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As an ML Engineer at Greenscreens.ai, you will play a crucial role in advancing logistics technology by developing and optimizing ML models that address new business challenges. You will be responsible for ensuring the efficiency and accuracy of our deployed models, scaling their performance, and automating ML pipelines. Your work will involve building and managing the infrastructure for training models, conducting research, and applying findings directly to improve client solutions. Additionally, you will enhance our predictive models, explore new features to refine predictions, and integrate complex business logic into our processes. Your contributions will shape the future of our ML-based solutions and drive innovation in the logistics industry.

Responsibilities

  • Research and identify new business features to enhance prediction accuracy
  • Enhance Rate Engine through algorithm manipulation, feature experimentation, and research to optimize data filtering and predictive model quality.
  • Monitor and maintain deployed ML models, ensuring accuracy and efficiency
  • Automate ML pipelines and manage the entire model lifecycle.
  • Develop complex business logic in Python to integrate models into a company's processes.
  • Scale and optimize the performance of existing models (RPS, memory consumption)
  • The primary focus of your work will be on tabular data

Requirements

  • 3+ years of experience as a Data Scientist, ML Engineer, or in a similar role.
  • Python, SQL,Git
  • Neural networks, time series, gradient boosting, and random forest.
  • Linear algebra, probability, statistics, optimization
  • Upper-intermediate English and Russian proficiency for effective communication in the teams.
  • Advanced proficiency in both Russian and English is required—no exceptions.

Desirable Technical skills

  • Unit testing
  • AWS S3, Docker, Kubernetes
  • Experience in logistics
  • Active engagement with industry articles and research papers
  • Participation in competitions (e.g., Kaggle)
  • Hyperparameter tuning methods
  • Anomaly detection

Qualifications

  • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.

Benefits

Remote Work: Ability to work from anywhere in the world or in our office in Vilnius. However, please note that there are restrictions on working from Russia and Belarus.

Options Program: Participate in our options program, allowing you to share in the growth and success of our startup.

Annual private health insurance allowance

PTO: Up to four weeks of fully paid leave per calendar year

Apply for this Position

Please ensure you meet geographic and skills requirements before applying.

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