Artificial Intelligence and Machine Learning Engineer, Lead
Listed on 2026-02-12
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IT/Tech
AI Engineer, Data Engineer, Cloud Computing, Machine Learning/ ML Engineer
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Artificial Intelligence and Machine Learning Engineer, Lead
The Opportunity:
As an experienced AI/ML Engineer, you will help develop and operationalize secure, scalable, production-grade AI solutions that sustain and advance mission-critical capabilities. You will work as part of a cross-functional team, collaborating with data engineers, data scientists, solution architects, and product owners to deliver high-impact AI/ML solutions across a broad range of use cases.
In this role, you will modernize and operate an end-to-end, AI-driven platform built on Databricks, Palantir, Amazon Bedrock, and custom AI/ML models. You will sustain and enhance batch and streaming data pipelines, improve data quality, lineage, and observability, and partner with data engineers and subject matter experts (SMEs) to define data contracts and feature pipelines. You will modernize legacy case selection capabilities by decomposing them into scalable services and operationalizing rules, and model-driven scoring, prioritization, routing, and human-in-the-loop review.
You will build and operate production-grade ML pipelines with strong MLOps practices, including versioning, CI/CD, monitoring, drift detection, explainability, and fairness, and integrate with shared enterprise services using API-first and event-driven patterns. You will also harden the platform to meet security and compliance requirements, including ATO, produce architecture and operational documentation, and collaborate closely with product, fraud, and case management teams in an Agile delivery environment.
Due to the nature of work performed within this facility, U.S. citizenship is required.
Join us. The world can’t wait.
You Have:
- Experience building, deploying, and operating production ML models such as supervised, unsupervised, and anomaly detection, including techniques for imbalanced datasets
- Experience with ML engineering and MLOps, including model versioning, CI/CD for ML, monitoring, drift detection, and automated retraining
- Experience with Python and ML frameworks such as scikit-learn, PyTorch, or Tensor Flow, and data engineering platforms such as Palantir, Databricks, Spark, and SQL, including batch and streaming pipelines
- Experience improving data quality, lineage, and observability in enterprise data environments
- Experience operationalizing rules and model-driven scoring for prioritization, routing, or case selection
- Experience with API-first and event-driven integration patterns, including secure service-to-service communication
- Experience working in Agile delivery environments, collaborating with product owners, SMEs, and engineering teams
- Knowledge of Responsible AI practices, including explainability, fairness, and bias assessment
- Ability to design and document architecture artifacts, data contracts, and operational runbooks
- Bachelor’s degree and 7+ years of experience with Dev Ops, software, or data engineering, or 10+ years of experience with Dev Ops, software, or data engineering in lieu of a degree
Nice If You Have:
- Experience with fraud detection, risk analytics, or case selection in government, tax, or financial domains
- Experience with Amazon Bedrock and integrating custom AI models into enterprise workflows
- Experience deploying ML solutions in AWS Gov Cloud or other regulated cloud environments
- Experience with federal ATO processes, continuous compliance, and operating systems under FISMA controls
- Experience in enterprise modernization programs such as cloud migration, microservices, API strategy, and Dev Sec Ops
- Knowledge of graph-based analytics and advanced anomaly detection techniques
- AWS Machine Learning Specialty, Security+, AI Engineer credentials, or similar Certification
Compensation
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