Senior AI ML Engineer - Databricks - #2
Summary
Build agentic AI systems using frontier LLMs, document AI pipelines, and RAG for legal/contract analysis, while collaborating with stakeholders to deliver production-grade solutions.
🚀 Join Our Remote Data Products & Machine Learning Startup! 🚀
At Muttdata, we build innovative Data Products and Machine Learning solutions that help companies solve complex business challenges. As a fast-growing, remote-first startup, we're passionate about technology, collaboration, and continuous learning.
This opportunity is with a leading multinational beverage company based in Mexico City.
We are looking for an innovative Senior AI ML Engineer to join our team 🐶🚀. You'll build an AI agent for the Model Factory Lab (MFL) community that turns a natural-language prompt into a fully instantiated model — orchestrating reusable catalog components under the “model as a YAML” paradigm.
This role works closely with the MFL platform team, combining agent development with a deep understanding of model packaging and reusable, governed components. Strong technical creativity and a product mindset are essential to succeed in this fast-paced, collaborative environment.
🚀 What We Do
- Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
- Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
- Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
- Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
- Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
- Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.
🌟 Our Partnerships
- Amazon Web Services
- Astronomer
- Databricks
🌟 Our Values
- 📊 We are Data Nerds
- 🤗 We are Open Team Players
- 🚀 We Take Ownership
- 🌟 We Have a Positive Mindset
Responsibilities 🤓
- Design and build the agent that translates natural language into a composition of trainable components (train/predict/evaluate), following the MFL development framework (PyFunc / custom flavor as standard).
- Implement the model's declarative configuration in YAML (config.yaml, features.yaml, databricks.yml), respecting the MFL's minimum library skeleton.
- Integrate the agent with Feature Store, MLflow, and model orchestration to assemble governed, reusable components.
- Apply production-grade agentic patterns on Databricks (Mosaic AI Agent Framework, Agent Bricks, MCP Servers, evaluation with MLflow 3.0).
Required Skills 💻
- Experience developing AI agents, ideally on Databricks (Mosaic AI, LangGraph / OpenAI SDK, Genie, Vector Search).
- Strong command of MLflow (tracking, registry, pyfunc / custom flavor), Unity Catalog, and advanced Python.
- Understanding of component-orchestration architectures and model packaging.
- Experience with MCP, RAG, agent evaluation, and model governance standards.
- Broader experience developing AI agents / agentic infrastructure (Mosaic AI Agent Framework, agent orchestration, MCP).
🎁 Perks
- Remote-first culture – work from anywhere! 🌍
- AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
- Birthday off + an extra vacation week (Mutt Week! 🏖️)
- Referral bonuses – help us grow the team & get rewarded!
- Maslow: Monthly credits to spend in our benefits marketplace.
- ✈️🏝️ Annual Mutters' Trip – an unforgettable getaway with the team!
Skills
As published by lever · 10 questions · 7 written answers
Basics
Resume/CV, Full name, Email, Phone, Current location, Current company, LinkedIn URL, GitHub URL, Other URL
Pick from a list (3)
- Do you currently reside in Latin America? (This is a mandatory requirement for this role. If you do not currently reside in Latin America, your application will not be considered.)
- Where did you hear about us? optional
- English Level
Written answers (7)
- Describe about your relevant experience in the role
- Do you have professional experience shipping and operating AI systems in production (not just prototypes or notebooks)?
- Do you have hands-on experience with cutting-edge LLM APIs (OpenAI, Anthropic, Google, etc.) and with any agent SDKs in production?
- Do you have experience designing or building agent systems (agent loops, tool use, agent skills, MCP servers)?
- How many years of experience do you have working with LLMs / generative AI in production projects?
- Study/Degree optional
- Gross salary expectations (or USD net)
