Power Systems Engineer

Wipro Technologies
Wokingham
10 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist in Power Electrical Systems

Data Scientist – Power Grids & Energy Analytics

Research Engineer, Machine Learning - Paris/London/Zurich/Warsaw

Data Engineer – Modern Data & AI Platforms

Data Engineer – Modern Data & AI Platforms

Staff Machine Learning Engineer

Search by ‘Skills’ or ‘Keywords’ or 'Requisition ID’

Search by Country

Select how often (in days) to receive an alert:

Work with us

Requisition ID: 36862

City: Wokingham

Country/Region: GB

Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients’ most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world. For additional information, visit us at www.wipro.com.

Job Description

Power Systems Engineer

Role Overview:

As a Power Systems Engineer at Wipro, you will work with a global team responsible for designing and implementing Power Systems Network Analytics and Smart Grid solutions. You will contribute to the research and development of innovative solutions using machine learning, deep learning, and RPA for global utilities, addressing operational and commercial challenges efficiently and effectively in their journey towards a zero or low carbon economy.

Responsibilities:

  1. Work as a Power Systems Analysis expert engineer/developer in complex agile customer projects to implement new network analysis & analytics solutions leveraging expertise in Python, Machine Learning, commercial analytics, DIgSILENT PowerFactory, DPL, and optimization techniques for Electricity Network and Grid Operator.
  2. Analyze requirements and understand functionality to be implemented using Python, DIgSILENT PowerFactory, and energy modeling tools, and other tools and techniques.
  3. Collaborate with business experts, business analysts, and solution architects on a daily basis to develop existing Python-based tools and analyze data.
  4. Design and develop Python applications to meet functional and non-functional requirements, ensuring high availability and high performance.
  5. Develop Python interface with PowerFactory using python APIs and DPL or other techniques.
  6. Deploy the Python code into various environments.

Desired Skills and Experience:

  1. Considerable relevant experience in Python programming and its application for complex problem solving, optimization, data processing, etc.
  2. Expertise in power system engineering, analysis, and experience in power system component modeling in Python.
  3. Considerable Experience in DIgSILENT PowerFactory and DPL and Python programming on top of DPL.
  4. Knowledge of the basics of power system engineering and some appreciation of the GB network is essential.
  5. Expertise in Pandas, Numpy, Scipy, ML libraries, matrix manipulation, Networkx scientific algorithms, and Pyomo.
  6. Expert knowledge in data management and visualization techniques in Python is desirable.
  7. Version Control using git is essential.
  8. Experience using MS VBA scripting to be able to analyze and enhance the code.
  9. Experience in linear programming and tools such as Gurobi/CPLEX is a plus.
  10. Experience working with visualization libraries Python API is desirable.
  11. Programming experience in DIgSILENT DPL, C/C++ etc.
  12. Expertise in Power Systems analysis functions such as Load Flows, Contingency, fault level calculations, stability assessment, Inertia Estimation, etc.
  13. Experience in Python-based interface/integration development with other systems running in different operating systems (using web service, remote procedure calls, APIs, database links, etc.).
  14. Experience in Linear Programming, mixed integer programming, algebraic modeling language (AMPL).
  15. Expertise in Mathematical algorithms.
  16. Knowledge of the Electricity industry including Power Systems Network Planning, Electricity supply demand balancing, frequency control, Electricity markets, system operations, etc.

We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA - as the world around us changes, so do we. Join a business powered by purpose and a place that empowers you to design your own reinvention. Come to Wipro. Realize your ambitions. Applications from people with disabilities are explicitly welcome.

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.