AI/ML Engineer- Mid-Level-2X

Key Responsibilities

• Build & Ship Production Models
• Implement and productionize ML solutions (supervised/unsupervised, NLP, deep learning) with robust data preprocessing, feature engineering, and evaluation pipelines.
• Support model selection, training, validation, optimization, and calibration, ensuring reliability, fairness, and performance at scale.
• MLOps Lifecycle (Azure)
• Establish MLOps workflows including CI/CD for ML, experiment tracking, model registry, and reproducible builds and deployments.
• Implement model monitoring (drift, data/feature quality, bias, and business KPIs), alerting, and automated rollback.
• Data Engineering for ML
• Design high-quality data pipelines (ingest, transform, validate) across structured and unstructured sources; enforce data contracts and lineage.
• Partner with analytics teams to make datasets discoverable, documented, and performant for iterative model development.
• AI Agents & Copilot Integration
• Build AI agents that operationalize safety analytics (Copilot Studio, Python agents, retrieval pipelines) to accelerate triage and decision flow.
• Integrate agents with APIs, event streams, dashboards, and case management systems.
• Engineering Excellence & Governance
• Champion secure-by-design practices, reproducibility, and auditability including model cards, data sheets, and deployment records.
• Contribute to coding standards and code reviews; support knowledge sharing across the team.
• Agile Collaboration & Impact
• Work in Agile teams; drive iterative delivery, joint problem-solving, and continuous improvement.
• Translate mission goals into technical contributions aligned with Sentinel time-to-intervention targets.

Required Qualifications

• Experience: 3+ years hands-on developing and deploying AI/ML models in production environments.
• Programming: Proficient in Python, including packaging, testing, and performance optimization.
• ML Expertise: Understanding of algorithms, model selection, training/validation/optimization, and evaluation at scale.
• Data Skills: Proficient in data preprocessing, feature engineering, and data visualization for decision support.
• Deep Learning & MLOps: Proficient with PyTorch/TensorFlow and modern MLOps including deployment, monitoring, scaling, CI/CD, experiment tracking, and model registry.
• Cloud: Experience with Azure for AI/ML workloads, including Azure ML, Azure Synapse, and Azure Data Lake.
• AI Agents: Experience developing AI agents in Copilot Studio and via Python frameworks.
• Educational Background: Bachelor's degree or equivalent experience in Computer Science, Data Science, Mathematics, Statistics, Engineering, or related field.

Preferred Qualifications

• Experience with streaming/event-driven architectures (Event Hubs), feature stores, and vector databases for retrieval augmented generation (RAG).
• Hands-on with responsible AI including fairness, explainability, privacy, model governance, and security in cloud ML.
• Familiarity with domain-specific risk analytics and public sector or regulated environments.
• Certifications in Azure AI/ML and/or MLOps.

Other Qualifications

• Strong analytical and problem-solving skills, with the ability to break down complex processes and design effective solutions.
• Excellent communication skills, able to translate complex technical concepts for diverse audiences.
• Demonstrated eagerness to learn and adopt new technologies, while actively sharing knowledge with the team.
• Must be able to pass a federal agency background check and obtain a government-issued ID badge prior to starting work.