Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Principal Engineer – Data Science

GE Vernova
Stafford
1 month ago
Create job alert
Principal Engineer – Data Science

GE Vernova


Overview

The Principal Engineer – Data Science combines a high level of technical expertise with sound business acumen and a strong understanding of engineering processes. Principal Engineers are part of a formal career path for technical personnel who want to continue to develop and grow their technical competencies while having increasing impact on the business.


Responsibilities

  • Lead technical direction for large projects during contract execution phase.
  • Support Consulting Engineers in business line technology strategy definition and Multi-Generational Product Plan (MGPP).
  • Chair design reviews for individual components, sub-assemblies and key engineering deliverables at tendering and contract execution stages.
  • Provide key technical consultation on product problems throughout the business, including supplier and field support and perform technical rescues when needed.
  • Participate in Patent Evaluation Board (PEB) to protect technology that gives the business a competitive advantage.
  • Represent the business externally at conferences or in professional working bodies (IEC, CIGRE etc) and maintain active relationships with relevant academic institutions.
  • Lead early research and proof-of-concepts for promising technology applications.
  • Provide ad-hoc technical guidance to the Engineering/Technology leadership team as required, e.g., joining customer negotiations or supplier audits.
  • Develop technical competencies by establishing and delivering structured technical training schemes within one’s own business lines.
  • Mentor and coach identified high potential Engineering talents within one’s business lines.

Qualifications & Requirements

  • Master of Science in Computer Science, Machine Learning, Engineering, or Mathematics.
  • At least 10 years of experience in an engineering or data science capacity.
  • Experience with state-of-the-art machine learning technologies & techniques in at least one of the following domains: Natural Language Processing, Time Series, Computer Vision.
  • Strong oral and written communication skills.
  • Strong interpersonal and leadership skills.
  • Problem analysis and resolution skills.
  • Ability to work across organizations in a matrix environment.
  • Preferably having taken a Senior Engineer or Senior Researcher role.
  • Able to interface effectively with most levels of the organization.
  • Able to pursue Engineering integrity in adverse conditions.
  • Lean experience preferred.

Additional Information

Relocation Assistance Provided: No.


This is a remote position.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Scientist

Principal Machine Learning Engineer

Principal Data Scientist

Principal Data Scientist

Lead Data Scientist

Senior Machine Learning Engineer

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.

AI Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation. Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead. This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.