Machine Learning Engineer
Description For Machine Learning Engineer
MindsDB is a fast-growing AI startup headquartered in San Francisco, California, backed by over $55M in funding from Mayfield, Benchmark, YCombinator, and nVidia. As a leading innovator bringing AI and Data together, MindsDB empowers companies to easily build AI capabilities that can Think, Understand and Orchestrate, enabling teams to move from prototyping & experimentation to production in a fast & scalable way.
As a Machine Learning Engineer at MindsDB, you'll 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. Your expertise in transformer models and advanced retrieval techniques will be essential in delivering state-of-the-art LLM-driven solutions.
Key responsibilities include:
- Researching, building, and evaluating novel LLM-powered enterprise applications
- Developing robust Text-to-SQL systems for interacting with enterprise data sources
- Building and maintaining RAG systems for diverse data sources
- Implementing advanced chunking techniques and optimizing retrieval systems
- Building agentic and tool-calling systems to extend LLM capabilities
- Fine-tuning and deploying transformer models
- Collaborating with cross-functional teams and participating in code reviews
Requirements:
- 3+ years of ML Engineering experience
- Strong software engineering skills and experience with LLMs and retrieval-based systems
- Ability to build end-to-end machine learning systems
- Excellent problem-solving abilities and passion for innovative AI solutions
This hybrid role (2-3 days in office/week) offers competitive compensation, comprehensive benefits, and the opportunity to work on cutting-edge AI technology in a fast-paced startup environment. Join MindsDB and be part of a team recognized by Forbes as one of America's most promising AI companies and by Gartner as a Cool Vendor for Data and AI.
Responsibilities For Machine Learning Engineer
- 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
- Building agentic and tool-calling systems to extend the capabilities of LLMs
- Employing an 'Evaluation Driven Development' approach
- Fine-tuning and deploying transformer models
- Building agent-based applications and integrating them into production environments
- Writing clean, maintainable code
- Collaborating closely with engineers and researchers
- Creating design documents, technical specifications, and leading architecture discussions
Requirements For Machine Learning Engineer
- 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
Benefits For Machine Learning Engineer
- Flexible Working Hours
- Competitive Compensation
- Competitive Medical, Dental, Vision, Life Insurance
- 401k with up to 6% matching
- Unlimited PTO
- New Hire Remote Setup budget ($1500)
- Lunch Provided Mon-Fri
- Internet Budget ($25/month)
- Commuter Budget ($1200/year)
- Learning & Development budget
- Wellbeing Budget ($1200/year)
- Monthly (virtual) team events
- International in-person company retreats
- Wellbeing/Mental Health leave
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