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Intertwine Associates

Senior AI / Data Engineer: Data Platforms - Machine Learning & Applied AI

Applied Machine Learning +1Updated on Nov 15
Full-time

About the Job

Requirements

  • At least 7 years of experience building data pipelines, machine learning systems, or AI applications in production, including at least 2 years leading technical work.
  • Expert Python skills, including Pandas and NumPy, and advanced SQL skills, with experience integrating relational and unstructured sources.
  • Deep hands-on experience with Azure data services, or equivalent depth in AWS or Google Cloud.
  • Production experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn.
  • Experience with data validation, schema enforcement, quality assurance, and governance in regulated environments.
  • Experience designing APIs and microservices for analytics and machine learning platforms.
  • Excellent written and verbal communication, including briefing senior, non-technical audiences.
  • U.S. citizenship or lawful permanent residency may be required by contract.
  • Ability to obtain a federal government Public Trust or security clearance where the assignment requires one.

Responsibilities

  • Architect and lead delivery of enterprise data platforms and pipelines on Azure services (Data Lake Storage, Azure SQL, Data Factory, Microsoft Fabric or Foundry) or equivalent cloud services.
  • Set standards for ETL design, schema enforcement, data validation, quality checks, and lineage, and review other engineers' work against them.
  • Design, build, and deploy machine learning and AI solutions, including large language model applications such as retrieval-augmented generation, document understanding, and agentic workflows, with evaluation and guardrails.
  • Build secure API endpoints and microservices that make data and models available to analytics and machine learning platforms.
  • Establish MLOps practices for experiment tracking, model registries, CI/CD, containers, monitoring, and cost and performance tuning.
  • Apply data and AI governance for compliance, reproducibility, auditability, and responsible AI, including the NIST AI Risk Management Framework.
  • Translate mission and business needs into technical roadmaps, estimates, and briefings for client leadership.
  • Mentor engineers and data scientists and lead technical work across multidisciplinary teams.

Desired Qualifications

  • A bachelor's or advanced degree in Computer Science, Data Science, Statistics, Engineering, or a related field, or equivalent professional experience.
  • Experience building applications on large language models, including retrieval-augmented generation, embeddings, vector databases, evaluation, and guardrails.
  • Microsoft certifications such as Azure Data Engineer, Azure AI Engineer, Fabric Data Engineer, or Azure Solutions Architect, or equivalent AWS or Google Cloud certifications.
  • Experience with Databricks, Snowflake, Microsoft Fabric, or similar modern data platforms at enterprise scale.
  • Familiarity with FedRAMP, FISMA, and federal data security requirements.
  • Experience supporting a federal agency, or health, scientific, or research data.
  • An active federal Public Trust or security clearance.

About the Company

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