Forward Deployed AI/ML Engineer, IV

This is a fully remote position, open to applicants in United States, +1 more country.

📋 Description

• Collaborate with utility clients to design, develop, and implement GenAI and ML systems within their environments.

• Take ownership of technical architecture, encompassing retrieval, orchestration, model selection, serving, evaluation, and monitoring.

• Conduct technical discovery to uncover fundamental client needs.

• Deliver functional systems within the initial weeks and continuously refine them towards production readiness.

• Create task-specific evaluation methods and establish correctness in collaboration with client subject matter experts.

• Develop retrieval and grounding systems across structured, unstructured, and graph-backed data.

• Integrate with client data platforms and business systems, including legacy solutions.

• Implement systems to assess accuracy, latency, cost, and drift.

• Design and deploy applications, interfaces, dashboards, and workflow tools for operators.

• Set achievable expectations with executives regarding AI capabilities.

• Manage scope, deadlines, and expectations in relation to statements of work, addressing risks promptly.

• Contribute reusable accelerators, evaluation harnesses, and reference architectures.

• Provide field feedback to E Source engineering and product teams.

• Implement AI safety, data privacy, and governance controls in compliance with utility regulations.

• Offer post-go-live support and empower client teams to manage delivered systems.

⛳️ Requirements

• Bachelor's degree in computer science, engineering, statistics, or a related quantitative discipline.

• Five or more years of engineering experience, including deploying GenAI or ML systems to production and iterating based on actual usage.

• Expert-level proficiency in Python.

• Proficient in at least one of TypeScript, Scala, or Java.

• Hands-on experience with at least one major model provider or open-weight stack, along with one vector or hybrid retrieval system.

• Skilled in building and applying evaluation frameworks for LLM and ML systems, including RAG, agentic or multi-agent systems, structured extraction, or text-to-SQL.

• Familiarity with LLMOps, covering model serving, latency and cost management, prompt and model versioning, monitoring, and regression detection.

• Working knowledge of at least one major cloud platform: AWS, Azure, or GCP.

• Proficient in Git, Docker, and CI/CD tools.

• Experience utilizing AI coding assistants and agentic development tools.

• Background in the energy or utility sector, or another asset-intensive industry.

• Proven track record of delivering projects on tight schedules, transforming initial discussions into a working system in weeks, not quarters.

• Candidates must be authorized to work for any employer in the US or Canada.

• Willingness to travel to client locations, typically 30 to 50% of the time.

• A Master's degree or PhD in a relevant quantitative field is a plus.

• Experience with production agent frameworks and tool-calling architectures is an added advantage.

• Familiarity with knowledge graphs or semantic layers is an additional benefit.

• Experience in fine-tuning, distillation, or prompt optimization is a bonus.

• Knowledge of classical ML is considered an advantage.

• Experience with Spark, pipeline design, and lakehouse architecture is a plus.

• Familiarity with Databricks Apps or similar operator-facing application experience is an advantage.

• Databricks or cloud AI/ML certifications are a noteworthy benefit.

🏝️ Benefits

• Comprehensive insurance options, including medical, dental, and vision coverage.

• Company-sponsored life insurance.

• Company-funded long- and short-term disability insurance.

• Flexible spending plans for medical and dependent care.

• Paid parental leave.

• Flexible time off (FTO) policy.

• 401(k) plan with a 3% employer match.

• Annual bonus opportunities.

• Remote work arrangement.

• Engaging work with opportunities to enhance skills.

• Global and client travel opportunities.