7 days ago
Remote, United StatesSenior
Base Salary
$150k - $200k/yr
Responsibilities
- Design and maintain entity, record, and relationship data models with source-level provenance
- Implement probabilistic record matching, blocking, candidate generation, pairwise scoring, clustering, threshold policies, deduplication, and known-record suppression
- Develop relevance and priority models, calibration and threshold strategies, abstention policies, feature engineering, baselines, and cost-aware error analysis
- Implement embeddings, vector storage, retrieval, language-model integrations, prompts, output schemas, grounded citations, model packaging, serving, versioning, and rollback
- Build secure ingestion, transformation, validation, and publishing pipelines for structured, semi-structured, and unstructured sources
- Implement quality checks, schema validation, lineage capture, audit logging, source-drift detection, and representative synthetic data generation
- Document assumptions, caveats, transformations, limitations, interfaces, and data flows for formal review
- Instrument telemetry and maintain audit trails for recommendations, human overrides, and model versions
- Submit model and pipeline changes through a gated release process
Requirements
- At least 5 years of experience in data engineering, data architecture, applied machine learning, ML engineering, or production analytics engineering
- Strong Python and SQL skills with experience handling large, imperfect operational data
- Experience delivering systems for sustained operational use rather than exploratory analysis alone
- Routine use of AI-assisted development with the judgment to verify generated output
- Ability to explain technical decisions to stakeholders who must defend the results
- US citizenship is required
- Active US Secret clearance is required, along with favorable investigation and CAC eligibility from the start
- Willingness to travel up to 25%
- Preferred active Top Secret clearance
- Preferred experience with probabilistic matching, record linkage, master data management, identity management, graph data modeling, PostgreSQL, pgvector, or graph algorithms
- Preferred experience with model calibration, threshold design, cost-sensitive learning, scikit-learn, XGBoost, or PyTorch
- Preferred production retrieval-augmented generation, prompt and output-schema design, grounded generation testing, self-hosted or open-weight models, fine-tuning, adapters, or custom embeddings
- Preferred experience with AWS Glue, Airflow, dbt, Spark, Kafka, or NiFi
- Preferred experience with federal DevSecOps, RMF, ATO, DoW cloud environments, hardened base images, and advancing pipelines through accreditation and deployment
- Preferred experience with sensitive federal or defense data and privacy or comparable handling constraints
- Preferred responsible AI experience, including documentation, model cards, fairness testing, model monitoring, or NIST AI RMF
Benefits
- Fully remote, results-based work environment
- Up to 25% travel to DEFCON AI headquarters, customer sites, and vendor facilities
- 100% employer-paid medical, dental, and vision insurance for the employee and family
- Unlimited paid time off with manager approval
- Flexible workday
- 14 weeks of fully paid parental leave
- Competitive salary, bonus, and equity package
Tech Stack
Categories
About DEFCON AI
RESILIENCE IN THE FACE OF DISRUPTION. DEFCON AI is an insights company that leverages artificial intelligence, mathematical optimization, data analytics, and software engineering for resilient optimization of complex systems. In today’s dynamically changing world, DEFCON AI’s technology aligns outcomes with operational goals, better decision making, and empowers customers to anticipate assess, and mitigate the impacts of disruptions.