EQT Corporation

AI Engineer – I/II/III/Sr./Expert

EQT Corporation

full-time

Posted on:

Location Type: Remote

Location: Remote • California, Connecticut, Illinois, Louisiana, Massachusetts, Missouri, New Jersey, New York, Tennessee • 🇺🇸 United States

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Job Level

Senior

Tech Stack

AzurePythonSparkSQLUnity

About the role

  • Design, build, and deploy AI/ML models end-to-end: from data exploration and feature engineering through training, evaluation, and productionization.
  • Operate models in production with observability for drift, bias, data quality, and service health; ensure reproducibility, versioning, and governance across data, code, models, and prompts.
  • Develop and maintain ML infrastructure (pipelines, jobs, orchestration, CI/CD) that scales with our needs.
  • Evaluate and tune algorithms for accuracy, efficiency, cost, and fairness.
  • Build generative AI and agent-based solutions (e.g., RAG pipelines, orchestration frameworks) that extend how our teams work and make decisions.
  • Leverage industry-standard AI tools and managed services when they improve speed, quality, or cost, while ensuring alignment with EQT’s architecture and security practices.
  • Partner across functions to shape requirements, SLAs, and success metrics; communicate outcomes in a way that drives understanding and adoption.
  • Stay current with advancements in AI/ML and bring forward ideas aligned with EQT’s architecture, strategy, and evolving business priorities.

Requirements

  • Bachelor’s degree in technical discipline (e.g., computer science, engineering, mathematics) or equivalent combination of education and experience.
  • Experience designing, building, and operating ML systems in production; strong Python and software engineering fundamentals (git, code reviews, testing, packaging).
  • Hands-on with Microsoft Azure and Databricks (notebooks/jobs, Delta Lake, Spark, Unity Catalog, MLflow/Model Registry, and model serving patterns).
  • Solid data engineering skills (advanced SQL, Spark optimization, data modeling, pipeline orchestration, and performance/cost tuning).
  • Applied machine learning expertise (feature engineering, supervised/unsupervised learning, rigorous evaluation, bias/fairness mitigation).
  • Experience building LLM/RAG and agentic applications (embeddings, vector indexes, prompt/policy design, evaluation harnesses).
  • MLOps competency (CI/CD for ML, containerization, secrets/config management, monitoring/alerting).
  • Strong communicator—able to translate technical details into business impact, document outcomes clearly (e.g., READMEs, technical specs, lightweight dashboards/notebooks), and collaborate effectively across technical and non-technical teams.
Benefits
  • Remote work is being considered for this role excluding the following states: California, Connecticut, Delaware, Illinois, Indiana, Louisiana, Massachusetts, Michigan, New Jersey, New York, and Tennessee.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
AI/ML model designfeature engineeringalgorithm evaluationdata engineeringadvanced SQLMLOpsPythonSpark optimizationcontainerizationpipeline orchestration
Soft skills
strong communicatorcollaborationrequirements shapingoutcome documentationbusiness impact translation