Machine Learning / AI Engineer Lead - Databricks - Eng
Summary
Lead end-to-end AI/ML project deliveries for clients at a remote data/ML consultancy: design and productionize machine learning and generative/agentic AI systems (RAG, multi-agent) using Python, Docker, Apache Spark, and Databricks, with strong MLOps and customer-facing consulting responsibilities.
🚀 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 🤓
- Serve as a primary technical consultant, leading and executing end-to-end AI/ML project implementations
directly with clients, translating complex business problems into robust technical solutions. - Exhibit excellent communication, presentation, and stakeholder management skills to clearly
articulate technical findings, proposals, and project status to both technical and non-technical audiences. - Design, build, and maintain production-grade AI and ML pipelines, focusing on continuous integration,
continuous delivery (CI/CD), and advanced MLOps/AIOps practices to ensure reliability and scalability of
models. - Implement and optimize cutting-edge Generative and Agentic AI applications, demonstrating hands-on
experience with technologies like multi-agent orchestration, agent evaluation, and Retrieval Augmented
Generation(RAG) Systems in a production setting. - Architect end-to-end AI/ML systems, designing both traditional Machine Learning- and Generative AI-based
solutions based on customer requirements - Manage underlying solution infrastructure necessary for production deployment, demonstrating proficiency
in technologies such as Docker, pipeline orchestrators, and lakehouse database systems like Databricks. - Leverage expertise in distributed computing frameworks, specifically in scalable machine learning and high-
performance data processing (e.g., using technologies like Apache Spark). - Contribute to the strategic growth of the AI FDE Practice, including participation in technical assignments
and knowledge transfer activities. - Ensure all client engagements and training activities are properly documented and reported via designated
partner platforms.
Required Skills 💻
- 4+ years of hands-on professional experience developing, deploying, and managing Generative/Agentic AI
or Machine Learning systems, with a mandatory requirement for productionizing and maintaining models in
a live environment. - 3+ years of experience in a customer-facing consulting or solutions architect role, focused on technical
implementation and delivery. - Excellent verbal and written communication skills for effective client and internal team interaction.
- Expertise in MLOps lifecycle management, including model versioning, testing, monitoring, and automated
deployment best practices. - Demonstrable experience with infrastructure management, encompassing containerization (Docker) and
data pipeline orchestration. - Expertise in Python for data-intensive and scalable AI/ML applications.
- Demonstrated commitment to continuous learning in emerging AI/ML fields.
🎁 Perks
- Remote-first culture – work from anywhere! 🌍
- AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
- In-Company English Lessons.
- 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!
- 👶 Monthly Childcare Reimbursement – Because supporting families matters too
Skills
As published by lever · 15 questions · 8 written answers
Basics
Resume/CV, Full name, Email, Phone, Current location, Current company, LinkedIn URL, GitHub URL, Other URL
Short answers (1)
- Gross salary expectations (ARS) or net salary expectations (USD)
Pick from a list (6)
- 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
- Do you have work experience with any of these tools? optional
- English Level
- Seniority optional
- Working mode
Written answers (8)
- Describe about your relevant experience in the role optional
- Have you ever worked with Databricks, particularly in data engineering, data analytics, or building and managing data pipelines?
- What is your level of experience in developing data architecture solutions? Have you primarily used Python or any other language?
- Do you have any of these certifications (Databricks, Azure, AWS, Astronomer, GCP)? If so, are they still active? optional
- What is your level of experience in designing and implementing cloud solutions? Did your cloud solutions involve developing new components or were they based on utilizing products from AWS/GCP/Databricks/DBT? optional
- Do you have experience leading teams? optional
- Study/Degree optional
- Did you know Muttdata before applying? Below, we are sharing a link with additional information about the company : https://linktr.ee/MuttDataJobs optional