Machine Learning Engineer

$200,000 - $240,000/Yr

Tbwa Chiat/Day - San Francisco, CA

Full-time - Mid Level

Hybrid - San Francisco, CA

About the position

As a Machine Learning Engineer at MindsDB, you will focus on building advanced machine learning solutions for the MindsDB platform, including robust Text-to-SQL systems and optimizing Retrieval Augmented Generation (RAG) for both structured and unstructured data. This role requires expertise in transformer models and advanced retrieval techniques to deliver state-of-the-art LLM-driven solutions. You will collaborate with cross-functional teams to solve complex problems and contribute to innovative AI solutions while having the opportunity to grow your skills in MLOps and model deployment.

Responsibilities

• Researching, building, and evaluating novel LLM-powered enterprise applications.
• Developing robust Text-to-SQL systems for interacting with enterprise data sources.
• Building and maintaining Retrieval Augmented Generation (RAG) systems for diverse data sources.
• Designing and optimizing retrieval systems for both structured and unstructured data.
• Researching and implementing advanced chunking techniques such as semantic and contextual retrieval.
• Building agentic and tool-calling systems to extend the capabilities of LLMs.
• Employing an 'Evaluation Driven Development' approach with messy datasets and creating evaluation metrics.
• Fine-tuning and deploying transformer models like Llama and OpenAI APIs.
• Collaborating closely with engineers and researchers, emphasizing team collaboration and best engineering practices.
• Creating design documents, technical specifications, and leading architecture discussions.

Requirements

• 3+ years of ML Engineering experience.
• Proven experience in machine learning engineering, particularly with LLMs and retrieval-based systems.
• Strong software engineering skills, including experience in data structures, algorithms, and software design.
• Experience working with transformer models, fine-tuning, and deploying them in production.
• Ability to build end-to-end machine learning systems, especially in RAG and agentic contexts.
• Familiarity with LLM frameworks or a willingness to learn.
• Excellent problem-solving abilities and a passion for creating innovative AI-driven solutions.
• Strong communication and team collaboration skills.

Nice-to-haves

• Startup experience with fast-paced adaptability.
• Cloud platform experience (AWS, GCP, Azure) for ML deployments.
• MLOps knowledge, including CI/CD and model monitoring.
• Experience with big data tools (SQL, NoSQL, Spark).
• Open-source contributions in LLM or AI projects.

Benefits

• Flexible Working Hours
• Competitive Compensation
• 401k with up to 6% matching
• Unlimited PTO
• New Hire Remote Setup budget ($1500)
• Lunch Provided Mon-Fri
• Commuter Budget ($1200/year)
• Monthly (virtual) team events
• International in-person company retreats
• Wellbeing/Mental Health leave