Machine Learning Engineer

TL;DR

Machine Learning Engineer (Python/ML): Develop and optimize scalable ML models for demand planning, budget forecasting, recommendation systems, and generative AI with an accent on MLOps, feature engineering, and model lifecycle management. Focus on designing data pipelines, implementing emerging AI techniques, and integrating deep learning models with cloud platforms.

Location: Remote (work from anywhere)

Company

Dynamic startup crafting innovative Big Data and Machine Learning systems for e-commerce platforms, retailers, and various industries.

What you will do

• Develop and optimize ML models ensuring scalability, monitoring, and integration with MLOps best practices.
• Implement client requirements from exploratory data analysis to feature engineering and model lifecycle management.
• Build ML Proof of Concepts to validate and refine solutions.
• Optimize models for performance, latency, memory, and throughput using statistical analysis and regression models.
• Design and maintain feature stores and data pipelines for ML workflows.
• Research emerging ML/AI techniques and collaborate with stakeholders to align solutions with business needs.

Requirements

• Experience implementing ML-based systems including model lifecycle management, monitoring, and MLOps pipeline setup.
• Strong proficiency in Python (Pandas, Numpy, Jupyter, Scikit-Learn, XGBoost, Plotly) and knowledge of SQL.
• Experience with cloud platforms (AWS, GCP, Azure).

Nice to have

• Experience with ML workflows (Airflow, MLflow, H2OAI, Databricks).
• Background in modern LLM technologies.
• Understanding of Deep Learning frameworks (Keras, PyTorch, TensorFlow).
• Basic knowledge of Docker.

Culture & Benefits

• Remote-first culture – work from anywhere.
• In-company English lessons.
• Wellhub or sports club stipend.
• AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered.
• Food credits via Pedidos Ya.
• Birthday off + extra vacation week (Mutt Week).
• Referral bonuses and annual team trip.