Note: The job is a remote job and is open to candidates in USA. Dice is seeking a Mid-Level AI/ML Engineer to support the design, deployment, and operation of production-grade AI systems. The role involves contributing to end-to-end model lifecycle engineering on Azure and building AI agents that translate safety signals into actionable decisions.
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
- 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
- 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
- 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
- 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
- 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
Skills
- 3+ years hands-on developing and deploying AI/ML models in production environments
- Proficient in Python, including packaging, testing, and performance optimization
- Understanding of algorithms, model selection, training/validation/optimization, and evaluation at scale
- Proficient in data preprocessing, feature engineering, and data visualization for decision support
- Proficient with PyTorch/TensorFlow and modern MLOps including deployment, monitoring, scaling, CI/CD, experiment tracking, and model registry
- Experience with Azure for AI/ML workloads, including Azure ML, Azure Synapse, and Azure Data Lake
- Experience developing AI agents in Copilot Studio and via Python frameworks
- Bachelor's degree or equivalent experience in Computer Science, Data Science, Mathematics, Statistics, Engineering, or related field
- 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
Company Overview