Machine Learning Engineer– physics based surrogate modelling

Rubius is an accredited IT company. We develop software for clients from various industries—from industrial and oil & gas to retail and medicine. Founded in the very heart of Siberia, Tomsk, we now have partner companies all over the world.

Our solutions are used by Russian and global leaders such as Apple, Tesla, Kaspersky, Amazon, IBM, Uber, Netflix, Gazprom, Russian Railways, and others. The company's partners are located in the UAE (Dubai), Kazakhstan (Astana), Russia (Moscow, St. Petersburg), and Saudi Arabia (Riyadh).

Job Description (contract for one year):

We are seeking a skilled Machine Learning Engineer to develop and deploy Graph Neural Network (GNN) based surrogate models that approximate complex physics simulations for oil & gas pipeline and well networks. This is a hands-on role for someone who can build high-fidelity neural network models that replace computationally expensive reservoir and network simulators (Nexus, Prosper).

Key Responsibilities:

• Design and implement Neural Network architectures to model flow dynamics in interconnected pipeline networks
• Build surrogate models that accurately predict pressure distributions, flow rates, and network behavior under varying operational scenarios (training data is acquired through running simulations of the physics models)
• Create data pipelines to extract network topology and simulation results from physics-based models (Nexus/Prosper) and transform them into graph representations
• Develop training frameworks that incorporate physics constraints (conservation laws, pressure-flow relationships) into neural network loss functions
• Collaborate with petroleum engineers to ensure model predictions align with physical behavior and operational constraints
• Implement model monitoring, validation, and continuous improvement workflows

Required Skills and Experience:

• Strong expertise in Graph Neural Networks (GCN, GraphSAGE, Message Passing Networks) with proven implementation experience
• Deep understanding of deep learning frameworks (PyTorch Geometric, DGL, or TensorFlow GNN)
• Experience building surrogate models or physics-informed neural networks (PINNs) for engineering applications
• Proficiency in Python and scientific computing libraries (NumPy, SciPy, Pandas)
• Demonstrated ability to work with complex data structures (graphs, time-series, spatial data)
• Understanding of optimization techniques and handling large-scale training data

Technical Domain Knowledge:

• Understanding of graph theory and network analysis
• Experience with data structures and graph representations (adjacency matrices, edge lists, sparse tensors)
• Knowledge of hyperparameter tuning, model building and uncertainty quantification in ML models

Nice to Have:

• Background in petroleum engineering, process engineering, or fluid dynamics
• Familiarity with reservoir simulation or pipeline hydraulics
• Experience with MLOps practices and model lifecycle management
• Publications or open-source contributions in graph ML
• Experience deploying ML models in production cloud environments (containerization, API development)

Industry Experience:

Oil & gas industry experience is a strong plus, However, candidates with relevant surrogate modeling experience from other engineering domains encouraged to apply

Educational Background:

• MS/PhD in Computer Science, Computational Engineering, Applied Mathematics, or related field preferred
• Strong mathematical foundation in linear algebra, graph theory, and numerical methods
• Understanding of graph theory and network analysis

What We Offer

Our employees are the main asset of Rubius. We support creative freedom and the soar of engineering thought. We strive to ensure that every member of our team realizes their potential. We care about our employees. Here, both remote and in-office teams feel maximally comfortable.

About Work and Compensation:

• Official employment and timely "white" salary (fully legal & transparent)

• Monthly performance bonus of up to 5%

• Comfortable workspace with an ergonomic chair

• Support with home office setup for remote employees

• Flexible start to the working day

• Bonuses for being part of an accredited IT company

• Business trip expenses on us

About Growth and Development:

• Individual development track

• Work with a Tech Lead and a mentor (we have technical guilds)

• Opportunity to join the company's Technical Council

• 50% compensation for professional certification within individual tracks

• Internal meetups on various topics and detailed guides

About the Office, Perks, and Atmosphere:

• Paid sports activities (even for home workouts)

• Opportunity to get private health insurance (including dental) after the probation period for office employees, and telemedicine for remote employees

• Tasty breakfasts, an office with a veranda and a large kitchen

• Discounts for you and your relatives at Rubius Academy

• Bonuses for the birth of children and marriage

• Diverse corporate events and activities

• Developed and comfortable corporate culture, without hierarchy

• Interest-based communities (soccer, tennis, our own music band, chess club...) and a team where everyone's opinion is heard.

To get to know us better, search for "Rubius" in your browsers.

We will be happy to work in a team with people who love what they do!

Please note that the employment contract will be for a fixed term of one year.