Data Engineer ML

We have 30 years of expertise in designing and building custom software systems. We provide software development services focusing on complex high-load applications, AI and BI solutions, and mobile apps.

Project description

You will work on a DNA-Encoded Libraries (DEL) project for a big pharma company. The core team includes 4 developers and 3 scientists.

A key part of the project is a Postgres database that stores experimental data for machine learning (ML). You won’t be building ML models from scratch, but you’ll use your strong technical skills and understanding of ML to help scientists solve technical challenges. You will mainly be a data consumer, not a database developer.

Currently, the focus is on automating ML training rather than deploying models to end users, although deployment might happen later.

A background in cheminformatics is a big plus.

Responsibilities

• Prepare large scientific datasets for ML by querying the Postgres database and automating data extraction.
• Create training, testing, and validation datasets, managing very large data volumes (terabytes).
• Collaborate with scientists to automate and optimize their initial ML packages for efficient, automated environments using tools like MLflow, Neptune AI, Amazon Sagemaker, or Kubernetes GPU clusters.
• Help test different ML models by automating experiments with hyperparameters, data splits, etc.
• Set up and manage ML environments.

Required Skills

• Strong Python programming.
• Good understanding of ML concepts and terminology.
• Experience with DevOps and MLOps tools like MLflow or Amazon Sagemaker.
• Familiarity with Docker, Kubernetes, Terraform, Jenkins.
• Experience with Postgres and SQL.

Nice to Have

• Experience with ML libraries such as PyTorch, Scikit-learn, or TensorFlow.
• Familiarity with AWS cloud services (learning supported).
• Strong background in cheminformatics.

Our offer as your future employer

• Collaboration via a B2B contract with payments in EUR or USD, depending on your preference, or through a labor contract if you are based in Georgia, Serbia, or Kazakhstan.
• Flexible work schedule.
• Possibility to work remotely (excluding Russia and Belarus).
• Opportunities for professional growth.
• A company laptop to ensure a comfortable and efficient work setup.