{"id":2996292,"url":"https://alion.io/job/ge-vernova-staff-ai-engineer-2","title":"Staff AI Engineer","company":{"id":6165,"name":"GE Vernova","domain":"gevernova.com","url":"https://alion.io/company/ge-vernova","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":83,"open_postings":423,"ghost_share":0.007,"stale_share":0.645,"repost_share":0.04,"time_to_fill_p50_days":27,"computed_at":"2026-10-30T05:48:23Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":33000,"max_usd":77000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":13},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"C++","optional":false},{"name":"Edge AI","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Synthetic Data","optional":false}],"status":"live","first_seen_at":"2026-10-12T00:00:00Z","employer_posted_date":"2026-10-12","last_verified_at":"2026-10-30T13:58:57Z","board_verified":true,"closed_at":null,"days_open":18,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":18},"description":"Job Description Summary\nGE Vernova’s Power Conversion & Storage business is at the forefront of the energy transition. We are seeking several highly skilled Senior AI Engineers to join our teams to design, develop, and deliver AI-driven solutions that improve efficiency and decision-making across our business.In this role, you will collaborate closely with domain experts and cross-functional teams to apply artificial intelligence, generative AI, and machine learning to real-world industrial challenges, helping accelerate innovation, productivity, and operational excellence.\nA defining part of the role is technical judgment; choosing the right tool for each problem: classical machine learning, deep learning, GenAI, or pure software development when needed.\nJob Description\nAI & ML Solution Development & Integration\nDesign, develop, and implement AI solutions, including generative AI, machine learning models, neural networks, and optimization algorithms, to improve business process efficiency and effectiveness.\nSelect the appropriate modelling approach for each problem and articulate the trade-offs behind that choice.\nOwn the machine learning lifecycle: dataset construction, metrics definition, acceptance criteria in accordance with the stakeholders needs, evaluation strategies.\nTranslate business and operational needs into scalable AI-enabled tools, applications, and workflows.\nSupport the deployment and integration of AI/ML models into existing business and technical systems, software environments, and products where applicable, including monitoring for drift, performance degradation, and running cost.\nTechnical Implementation & Architecture\nCollaborate with domain experts to identify high-value use cases and define technical requirements for AI solutions.\nDefine and document the solution architecture end to end: from data sources to the integration with the existing enterprise and technical IT landscape.\nDesign cloud-ready and on-premises solutions aligned with company IT, cybersecurity and data-governance standards.\nIntegrate AI/ML capabilities into hardware, software, and business process ecosystems in a way that supports reliability, usability, and maintainability.\nContribute to the development of robust, production-ready AI solutions suitable for industrial environments.\nSolution Delivery, Partner & Contractor Management\nWrite clear technical specifications, statements of work, and acceptance criteria for work delivered by external contractors, software vendors, or internal digital teams.\nContribute to supplier, platform, and tool selection through structured technical evaluation, benchmarking, and proof-of-concept comparison.\nSteer and review the work of internal & external partners: technical follow-up, design reviews, code and model reviews, quality gates, and acceptance testing; remaining the technical owner and guardian of the delivered solution.\nEnsure solutions remain maintainable after handover through documentation, knowledge transfer, and clearly assigned ownership, so that delivered tools do not become orphaned.\nData Strategy & Analytics\nLead or support the collection, processing, structuring, and analysis of large-scale operational and business data.\nAssess data readiness ahead of any development (availability, quality, labelling needs, access rights, confidentiality) and define strategies to close the gaps.\nIdentify patterns, trends, and performance improvement opportunities using advanced analytics and AI methods.\nDevelop data-driven solutions such as predictive maintenance, anomaly detection, quality and performance prediction, forecasting, cost analysis, document and requirement analysis, and knowledge support tools.\nCross-Functional Collaboration\nWork closely with technical, operational, business and IT teams to ensure AI solutions meet business and industry requirements for safety, reliability, performance, and scalability.\nCommunicate technical concepts clearly to both technical and non-technical stakeholders.\nHelp align AI initiatives with business priorities, operational goals, and constraints.\nSupport end-user adoption: training, onboarding, feedback loops and measurement of the benefits realized once the solution is live.\nContinuous Innovation\nEvaluate emerging technologies such as edge AI, synthetic data, reinforcement learning, and large language models for industrial and business applicability.\nStay current with developments in AI, machine learning, and digital tools, and recommend practical adoption opportunities.\nMaintain an active technology watch on the AI tooling landscape and filter it, distinguishing capability gains from hype before proposing adoption.\nContribute to building an innovation-oriented culture through knowledge sharing, experimentation, and continuous improvement.\nYour Profile\nEducation\nMaster’s degree in Engineering, Computer Science, Data Science, Applied Mathematics, or a related field.\nExperience\nOverall 8+ Years Experience.\nSeveral years (2 to 4) of professional experience in artificial intelligence, machine learning, data science, software engineering, or a comparable technical role.\nExperience developing and deploying AI/ML solutions in industrial, technical, or other complex operational environments is preferred.\nTechnical Expertise\nStrong programming skills in Python, C++, or similar languages, and proficiency with modern development environments such as VS Code.\nAdditional Information\nRelocation Assistance Provided: Yes","description_format":"text","description_chars":5481,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":["Relocation assistance"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":true,"industries":["Hydroelectric","Power Grid","Industrial Machinery","Wind 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