Full-Time
Senior Staff Engineer
AI Engineering
GE Vernova
1,001-5,000 employees
Global energy provider: power, wind, electrification
No salary listed
Bengaluru, Karnataka, India
In Person
Travel of at least two weeks per year is required. Relocation assistance is provided.
Master's, PhD
 AI & Machine Learning (1) |
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- A Master's or PhD degree in Computer Science, Engineering, Mathematics, or a related field is required, along with 10 or more years of relevant experience.
- Experience with prompt engineering and familiarity with tools such as OpenAI's GPT models and Hugging Face are required.
- Proficiency in Python or other programming languages commonly used in artificial intelligence and machine learning development is required.
- Strong problem-solving skills and attention to detail are required.
- Excellent communication skills and the ability to articulate complex technical concepts to non-technical stakeholders are required.
- The ability to work collaboratively in a team environment and adapt to changing project requirements is required.
- Willingness to travel a minimum of two weeks per year is required.
- Collaborate with domain experts to understand business needs and translate them into clear and effective large language model prompts.
- Develop, test, and refine prompts for a variety of use cases, ensuring high accuracy and relevance in generated outputs.
- Work closely with software developers to integrate large language model solutions into existing or new applications.
- Contribute to the development of a scalable framework for prompt engineering, promoting reuse and knowledge sharing across different business units.
- Assist in gathering and analyzing user feedback to continually improve prompt effectiveness.
- Stay up to date with advancements in large language model technology and contribute to strategic decisions on tool and platform selection.
- Document prompt engineering processes, best practices, and use case outcomes to build a comprehensive knowledge base.
- A PhD in Computer Science, Engineering, Data Science, AI Engineering, or a related field.
- Experience with machine learning frameworks such as PyTorch and data processing libraries such as Pandas and NumPy.
- Previous experience or internships involving natural language processing or machine learning projects.
- Familiarity with version control systems such as Git.
- Understanding of traditional industry operations and challenges.
GE Vernova is a global energy company created in 2024 to support the electricity grid and the energy transition, with three focuses: Power, Wind, and Electrification. It sells large-scale equipment, signs long-term service agreements, and provides software to utilities, independent power producers, grid operators, and large industrial energy users. Its products include H-Class gas turbines that can burn natural gas with blends of hydrogen toward 100% hydrogen, Haliade-X offshore wind turbines up to 14.7 MW, and GridOS software that unifies grid data to help manage networks and integrate renewables. By combining hardware, services, and software under GE heritage, it aims to meet rising electricity demand while accelerating decarbonization across global energy systems.
Company Size
1,001-5,000
Company Stage
N/A
Total Funding
$17.6M
Headquarters
Cambridge, Massachusetts
Founded
2022
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Simplify's Take
What believers are saying
- Q2 2026 orders jumped 88% to $24.2 billion, led by Power and Electrification.
- Data center orders exceeded $5 billion in first-half 2026, more than all 2025.
- Management raised 2026 guidance and expects at least 125 GW gas backlog by year-end.
What critics are saying
- Wind orders fell 40% in Q2 2026, and GE Vernova expects roughly $400 million losses.
- Massachusetts courts blocked GE Vernova from exiting Vineyard Wind over unpaid $300 million claims.
- Tariff uncertainty and permitting delays still throttle U.S. onshore wind orders through 2026.
What makes GE Vernova unique
- GE Vernova sells the grid and turbine hardware that runs 25%-30% of global electricity.
- Its 116 GW gas backlog and H-Class turbines lock customers into decade-long service contracts.
- GridOS, HVDC, and Prolec-backed electrification make it harder for utilities to multi-source suppliers.
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Benefits
Health Insurance
Dental Insurance
Vision Insurance
Life Insurance
Disability Insurance
401(k) Retirement Plan
401(k) Company Match
Paid Vacation
Paid Parental Leave
Mental Health Support
Relocation Assistance
Performance Bonus
Company News
SHINE is joining a GE Vernova-led project funded by the Department of Energy's Advanced Research Projects Agency-Energy to develop modernised nuclear material tracking systems for fuel recycling facilities. The project aims to use artificial intelligence to optimise spent nuclear fuel tracking and measurement. As a subcontractor, SHINE is developing improved sensor deployment and AI-powered material-tracking systems for nuclear fuel recycling facilities. The technology, called Monochromatic Assays Yielding Enhanced Reliability (MAYER), is designed to track and measure nuclear material in real time, feeding information into a virtual digital twin. The system aims to replace current methods involving redundant instrumentation, manual sampling, and periodic shutdowns for inventory checks. SHINE's participation supports its broader goal of building a commercial nuclear fuel recycling facility in a lower-security regulatory category.
GE Vernova reported strong second-quarter results with revenue rising 22% year-over-year to $11.1 billion, surpassing analyst estimates by $330 million. Total orders surged 88% organically to $24.2 billion, driven by AI-related demand for gas turbines and grid equipment. However, the company's Wind segment saw organic orders plunge 40%. The decline stems from quality-control issues, including turbine failures at major projects, alongside inflation and supply chain problems that compressed margins on fixed-price contracts. The segment now represents just 5% of total orders, down from 13% in 2025. GE Vernova's Wind business posted a negative 19% adjusted EBITDA margin in the first half of 2026. Despite this, investors remain unfazed as the Power and Electrification segments deliver strong margins of 17.6% and 18.2% respectively, easily offsetting Wind's losses.
Weirton, WV – August 12, 2026 – Form Energy, Inc., an American technology company developing and commercializing a new class of cost-effective, multi-day energy storage systems, announced today a $750 million Series G financing round led by T. Rowe Price, which also led the company’s prior Series F round. This round brings Form Energy’s total […]
GE Vernova, General Electric's former energy division spun off in 2024, reported a $176.3 billion backlog in Q2 2026, up 37% year-over-year. The company's growth has been driven by expanding cloud, AI, and data centre markets requiring increased power infrastructure. Total orders surged 89% in the first half of 2026, with Power and Electrification segments rising 99% and 131% respectively. GE Vernova expects full-year revenue growth of 19% to 22%. Despite strong performance, shares declined 5% over the past month whilst the S&P 500 gained 3%. The pullback followed Q2 results where adjusted EBITDA and earnings per share missed Wall Street expectations due to increased capacity spending and additional losses in the Wind division.
GE Vernova and Eaton released second-quarter 2026 results highlighting surging demand from AI infrastructure buildout. Vernova reported $5.50 billion in Power segment revenue with gas equipment orders up 134% organically. The company booked $2.7 billion in data centre orders during the quarter alone and expects to reach at least 125 gigawatts of gas equipment under contract by year-end. Total backlog stands at $176 billion. Eaton posted revenue of $8.531 billion, up 21.39%, with adjusted earnings per share of $3.15. Data centre revenue grew roughly 65% in both its Electrical Americas and Electrical Global divisions. The Boyd Thermal liquid-cooling business, acquired for $9.55 billion in March, generated $432 million in second-quarter revenue. Vernova guided free cash flow to $11.5 billion to $12.5 billion, whilst Eaton raised its full-year earnings guidance to $13.40 to $13.60 per share.