Machine Learning Engineer

This is a fully remote position, open to applicants in Poland.

📋 Description

• Design, construct, and maintain comprehensive machine learning pipelines that encompass data ingestion, feature engineering, model training, evaluation, and deployment.

• Train and enhance gradient boosting models (LightGBM, XGBoost) as well as deep learning architectures like Temporal Fusion Transformers (TFT) for large-scale time-series forecasting.

• Deploy and oversee ML workloads on AWS (S3, EC2, Lambda), including containerized training jobs, scheduled retraining, and management of model artifacts.

• Prepare models for production use with appropriate versioning, monitoring, and automated testing procedures.

• Develop clean, well-tested, modular Python code that adheres to software engineering best practices (OOP, design patterns, typing, linting, CI/CD).

• Collaborate closely with Data Scientists and business stakeholders to convert analytical prototypes into production-ready solutions and effectively communicate technical decisions.

⛳️ Requirements

• A degree in Computer Science, Data Science, Engineering, Applied Mathematics, or a related discipline.

• At least 2 years of professional experience as a Machine Learning Engineer, Data Engineer, or a similar role with a strong focus on machine learning.

• Strong proficiency in Python, emphasizing best practices (OOP, type hints, testing, clean architecture, packaging).

• Practical experience in training and deploying gradient boosting models (LightGBM, XGBoost).

• Familiarity with AWS (S3, EC2, Lambda) and the capability to set up and manage cloud-based machine learning workloads.

• Expertise in Docker for containerizing machine learning services and pipelines.

• Strong SQL skills for data extraction and transformation tasks.

• Comfortable operating within a Linux terminal environment.

• Proficient in English, sufficient for reading documentation, conducting code reviews, and presenting technical decisions to the team.

🏝️ Benefits

• Option for an employment contract or B2B arrangement.

• Fully remote work with quarterly onsite meetups (2-3 days).

• Opportunity to work with large-scale datasets and make a significant impact on the decisions of major corporations.

• A structured development process that spans from research to production deployment.

• Access to cloud computing infrastructure (AWS) and a modern technology stack.

• Chance to influence the ML engineering culture and tooling within the team.

• Mentorship support available.

• Multisport card benefits.

• Private medical care provided.