Senior Machine Learning Engineer

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

• Orchestrate production pipelines on Databricks Jobs, chaining tasks via depends_on and managing failure modes (ALL_SUCCESS / ALL_DONE).
• Configure and maintain deployments via Databricks Asset Bundles (DABs), promoting across dev → qa → prd targets, with resource/deployment files per country.
• Manage the lifecycle of models and artifacts in MLflow + Unity Catalog (registration, versioning, Champion/Challenger aliases, rollback).
• Ensure operational continuity: manage compute across workspaces, standardize cost-monitoring tags (FinOps), and integrate with AIOps/observability.
• Master the product end-to-end to diagnose runtime incidents and coordinate with development squads.

Required Skills

• Proven experience orchestrating data/ML pipelines on Databricks (Jobs, Workflows, cluster policies).
• Solid CI/CD experience (Azure DevOps, gitflow, PRs), IaC with DABs, and code quality standards (black, isort, mypy).
• Advanced Python, SQL, Delta / Unity Catalog.

Nice to Have

• Experience working with Large Language Models (LLMs).
• Knowledge of AI agents and agentic systems.
• Familiarity with MLOps practices and tools.
• Experience deploying and maintaining Data Science and AI solutions in production environments.
• Knowledge of job orchestration, computing infrastructure, deployments, monitoring, and maintenance.
• Experience working with event data, user tracking, and application tagging.
• Ability to collaborate effectively with Product, Engineering, and Business teams.

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!