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Senior AI/ML Engineer
Zyxware TechnologiesUnited States🇺🇸United StatesPosted 8 Jul 2026
Quick Overview
Work Type
Remote
Level
Mid Senior
Job Description
Role: Senior AI/ML Engineer
Location: Fully Remote
Duration: Full Time
Job Description
As a Senior AI/ML Engineer , you will lead the design, deployment, and operation of production- grade AI systems . Sentinel model — protecting more consumers, faster, from more hazards by
using analytics to shorten time to intervention. You will own end-to-end model lifecycle engineering on Azure, advance MLOps best practices, and build AI agents using Copilot Studio and Python frameworks that translate signals into timely, actionable decisions. This role offers a high-impact opportunity to apply advanced AI/ML expertise in a federal mission environment, directly improving public safety outcomes.
Key Responsibilities
Build & Ship Production Models
• Architect, implement, and productionize ML solutions (supervised/unsupervised, NLP, deep learning) with robust data preprocessing, feature engineering, and evaluation pipelines.
• Lead model selection, training, validation, optimization, and calibration, ensuring reliability, fairness, and performance at scale.
Own the 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 to keep systems safe and responsive.
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 to reduce cycle time from signal to action.
Engineering Excellence & Governance
• Champion secure-by-design practices, reproducibility, and auditability including model cards, data sheets, and deployment records.
• Contribute to coding standards, code reviews, and knowledge sharing; mentor engineers and data scientists.
Agile Collaboration & Impact
• Work in Agile teams; drive iterative delivery, joint problem-solving, and continuous improvement.
• Translate mission goals into technical roadmaps and measurable outcomes tied to Sentinel time-to-intervention targets.
Required Qualifications
• Experience: 5+ years hands-on developing and deploying AI/ML models in productionenvironments.
• Programming: Expert in Python, including packaging, testing, and performance optimization.
• ML Expertise: Deep understanding of algorithms, model selection,training/validation/optimization, and evaluation at scale.
• Data Skills: Expert in data preprocessing, feature engineering, and data visualization for decision support.
• Deep Learning & MLOps: Expert with PyTorch/TensorFlow and modern MLOps including deployment, monitoring, scaling, CI/CD, experiment tracking, and model registry.
• Cloud: Proven 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 frameworksincluding tooling, orchestration, retrieval, and connectors.
• Education: PhD, Master''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, andvector databases for retrieval augmented generation (RAG).
• Hands-on with responsible AI including fairness, explainability, privacy, model governance (model cards, audits), 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 diversetechnical and non-technical audiences.
• Highly organized, detail-oriented, and proactive; capable of working independently with minimal supervision.
• Must be able to pass a federal agency background check and obtain a government-issued ID badge prior to starting work.
• Public sector consulting experience is a plus.
Location: Fully Remote
Duration: Full Time
Job Description
As a Senior AI/ML Engineer , you will lead the design, deployment, and operation of production- grade AI systems . Sentinel model — protecting more consumers, faster, from more hazards by
using analytics to shorten time to intervention. You will own end-to-end model lifecycle engineering on Azure, advance MLOps best practices, and build AI agents using Copilot Studio and Python frameworks that translate signals into timely, actionable decisions. This role offers a high-impact opportunity to apply advanced AI/ML expertise in a federal mission environment, directly improving public safety outcomes.
Key Responsibilities
Build & Ship Production Models
• Architect, implement, and productionize ML solutions (supervised/unsupervised, NLP, deep learning) with robust data preprocessing, feature engineering, and evaluation pipelines.
• Lead model selection, training, validation, optimization, and calibration, ensuring reliability, fairness, and performance at scale.
Own the 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 to keep systems safe and responsive.
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 to reduce cycle time from signal to action.
Engineering Excellence & Governance
• Champion secure-by-design practices, reproducibility, and auditability including model cards, data sheets, and deployment records.
• Contribute to coding standards, code reviews, and knowledge sharing; mentor engineers and data scientists.
Agile Collaboration & Impact
• Work in Agile teams; drive iterative delivery, joint problem-solving, and continuous improvement.
• Translate mission goals into technical roadmaps and measurable outcomes tied to Sentinel time-to-intervention targets.
Required Qualifications
• Experience: 5+ years hands-on developing and deploying AI/ML models in productionenvironments.
• Programming: Expert in Python, including packaging, testing, and performance optimization.
• ML Expertise: Deep understanding of algorithms, model selection,training/validation/optimization, and evaluation at scale.
• Data Skills: Expert in data preprocessing, feature engineering, and data visualization for decision support.
• Deep Learning & MLOps: Expert with PyTorch/TensorFlow and modern MLOps including deployment, monitoring, scaling, CI/CD, experiment tracking, and model registry.
• Cloud: Proven 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 frameworksincluding tooling, orchestration, retrieval, and connectors.
• Education: PhD, Master''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, andvector databases for retrieval augmented generation (RAG).
• Hands-on with responsible AI including fairness, explainability, privacy, model governance (model cards, audits), 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 diversetechnical and non-technical audiences.
• Highly organized, detail-oriented, and proactive; capable of working independently with minimal supervision.
• Must be able to pass a federal agency background check and obtain a government-issued ID badge prior to starting work.
• Public sector consulting experience is a plus.
Skills
MLOps
NLP
Agile
Azure
Deep Learning
PyTorch
Python
SAFe
TensorFlow
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