Senior Data Engineer- AI​/ML; Remote

Senior Data Engineer

This is a remote position with heavy travel during the first 3-6 months

Ad Hoc is a technology company that empowers organizations to deliver scalable, impactful digital services. Using modern, agile methods, our team creates products that meet people's needs and transform their experience of government.

Our collaborations have shaped some of the defining moments in public-sector service delivery. We've helped build products that connect Veterans to tailored services, help millions access affordable health care, and support important programs like Head Start. As we work with agencies to deliver critical services, we're also changing how the government approaches technology.

Our culture, communications, and tools are built for remote work, enabling us to bring together top talent nationwide. At Ad Hoc, remote life empowers our teams to design work environments that fit their lives and that foster flexibility and collaboration to achieve positive outcomes for our customers.

Ad Hoc values acceptance, accountability, and humility. We aren't heroes. We learn from our mistakes and improve the process for the next time. We build small, inclusive teams to collaborate closely with our partners to solve the right problems and deliver software that works.

The Federal Civilian business unit supports many customers spanning the federal, commercial, and nonprofit space. Our customers include NASA, the General Services Administration, Office of Personnel Management, the Library of Congress, Health & Human Services, and the FDIC. We partner with these agencies to build new capabilities, deliver products, establish data as a strategic asset for informed decision-making, modernize legacy systems, and build the digital service infrastructure necessary to scale their mission impact.

The Senior

AI/ML Engineer will build the adaptive intelligence capabilities that enable communication systems and/or platforms to deliver personalized, context-aware health guidance at population scale. They'll develop a portfolio of AI solutions that may include conversational interfaces for health Q&A, prediction models for disease outbreak trends, content recommendation systems that surface relevant health information, and detection algorithms for health misinformation with the flexibility to pivot based on user research and HHSS priorities.

This engineer will establish MLOps practices that allow rapid experimentation while maintaining production stability, implement responsible AI frameworks that ensure equity and accuracy across diverse populations, and create modular AI components that can be composed into different features as needed. Working at the intersection of public health and machine learning, they'll build systems that augment stakeholder expertise rather than replace it to create AI tools that help epidemiologists analyze data faster, help communicators craft targeted messages, and help the public find trusted health information.

Their work ensures HHS stakeholders can leverage AI innovations responsibly, while maintaining the scientific rigor and public trust essential to HHS' mission.

• Strong influential skills to propose and evaluate multiple approaches to technical and process problems
• Serves as a mentor to individuals within the team
• May leads small, less critical, or temporary team structures and projects
• Presents design documents, system diagrams, etc. to clients, stakeholders, partners, and other engineers
• Fully understands and consistently implements data engineering best practices
• Generates data architecture recommendations and demonstrates the ability to implement them
• Diagnoses and effectively resolves issues with the systems they own, using incidents to inform educational opportunities and system improvements
• Actively mentors and assists more junior engineers in the development of their skills
• Effectively communicates technical issues and developments with team members and clients
• Participates in technical interviews with new candidates

• Bachelor's degree and 7+ years of experience
  • Relevant years of experience may be substituted for education
• Python with multiple ML frameworks (PyTorch/Tensor Flow for deep learning, scikit-learn for traditional ML, Lang Chain/Llama Index for LLM applications) - Versatility to implement everything from simple classification to complex generative AI
• MLOps platforms (MLflow, Weights & Biases, or AWS Sage Maker) - For experiment tracking, model versioning, and production deployment of various AI services that may evolve during development
• Embedding models and similarity search (Sentence Transformers, FAISS, OpenAI embeddings) - Foundation for semantic search, content recommendation, and information retrieval across any AI-powered feature

• Edge deployment frameworks…