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About This Role
The Opportunity
Control systems are at the heart of how energy gets generated, converted, and delivered reliably at scale. In this role, you will advance the modeling, control, and optimization technologies that power GE Vernova's energy portfolio — from renewables and gas power to grid solutions and power conversion. You will work at the intersection of rigorous research and real-world application, developing algorithms and systems that move from the lab into next-generation products used by utilities and grid operators around the world.
This is a senior individual contributor role with team leadership responsibilities, embedded within GE Vernova's research organization and connected to external partners across industry, academia, and U.S. government agencies including the Department of Energy (DOE) and Department of Defense (DOD).
> Please note: A Top Secret security clearance is required for this role. Legal authorization to work in the U.S. is required. GE Vernova is unable to sponsor employment visas for Master's-level candidates for this opening. Due to the nature of data handled at GE Research, candidates who are nationals of embargoed countries subject to restriction under U.S. Export Administration Regulations (EAR) — currently North Korea, Syria, Iran, and Cuba — cannot be considered, unless they hold U.S. person status under U.S. export control laws or subsequent citizenship from a non-embargoed country. You must be 18 years or older to apply. Job Description
What You'll Do
- Lead cross-functional research teams and contribute as a senior individual to the development of advanced controls, optimization, estimation, and detection algorithms for GE Vernova's energy businesses.
- Validate solutions through simulation and hands-on testing on target systems, ensuring performance meets technical and operational requirements.
- Document your work through patent applications, peer-reviewed publications, and technical reports that advance the field and protect GE Vernova's intellectual property.
- Transfer mature technologies to GE Vernova engineering teams for integration into next-generation products and services.
- Build and maintain awareness of emerging developments in systems technology, identifying new research directions and application opportunities.
- Collaborate with colleagues across GE Research, GE Vernova business units, and external partners from academia, industry, and government.
Who You Are
You are a researcher who bridges theoretical rigor and practical engineering impact — someone who finds energy in solving hard problems and satisfaction in seeing your work shape real systems at scale.
Required
- A doctorate in an engineering field with significant experience in advanced controls, optimization, estimation, or detection algorithm design; or a Master's degree in an engineering field with 10+ years of experience in the same domain.
- Deep technical knowledge in one or more of: advanced controls, optimization, estimation, or detection algorithms.
- Proficiency in MATLAB/Simulink and at least one of C, C++, or Python.
- Demonstrated experience developing and implementing algorithmic solutions for complex physical systems such as mechanical systems, chemical plants, power systems, transportation, or aviation.
- A strong publication record in peer-reviewed journals and conferences.
Preferred
- Experience with real-time implementation of system solutions across varied hardware platforms.
- Familiarity with machine learning (ML) and artificial intelligence (AI) techniques applied in a controls context.
- Experience developing cybersecurity algorithms for industrial control systems.
- Proficiency in source code management using Git/GitHub.
- Experience contributing to government funding applications and project proposals.
- Experience leading project teams, including scheduling, milestone tracking, and technical reviews.
- Demonstrated ability to advance an idea from concept through to product application.
Why GE Vernova
GE Vernova employees rise to the challenge of building a world that works. We offer varied, competitive benefits designed to reward strong performance and support your personal and family needs — including health and wellness programs, financial benefits, and flexible arrangements suited to how you work and live today. We invest in your growth through structured on-the-job learning, development pathways, and access to a global network of researchers and engineers working on some of the most consequential energy problems of our time.
GE Vernova offers a great work environment, professional development, challenging careers, and competitive compensation. GE Vernova is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
GE Vernova will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a drug screen (as applicable).
Relocation Assistance Provided: Yes
For candidates applying to a U.S. based position, the pay range for this position is between $113,200.00 and $188,800.00. The Company pays a geographic differential of 110%, 120% or 130% of salary in certain areas. The specific pay offered may be influenced by a variety of factors, including the candidate’s experience, education, and skill set.
Bonus eligibility: discretionary annual bonus.
This posting is expected to remain open for at least seven days after it was posted on October 15, 2026.
Available benefits include medical, dental, vision, and prescription drug coverage; access to Health Coach from GE Vernova, a 24/7 nurse-based resource; and access to the Employee Assistance Program, providing 24/7 confidential assessment, counseling and referral services. Retirement benefits include the GE Vernova Retirement Savings Plan, a tax-advantaged 401(k) savings opportunity with company matching contributions and company retirement contributions, as well as access to Fidelity resources and financial planning consultants. Other benefits include tuition assistance, adoption assistance, paid parental leave, disability benefits, life insurance, 12 paid holidays, and permissive time off.
GE Vernova Inc. or its affiliates (collectively or individually, “GE Vernova”) sponsor certain employee benefit plans or programs GE Vernova reserves the right to terminate, amend, suspend, replace, or modify its benefit plans and programs at any time and for any reason, in its sole discretion. No individual has a vested right to any benefit under a GE Vernova welfare benefit plan or program. This document does not create a contract of employment with any individual.
Candidates should be aware that this role involves a client's critical infrastructure; shortlisted candidates would therefore be subject to heightened security checks as directed by our clients. All personal data will be handled with the utmost confidentiality and in accordance with our data protection policies, solely for recruitment and security purposes.
Salary Context
This $113K-$188K range is below the median for Research Engineer roles in our dataset (median: $185K across 72 roles with salary data).
View full Research Engineer salary data →Role Details
About This Role
Research Engineers bridge the gap between research and production. They implement papers, build experiment infrastructure, optimize training pipelines, and make research prototypes production-ready. They're the engineers who make research work at scale.
The role sits at a unique intersection. You need to understand the math well enough to implement novel architectures correctly, and you need the engineering chops to make them run efficiently on distributed systems. When a research scientist has a breakthrough idea, you're the person who turns it from a notebook prototype into a training pipeline that runs on 256 GPUs.
Across the 11,520 AI roles we're tracking, Research Engineer positions make up 2% of the market. At GE Vernova, this role fits into their broader AI and engineering organization.
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
What the Work Looks Like
A typical week involves: implementing a new attention mechanism from a recent paper, profiling and optimizing a training pipeline that's bottlenecked on data loading, building evaluation infrastructure for a new benchmark, debugging distributed training issues across a GPU cluster, and pair-programming with a research scientist on their latest experiment. The work is deeply technical.
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
Skills Required
Strong software engineering fundamentals plus ML knowledge. Python, C++, and CUDA experience are common requirements. You'll need to read papers and turn ideas into working code. Distributed systems experience (especially distributed training) is highly valued. Performance optimization skills separate great candidates from good ones.
Experience with large-scale training infrastructure (FSDP, DeepSpeed, Megatron), GPU programming (CUDA, Triton), and the internals of ML frameworks (PyTorch internals, custom autograd functions) is what makes candidates stand out. The best research engineers can debug issues that span the full stack from GPU memory management to numerical precision to algorithmic correctness.
Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.
Compensation Benchmarks
Research Engineer roles pay a median of $252,000 based on 476 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($151K) sits 40% below the category median. Disclosed range: $113K to $188K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
GE Vernova AI Hiring
GE Vernova has 21 open AI roles right now. They're hiring across AI/ML Engineer, Research Engineer, AI Product Manager, AI Software Engineer. Positions span Bengaluru, Karnataka, India, Niskayuna, NY, US, Niskayuna, NY. Compensation range: $120K - $203K.
Location Context
Across all AI roles, 6% (708 positions) offer remote work, while 10,737 require on-site attendance. Top AI hiring metros: New York (3,257 roles, $221,000 median); San Francisco (2,766 roles, $260,550 median); Los Angeles (1,580 roles, $210,000 median).
Career Path
Common paths into Research Engineer roles include Software Engineer, ML Engineer, Research Intern.
From here, career progression typically leads toward Senior Research Engineer, Research Scientist, ML Architect.
This is one of the best entry points into AI research without a PhD. Build a strong engineering portfolio with ML projects, contribute to open-source ML frameworks, and demonstrate that you can implement complex ideas correctly and efficiently. The transition to Research Scientist is possible with published first-author work, which some research engineer roles support.
What to Expect in Interviews
Technical screens test both engineering skill and research understanding. Expect coding rounds with performance-critical implementations (GPU optimization, efficient data loading). Be prepared to discuss papers relevant to the team's research area and explain how you'd implement key ideas. System design questions focus on training infrastructure: distributed training, experiment tracking, and compute resource management.
When evaluating opportunities: Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.
AI Hiring Overview
The AI job market has 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 roles).
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
The AI Job Market Today
The AI job market spans 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (140) are outnumbered by mid-level (5,630) and senior (4,176) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $266,050 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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