AI/ML Engineer — NLP & Document AI, Secret Clearance

Softek Enterprises LLC; Rockville (MD); On-site; USD 120,000 - 170,000; Full time

Job summary

Softek is seeking an AI/ML Engineer to develop and deploy models powering the Axiom multi-agent platform used by federal agencies to process millions of records. You will work on NLP and document understanding with cross-functional teams including data scientists, engineers, and government stakeholders.

Design, train, and deploy models, build ML pipelines, and optimize production performance while integrating AI into the platform. A focus on federal use cases and security clearance is required.

Qualifications

• 3+ years of experience in machine learning engineering.
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow, or scikit-learn).
• Experience deploying ML models in production cloud environments.
• Strong understanding of NLP and document understanding techniques.
• Ability to obtain and maintain a Secret clearance.

Responsibilities

• Design, train, and deploy machine learning models for document processing and NLP tasks.
• Build and maintain ML pipelines for data ingestion, feature engineering, and model serving.
• Optimize model performance for accuracy, latency, and cost in production environments.
• Integrate AI capabilities into the Axiom platform architecture.
• Evaluate new ML techniques and frameworks for applicability to federal use cases.
• Document model architectures, training procedures, and performance benchmarks.

Skills

ML engineering

Python

ML frameworks

Production cloud deployment

NLP & document understanding

Security clearance

MLflow / Kubeflow

Tools

Azure AI

AWS SageMaker

MLflow

Kubeflow

Job description

Softek is seeking an AI/ML Engineer to develop and deploy models powering the Axiom multi-agent platform used by federal agencies to process millions of records. You will work on NLP and document understanding with cross-functional teams including data scientists, engineers, and government stakeholders.

Design, train, and deploy models, build ML pipelines, and optimize production performance while integrating AI into the platform. A focus on federal use cases and security clearance is required.