Machine Learning Engineer
Company: Tbwa Chiat/Day Inc
Location: San Francisco
Posted on: November 14, 2024
Job Description:
MindsDB is a fast-growing AI startup headquartered in San
Francisco, California. As a leading innovator bringing AI and Data
together, our passion is empowering 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.MindsDB was founded in 2017 by Adam Carrigan
and Jorge Torres, inspired by Ian M. Banks's Culture series, in
which super AI systems called Minds collaborate with other forms of
life to accomplish incredible goals. Starting as an Open-Source
project, MindsDB has grown to be one of the most widely used
AI-Data platforms in the world, with a growing community and more
than 700 contributor developers from every corner of the globe.We
are backed with over $55M in funding from Mayfield, Benchmark,
YCombinator, and nVidia. MindsDB is also recognized by Forbes as
one of America's most promising AI companies (2021) and by Gartner
as a Cool Vendor for Data and AI (2022).THE ROLEAs a Machine
Learning Engineer 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.In
this role, you'll fine-tune and deploy transformer models like
Llama and OpenAI APIs, while collaborating with cross-functional
teams to solve complex problems. Your experience in data
structures, algorithms, and software design will help you
contribute to innovative AI solutions at MindsDB, where you'll also
have the opportunity to grow your skills in MLOps and model
deployment.This is a hybrid role (2-3 days in office/week) and we
are looking for a candidate based in the Bay Area.WHAT YOU'LL BE
WORKING ON
- 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, and designing and optimizing
retrieval systems for both structured and unstructured data.
Experience with advanced RAG algorithms beyond naive approaches is
required.
- Researching and implementing advanced chunking techniques
(e.g., semantic, contextual retrieval, late chunking) along with a
thorough understanding of retrieval concepts such as embeddings,
late interactions, query expansion, bi-encoders, and
cross-encoders. Apply these techniques based on specific
application needs.
- Building agentic and tool-calling systems to extend the
capabilities of LLMs.
- Employing an "Evaluation Driven Development" approach, working
with messy datasets and creating evaluation metrics.
- Fine-tuning and deploying transformer models (e.g., Llama,
OpenAI APIs), building agent-based applications, and integrating
them into production environments.
- Be capable of building a RAG system from scratch without
relying on LLM frameworks, while being familiar with LLM frameworks
(e.g., Langchain, LlamaIndex, DSPy) or willing to learn.
- Demonstrating strong skills in data structures, algorithms,
concurrency, multi-threading, and design patterns. Write clean,
maintainable code.
- Collaborating closely with engineers and researchers,
emphasizing team collaboration, documentation, and best engineering
practices. Work with cross-functional teams, manage pull requests,
and participate in code reviews.
- Creating design documents, technical specifications, and lead
architecture discussions.REQUIREMENTS/QUALIFICATIONSYou will have:
- 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
have:
- 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 &
PERKS
- 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 leaveDIVERSITY, EQUALITY &
INCLUSIONMindsDB is an equal-opportunity employer. We celebrate
diversity and are committed to creating an inclusive environment
for all of our employees. MindsDB will give all qualified
applicants consideration for employment without regard to age,
ancestry, color, family or medical care leave, gender identity or
expression, genetic information, marital status, medical condition,
national origin, physical or mental disability, political
affiliation, protected veteran status, race, religion, sex
(including pregnancy), sexual orientation, or any other
characteristic protected by applicable laws, regulations, and
ordinances.Salary Range$200,000 - $240,000 USDApply for this
job
#J-18808-Ljbffr
Keywords: Tbwa Chiat/Day Inc, Castro Valley , Machine Learning Engineer, Engineering , San Francisco, California
Didn't find what you're looking for? Search again!
Loading more jobs...