Senior AI/ML Operations Engineer

 Please note that this role is contingent upon a contract award. While it is not an immediate opening, we are actively conducting interviews and extending offers in anticipation of the award.  

Job Description

We are seeking an AI/ML Ops Engineer who is passionate about transforming AI/ML capabilities, especially Natural Language Processing (NLP) and Large Language Models (LLMs/Generative AI), into tangible, high-value features within modern software systems. This role will support a major data migration initiative with the Department of Transportation which involves transitioning from a legacy Oracle-based system to a modern data analytics platform, integrating dozens of data sources and thousands of reports. This position requires strong MLOps expertise, technical curiosity, and the ability to engage directly with clients, data scientists, and engineers.

You will focus on automating the deployment, integration, and operationalization of AI capabilities, working with pre-trained and custom models to ensure they are seamlessly embedded into production systems for measurable business and user impact. This includes designing and managing scalable AI/ML pipelines, integrating models with cloud-native platforms, and ensuring solutions remain reliable, explainable, and continuously optimized.

Job Location: This position is remote. Travel to the metropolitan DC area may be required for critical client meetings.  

This position requires that the job be performed in the United States. If you accept this position, note that ICF monitors employee work locations, blocks access from foreign locations/foreign IP addresses, and prohibits personal VPN connections. 

What you’ll be doing:

• Participate in client and stakeholder sessions to identify automation opportunities and requirements for AI integration, focusing on practical deployment within existing and new systems.

• Implement AI-driven automation using a mix of pre-trained and fine-tuned models, including NLP and LLM-based solutions, for tasks such as text generation, summarization, classification, and conversational interfaces.

• Work with data scientists and developers to package and deploy AI capabilities via CI/CD pipelines and container orchestration tools.

• Integrate cloud-hosted AI/ML services (AWS SageMaker, Azure ML, GCP Vertex AI, OpenAI, Azure OpenAI) into production systems with security, scalability, and compliance in mind.

• Apply AI-augmented coding best practices to accelerate development cycles and improve code quality through intelligent tooling and automated testing.

• Automate AI workflows for ingestion, inference, retraining, and performance optimization, ensuring sustained business value.

• Implement monitoring solutions for AI feature performance, including drift detection and usage analytics, with triggers for updates or recalibration.

• Collaborate with software engineers and DevOps teams to ensure seamless integration of AI services into broader platform architecture.
   

What you must have:

• Bachelor’s degree (e.g., Computer Science, Data Engineering, AI/ML, or related discipline).

• 3+ years of experience in AI/ML operations, AI automation, or integrating AI capabilities into production systems.

• 3+ years of experience working with Natural Language Processing tools, APIs, or frameworks (spaCy, Hugging Face Transformers, OpenAI API, Azure OpenAI).

• 2+ years of experience with Large Language Models (Generative AI) and their application in real-world software solutions.

• 2+ years building and maintaining CI/CD pipelines (e.g., GitHub Actions, Jenkins, Azure DevOps, GitLab CI).

• 3+ years of experience in Python for integrating and orchestrating AI services; familiarity with MLflow, Kubeflow, or similar frameworks a plus.

• 3+ years of experience in cloud-native ML/AI platforms (AWS SageMaker, Azure ML, GCP Vertex AI) and containerization/orchestration (Docker, Kubernetes).

• US Citizen or Permanent Lawful Resident (Green Card Holder) preferred.

• Employment must be compliant with eligibility for Public Trust Clearance due to Government Contract.

Technologies you’ll use:

• Programming & AI: Python, R, TensorFlow, PyTorch, scikit-learn, Hugging Face, spaCy

• MLOps/Automation: MLflow, Kubeflow, Airflow, Prefect

• Cloud AI Services: AWS SageMaker, Azure ML, Azure OpenAI, GCP Vertex AI, OpenAI API

• DevOps: Docker, Kubernetes, Terraform, Jenkins, GitHub Actions

• Data Engineering: SQL, Spark, Databricks, Kafka

• Collaboration: Confluence, Jira, SharePoint, Mu