Senior Machine Learning Engineer

Protagonist•Washington, DC

7d•$95,000 - $141,000

About The Position

Protagonist is looking for a Senior Machine Learning Engineer who builds production-ready systems for mission-critical work. This role requires strong engineering discipline, systems thinking, and a bias toward scalable, well-architected solutions, owning the full ML lifecycle from design to deployment. The engineer will act as a builder and strategic partner across engineering, product, and client-facing teams, expanding what AI can do at Protagonist. The ideal candidate stays curious and current with advances in ML, infrastructure, and software development.

Requirements

U.S. person eligible to work on government contracts; active or prior SECRET clearance preferred
Bachelor’s and 5 years of experience, or master’s degree and 3 years of experience, in Computer Science, Machine Learning, or a related technical field
Proven track record building and deploying production ML systems, with deep NLP expertise (transformers, LLMs, embedding models)
Strong Python skills and fluency with PyTorch and the Hugging Face ecosystem
Hands-on experience with AWS (GovCloud experience a strong plus), Kubernetes, Docker, Terraform, and CI/CD pipelines
Experience with ML orchestration and experiment tracking (e.g., Metaflow, Argo Workflows, MLflow, or similar)
Experience with vector search and document indexing (OpenSearch/Elasticsearch or similar)
Experience building LLM applications, RAG, agents, prompt engineering, and evaluation
Skilled at scaling ML for multi-modal (text, image, video) and domain-specific applications, and working effectively across engineering, product, and business teams

Nice To Haves

Experience integrating ML into full-stack products (Django/REST APIs, React frontends) or decision-support tools
Experience operating in compliance-constrained environments
Strong communicator and cross-functional collaborator
Self-starter who thrives in ambiguity and startup-like environments

Responsibilities

Partner with product, engineering, and data science teams to identify high-impact NLP use cases and turn business needs into ML solutions that deliver measurable value
Own production NLP pipelines spanning narrative detection, NER, span classification, stance and characterization analysis, event extraction, deduplication, and knowledge-base entity linking over multi-language, noisy real-world text
Design, build, and operate production NLP pipelines, narrative detection, event classification, entity resolution and linking, deduplication — over multi-language, noisy real-world text at scale
Build and maintain ML workflows in Metaflow orchestrated on Argo Workflows and Kubernetes (EKS), including GPU-accelerated training and batch inference
Develop LLM-powered features on AWS Bedrock: RAG pipelines with vector search on OpenSearch, tool-using agents, and document-analysis workflows — within GovCloud/ITAR constraints
Fine-tune and deploy transformer models (classification, embeddings, entity linking) for domain-specific and foreign-language content
Establish ML evaluation frameworks regression testing, hallucination detection, quality metrics and define success criteria with product managers
Integrate ML services into our Django/PostgreSQL platform and event-driven infrastructure (Kafka, Redis, OpenSearch)
Lead technical discussions to align cross-functional teams on ML strategy, architecture, and implementation
Mentor others, share knowledge, and help evolve ML practices—balancing innovation with practical delivery