Battery Energy Storage System Machine Learning Engineer

Job Description

Looking for challenging role? If you really want to make a difference - make it with us

Siemens Energy is focused on helping customers navigate the world’s most pressing energy problems.

As a world leader in developing and producing the most advanced engineering technologies, we improve lives and further human achievements worldwide, while also protecting the climate - all thanks to our employees.

Your new role – challenging and future-oriented

The position presents a unique opportunity to improve and transform the current state-of-the-art Battery Energy Storage Systems (BESS) Digitalization and Analytics. You will, together with dedicated international colleagues, get the chance to work with and build up a world-class BESS Digitalization R&D group. We are looking for flexibility, curiosity, and eagerness to learn in the candidate. You will get the opportunity to have a tangible impact on our success story. This position requires a creative and analytical mindset, a strong understanding of data analysis, modern machine learning tools, algorithms and pipelines, and a solid knowledge base in time-series modelling, dynamic systems and energy storage systems. The candidates will be able to develop their skills and knowledge on two highly demanded topics: data analysis and battery energy storage technology.

  • Developing foundational ML/AI models, algorithms, and solutions involving BESS that can be vetted in experimental setups.
  • Develop requirements for performance prediction models and algorithms based on time series data.
  • Develop, simulate and verify battery state algorithms (SoX) for battery cells, modules, and packs based on voltage, temperature and electrochemical impedance data obtained from field and test set-up. The SoX estimation includes state-of-charge, state-of-health and state-of-power.
  • Integrating new forecasting algorithms into our production code base with robust test coverage.
  • Perform feature engineering and benchmark performance across various load profiles.
  • Investigate the optimum partitioning of algorithms between constrained edge, cloud and hybrid configuration.
  • Working with stakeholders to understand and translate the domain drivers into requirements for the AI solutions in the BESS domain.
  • Working with domain engineers to identify the improvement areas in the currently available techniques.
  • Proactively identify opportunities within Siemens Energy’s BESS R&D group that can benefit from data science analysis and present those findings.
  • Collaborating and coordinating with field test engineers to evaluate and optimise different test procedures, i.e., HPPC, OCV, thermal and calendar/cycling life tests, and design Li-ion cells/packs to meet desired model parameterization, characterization and performance requirements.
  • Support the hardware and software teams on algorithm implementation, integration, testing and verification.
  • Managing technical meetings and drafting and presenting reports.
  • Gain in-depth experience in an exciting industry as you work with storage sizing, energy financial models, energy tariffs, storage controls & monitoring.

We don’t need superheroes, just super minds

  • A Master’s or PhD degree in electrical engineering/electronic engineering/ computer science or similar numerical-intensive fields.
  • Knowledge of mathematical foundations of statistics and statistical signal processing, dynamic systems, and state estimation algorithms.
  • Hands-on experience and in-depth knowledge of probabilistic programming, Bayesian learning, optimisation, deep learning, and other advanced machine learning techniques are highly preferred.
  • Good data analysis and scripting skills to process and analyze large volumes of data.

Expected Skills:

  • You have a passion for time-series forecasting and experience bringing time-series forecasts to production.
  • Full stack/machine learning engineering experience.
  • Programming skills in Python/R/TensorFlow/Pytorch/PyMC etc., and its broader numerical ecosystem.
  • At least 2-3 years of commercial experience developing production-ready real-time projects in machine learning and data science.
  • At least 1-2 years of experience with cloud technologies Azure/AWS/Google Cloud and tech stack, Kubernetes, Kubeflow, MLFlow, or any other data science/ML pipeline or platforms.
  • AzureML, AWS, terraform, continuous integration, monitoring and alerting.
  • Extra credit if you can demonstrate the following:
  • Exposure to energy markets or battery systems modelling, knowledge of Li-ion battery electrochemistry, design of experiments (DOE), parameter optimisation.
  • Knowledge or experience in state estimation algorithms for Lithium-ion batteries
  • You should be able to work as an individual contributor (IC role).
  • You must have a customer focus and practical stakeholder management skills.
  • Version control code (Git), including dev, test and production environments.

Other expected traits:

  • Creativity and analytical mindset
  • Quick learner and detailed oriented.
  • Working collaboratively in a diverse environment. We commit to reaching better decisions by respecting opinions and working through disagreements.
  • Excellent communication skills with an ability to present solutions to senior management.

We’ve got quite a lot to offer. How about you?

This role is based at Site ( Maratha / Wadi / Ambujanagar ). You’ll also get to visit other locations in India and beyond, so you’ll need to go where this journey takes you. In return, you’ll get the chance to work with teams impacting entire cities, countries – and the shape of things to come.

We’re Siemens. A collection of over 379,000 minds building the future, one day at a time in over 200 countries. We're dedicated to equality, and we welcome applications that reflect the diversity of the communities we work in. All employment decisions at Siemens are based on qualifications, merit and business need. Bring your curiosity and imagination and help us shape tomorrow.

Organization: Siemens Energy

Company: Siemens Limited

Experience Level: Experienced Professional

Full / Part time: Full-time

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