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Remote, mid-level popular AI role, metro location, and broad LLM/MLOps requirements increase competition.
Core ML/AI skills are transferable, though energy domain knowledge is preferred.
Explicit six-year minimum plus required production ML, LLM, cloud, and MLOps skills make filters strict.
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Design, develop, deploy, and scale AI-powered products and solutions involving LLMs, Generative AI, machine learning, and intelligent agents.
Lead technical initiatives including building production-grade AI applications such as Retrieval Augmented Generation (RAG), AI agents, prompt engineering, and model fine-tuning.
Collaborate with cross-functional teams and stakeholders to capture requirements, optimize AI solutions balancing quality and performance, and mentor junior engineers.
Bachelor's degree in Computer Science, Computer Engineering, Artificial Intelligence, Data Science, or other STEM discipline.
Minimum 6 years professional experience in software engineering, machine learning, data science, AI engineering, or related technical fields.
Proven experience designing, developing, and deploying production-grade AI or machine learning solutions.
Proficiency in Python and modern software engineering practices including source control, testing, CI/CD, and cloud-native development.
Experienced in AI systems with strong domain knowledge of Generative AI, LLMs, RAG, prompt engineering, and AI orchestration frameworks.
Ability to lead AI technical initiatives, influence cross-functional teams, and contribute to AI strategy and governance standards.
Skilled at bridging business requirements and technical implementation, with experience delivering measurable AI-driven business value in industry sectors relevant to Baker Hughes.