Responsibilities
- Design, develop, train, and optimize machine learning and deep learning models supporting predictive analytics, classification, anomaly detection, NLP, and AI-assisted decision support.
- Apply advanced ML techniques using supervised, unsupervised, and semi-supervised learning approaches.
- Design and implement end-to-end MLOps pipelines supporting model training, validation, versioning, deployment, and rollback.
- Deploy models into production environments using Microsoft Azure ML, containerization, and CI/CD pipelines.
- Implement model monitoring, performance tracking, and drift detection to ensure long-term reliability and accuracy.
- Build and maintain AI solutions leveraging Microsoft Azure services, including:
- Azure Machine Learning
- Azure Data Lake Storage
- Azure Synapse Analytics
- Integrate AI/ML solutions with existing data platforms, APIs, and analytics services.
- Optimize AI workloads for cost, performance, and reliability in cloud environments.
- Ensure AI systems adhere to federal standards for responsible AI, transparency, explainability, and auditability.
- Support model documentation, validation artifacts, and compliance reporting.
- Collaborate with governance and stakeholder teams to ensure models are suitable for high-impact decision-making.
- Work closely with data scientists, data engineers, analysts, architects, and Agile project managers in a fast-paced Agile delivery environment.
- Mentor junior engineers and contribute to shared engineering standards and best practices.
- Minimum of 5+ years of experience designing, deploying, and operating production AI/ML systems.
- Demonstrated experience moving models from research or prototype stages into production environments.
- Proven experience supporting AI systems in mission-critical or regulated settings.
- Bachelor's Degree in Computer Science, Machine Learning, Data Science, Engineering, or a related field — or equivalent professional experience.
- Experience supporting federal, public-sector, or other regulated environments.
- Expert proficiency in Python and AI/ML frameworks such as PyTorch and/or TensorFlow.
- Strong experience with machine learning libraries including Scikit-learn, NumPy, and Pandas.
- Hands-on experience with Microsoft Azure AI/ML services, particularly Azure Machine Learning.
- Experience building CI/CD pipelines for ML workflows.
- Familiarity with containerization (Docker) and model deployment patterns.
- Experience with SQL and data integration for ML workloads.
- Proficiency with Git-based version control and collaborative development.
- Strong written and verbal communication skills.
- Ability to explain complex AI/ML concepts to technical and non-technical stakeholders.
- Proven ability to lead technical efforts and collaborate across multidisciplinary teams.
Preferred qualifications
- Master's or Ph.D. in Computer Science, Machine Learning, Data Science, Engineering, or a related field — or equivalent professional experience.
- Familiarity with AI agents, vector databases, large language models (LLMs), or Copilot-style architectures.
- Azure certifications (AI Engineer, Data Scientist, or related).
- Experience with streaming or near-real-time AI pipelines.
- Real opportunity for career growth in an environment where your achievements will be celebrated
- Constant collaboration with numerous teams to ensure client success
- A team that respects and embraces your ideas and expertise
- Coworkers that are motivated by pursuing excellence, rather than the prospect of personal gain
- A workplace dedicated to supporting and bettering public safety and government agencies
Benefits
- Very competitive salary based on qualifications and experience
- Comprehensive, Company paid healthcare for you (We pay your premiums and deductibles)
- 401(k) with company match
- Travel & performance incentives
- 3 weeks paid time off (plus Federal Holidays)
- $5K annual training allowance
- $500 book allowance
Tags & focus areas
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