Principal Engineer – Data Science

GE Vernova
Stafford, England
12 months ago
Applications closed

Related Jobs

View all jobs

Director of AI Platforms & Delivery - AI, Tech

Adecco Cambridge, Cambridgeshire, United Kingdom

Principal CFD Engineer

PhysicsX United Kingdom
Hybrid

Principal Machine Learning Engineer

Faculty London, United Kingdom
Hybrid

Principal Machine Learning Engineer

Faculty AI London, United Kingdom
Hybrid

Principal Machine Learning Engineer

PhysicsX United Kingdom
Hybrid

Principal Data Scientist / Algorithm Engineer

PhysicsX United Kingdom
Hybrid
Posted
20 Oct 2025 (12 months ago)
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

Industry Insights

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

What Is an AI Forward Deployed Engineer? The Fastest-Growing Job in AI for 2026

If you have been watching AI job boards over the past year, one title keeps surfacing again and again: the forward deployed engineer, or FDE. It has gone from a niche term known mainly to Palantir alumni to arguably the hottest role in the entire AI hiring market. Job postings for forward deployed engineers have exploded, salaries have climbed past levels most software engineers will ever see, and the biggest names in AI — OpenAI, Anthropic, Google, Salesforce, Databricks and Palantir — are all competing for the same small pool of talent. So what exactly is an AI forward deployed engineer, why has demand surged so dramatically, and how do you position yourself to land one of these roles? This guide breaks it all down for AI engineers, software engineers and data scientists looking at their next move.