AI & Machine Learning Engineer (12 month Internship)

Mitsubishi Power Europe
London
1 year ago
Applications closed

Related Jobs

View all jobs

Energy Data Scientist - AI/ML for Smart Grids

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Reporting to theControl System and Digital Solution ManagertheAI & Machine Learning Internwill focus on supporting in the development of AI and Machine Learning initiatives to provide data led solutions for Turbine operation and maintenance activities.

Duties and Responsibilities

Support the study and development of data led solutions for the operation and maintenance subjects around Steam and Gas turbines. Support the Engineering team for Operation and Maintenance of Mitsubishi Gas Turbines, Steam Turbines, Control Systems and Auxiliary Equipment. To prepare and write technical documents, technical procedures, etc. following the instruction of the Engineering Management team Respond to internal customer requests for support in technical issue resolution, technical and analytical skills while adhering to sound engineering principles, standards, practices, and procedures. Support root cause analysis for technical issues, supporting project assigned to resolve customer technical issue. Document technical data generated by the assigned project consistent with engineering policies and procedures. Prepare technical presentations for customers ensuring the timely communication of significant issues or developments. To support unplanned/forced outages to meet availability goals. Provide commercial teams with technical support for sales and services proposal activities.

Skills and experience we’re looking for

Currently studying for a master’s in engineering, with Computer Science or AI related discipline (or just completing). Ability to demonstrate and execute a project development agenda. Good understanding of various data analysis and modelling methods Ideally possess experience in software libraries and toolboxes such as TensorFlow, Keras, Pytorch, Pandas, Matplotlib and Scikit-Learn. Efficiency in elementary topics in mathematics (calculus, probability, statistics, linear algebra, and optimization) and computer science (algorithms, data structures, parallel/distributed computing). Experience in one or more general purpose programming languages such as Python, Java, C and C++. Experience in mathematical optimisation or statistical machine learning. SQL and Power BI experience (useful) 3D CAD experience (useful) Finite Element Modelling experience (useful)

About Us

The greatest challenge facing the power sector today is ensuring reliable power generation and delivery, while reducing the CO2 emission burden in an increasingly regulated industry. As a trusted partner and pioneering leader in innovative technology and solutions, Mitsubishi Power is efficiently enabling this energy transition for our customers.

Mitsubishi Power in Europe, Middle East and Africa is a leading provider of innovative technology and solutions for the energy sector. Along with our predecessor companies, we have had a presence in the region since . Today, we have more than 1, employees across EMEA, with Centres of Excellence and customer support capabilities across the region.

Committed to decarbonizing EMEA’s power industry, our comprehensive solutions include hydrogen-capable advanced class gas turbines, battery energy storage for short duration storage and hydrogen for long duration storage.

From the delivery of complex engineering solutions through to project execution, Mitsubishi Power can offer you the chance to become part of a global company, leading in the field of thermal power generation systems and environmental technology.

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.

Education Jobs

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

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.

Jobs

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Jobs

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.