Senior NLP ML Engineer — Production Pipelines

Protagonist; Washington (District of Columbia); On-site; USD 95,000 - 141,000; Full time

Job summary

Protagonist is seeking a Senior Machine Learning Engineer to build production-ready systems for mission-critical work. You will own the full ML lifecycle from design to deployment, applying strong discipline and systems thinking to scalable, well-architected solutions.

You’ll collaborate across engineering, product, and client-facing teams to push AI capabilities forward, stay current with ML advances, and deliver impact while ensuring GovCloud/ITAR compliance.

Qualifications

• U.S. person eligible to work on government contracts; active or prior SECRET clearance preferred.
• Bachelor’s degree and 5+ years of experience, or Master’s degree with 3+ years in CS/ML or related field.
• Proven track record deploying production ML systems with deep NLP expertise (transformers, LLMs).
• Strong Python skills and fluency with PyTorch and the Hugging Face ecosystem.

Responsibilities

• Identify high-impact NLP use cases with product and engineering teams.
• Own production NLP pipelines: narrative detection, NER, span classification, stance analysis.
• Design and operate ML workflows using Metaflow, Argo, and Kubernetes at scale.
• Develop LLM-powered features on AWS Bedrock within GovCloud/ITAR constraints.
• Fine-tune transformer models for domain-specific content.
• Establish ML evaluation frameworks and success criteria with PMs.
• Integrate ML services into Django/PostgreSQL platform and Kafka/OpenSearch.
• Mentor team members and advance ML best practices.

Skills

Python

PyTorch

Hugging Face

Kubernetes

Docker

Terraform

CI/CD

NLP

LLMs

AWS

Education

Bachelor's in Computer Science or ML

Master's in Computer Science or ML

Tools

Metaflow

Argo Workflows

MLflow

OpenSearch

Job description

Protagonist is seeking a Senior Machine Learning Engineer to build production-ready systems for mission-critical work. You will own the full ML lifecycle from design to deployment, applying strong discipline and systems thinking to scalable, well-architected solutions.

You’ll collaborate across engineering, product, and client-facing teams to push AI capabilities forward, stay current with ML advances, and deliver impact while ensuring GovCloud/ITAR compliance.