Reinforcement Learning Specialist

Lausanne, Vaud, Switzerland

Applications have closed

INAIT is an AI scale-up founded in 2017 by Henry Markram, renowned professor in neuroscience, director of EPFL’s Blue Brain Project (BBP) and co-founder of Frontiers. INAIT has raised CHF 55 million to fulfill its mission: build a new dimension of AI reverse engineering the way the brain works.

We offer B2B and B2C products and solutions in computer vision, forecasting and document understanding across industries: automotive, healthcare, manufacturing, trading and scientific publishing.

We are a team of 50+ ambitious & creative talents and are looking for an impact-driven research scientist with focus on (Deep) Reinforcement Learning to join the INAIT Forecast Team. The INAIT Forecasting team is developing exciting use cases for financial and non-financial applications.

Your responsibilities

  • Apply state of the art machine learning and deep learning techniques to automatically learn strategies based on streams of data
  • Conduct and apply RL research for actionizing timeseries forecasts (e.g., automatic trading, asset optimization, preventive maintenance, ...)
  • Turn business and decision problems into games (aka environments) that could be solved by reinforcement learning algorithms or control algorithms
  • Conduct and apply RL and control theory research to solve those games
  • Contribute production level code to INAIT software stack
  • Provide detailed analysis and present results in a clear manner

Requirements

Essential experience required

  • Experience in solving complex tasks (in difficulty and scale) using (deep) reinforcement learning
  • Developing and optimizing machine learning models in python using frameworks such as PyTorch, TensorFlow, scikit-learn, ...
  • Familiar with git command line and knowledge of the software development life-cycle (continuous integration, version control, debugging and documentation).

Essential skills

  • Robust analytical, mathematical, statistical, and probability skills
  • Strong problem-solving skills with an emphasis on product development
  • Strong drive to learn and master new technologies and techniques
  • Knowledge in game theory and multi-agent machine learning is a plus
  • Excellent communication and presentation skills
  • Proven ability to work both independently and in team-based environments

Preferred skills

  • Established publication record at well-known machine learning conferences
  • PhD in mathematics, engineering, computer science or equivalent with 3+ years of experience in machine learning
  • Professional experience in applying RL to forecasting use cases
  • Professional experience in time series forecasting
  • Professional experience in commodity trading / finance
  • Previous experience in deploying machine learning algorithms

Recruitment process

  • 30-mn call with our HR manager
  • 60-mn python interview
  • 60-mn ml/dl/reinforcement learning interview
  • 60-mn interview with the team
  • 30-mn meet the CEO and CTO

What we offer

  • Hybrid working model.
  • Dynamic work environment, a multicultural and highly talented team in a growing scale-up.
  • Attractive salary and compensation scheme including a company participation package.
  • Well-located office in Lausanne with easy access by public transportation.
  • Free seasonal fresh fruits and drinks.
  • Discounts for some products and services in Switzerland

Tags: Computer Science Computer Vision Deep Learning Engineering Finance Git Machine Learning Mathematics ML models PhD Python PyTorch Research Scikit-learn Statistics TensorFlow

Perks/benefits: Career development Conferences

Regions: Europe North America
Job stats:  29  4  0

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