLaMA) and their optimization for low-latency inference. (experience)
• Ability to meaningfully present results of analyses in a clear and impactful manner, breaking down complex ML/LLM concepts for non-technical audiences. (experience)
• Experience applying ML techniques in manufacturing, testing, or hardware optimization is a major plus. (experience)
• Proven experience in leading and mentoring teams is a plus. (experience)

Responsibilities

• Product Operations partners with a variety of different engineering and operations teams, our team leads development of machine learning solutions. We deliver projects from end-to-end: problem statement and conceptualization, proof-of-concept, and participation in final deployment!
• You will also perform ad-hoc statistical analyses. You will also work closely with data engineers to generate detailed business intelligence solutions. You will be expected to conduct presentations of analyses to a wide range of audiences including executives.

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