Senior ML Specialist (Data Science)

The Green Power Solution idea is to implement a Service that will identify delays in train travel along the routes, caused by Temporary Speed Restrictions (TSRs) and other mid- and long-term issues, and suggest preventive compensations of such delays, to keep trains on time without extra accelerations and thus without extra energy consumption.

Job Description

Qualifications
- 5+ years of hands on experience with ML

• -Optimization Algorithms  (solvers for nonlinear problems (with support for both local and global optimization algorithms), linear programming, constrained and nonlinear least-squares, root finding curve fitting, etc.), COT, RL/DRL
• Strong background in classical machine learning and statistical modeling.
• Deep understanding of optimization algorithms:
• Solvers for nonlinear, constrained, and least-squares problems
• Curve fitting, root finding, and related numerical methods
• Experience with Reinforcement Learning / Deep RL frameworks.
• Familiarity with COT (Causal Optimization Trees) or related decision-based optimization approaches is a strong plus.
• Proficiency in Python (SciPy, NumPy, PyTorch/TensorFlow, scikit-learn, etc.); additional experience with C++ or Julia is a bonus.
• MSc or PhD in Computer Science, Applied Mathematics, Engineering, or a related field.

• As a plus
  FastAPI,(Reddis, Postgres). Python, Docker (Cloud)

• Experience with simulation-based optimization

  Background in operations research or mathematical modeling

  Contributions to open-source optimization or ML libraries

   

Job Responsibilities

We are looking for a highly skilled Machine Learning Engineer with strong expertise in classical ML methods, mathematical optimization, and reinforcement learning (RL/DRL). This role is ideal for someone who enjoys working on challenging applied research and engineering tasks involving solvers, optimization techniques, and real-world problem modeling.

Key Responsibilities

• Design, implement, and optimize algorithms for:
• Nonlinear optimization problems (both local and global solvers)
• Linear programming
• Constrained and nonlinear least-squares
• Root finding and curve fitting
• Develop and apply classical ML models as well as custom optimization-driven solutions.
• Implement and experiment with Reinforcement Learning (including Deep RL) techniques.
• Work on Causal Optimization Trees (COT) and decision-based optimization frameworks.
• Collaborate with cross-functional teams (e.g., product, data engineering, domain experts) to integrate algorithms into production systems.
• Document and communicate technical concepts clearly to technical and non-technical stakeholders.