Expert ML Software Engineer

About the Role

We are searching for a machine learning (ML) engineer in support of our customer in Springfield, VA. This onsite role combines software engineering and machine learning expertise to design, build, and maintain ML systems that learn from data to automate decision-making, such as predictive models, recommendation engines, or anomaly detection systems.

Responsibilities

• Model Development: Create and train ML models for classification, regression, forecasting, or deep learning.
• Pipeline Design: Build end-to-end ML pipelines for data preprocessing, feature engineering, model training, and evaluation.
• Deployment: Deploy models as APIs or backend services using frameworks like FastAPI, Flask, or Django.
• Monitoring & Maintenance: Track model performance, detect drift, and retrain with new data.
• Integration: Connect ML systems to applications, databases, and cloud platforms.

Requirements

• US Citizen with a TS/SCI Clearance and ability to obtain a CI Polygraph.
• Bachelor’s Degree in a relevant field of study with 8 years of experience (or Master’s Degree with 6 years of experience).
• Expert experience in Kubernetes programming, with Python as the essential language, and proficiency in Git, Linux, and REST APIs.
• Expert experience in Backend Development, including API design, database integration, and containerization (Docker).
• Fundamental understanding of Math & Statistics, including linear algebra, probability, and/or calculus for ML theory.
• Experience with MLOps tooling and workflow orchestration, including experiment tracking and model registry (MLflow or equivalent), and pipeline orchestration on Kubernetes (Kubeflow, Argo Workflows, or Airflow) to support automated retraining, model versioning, and drift detection.
• Expert experience developing ML algorithms, including supervised/unsupervised learning, neural networks, and NLP, with hands-on expertise in at least one major framework (PyTorch or TensorFlow) and the broader Python ML stack (scikit-learn, pandas, NumPy).
• Expertise in Data Engineering, including data cleaning, feature engineering, and preventing data leakage.

Preferred Qualifications

• Experience serving models for low-latency inference at scale, including LLM serving frameworks (vLLM, TGI, or NVIDIA Triton Inference Server), GPU memory management, and batching/quantization tradeoffs.
• Experience with GPU orchestration and scheduling on Kubernetes in shared or multi-tenant clusters (NVIDIA Run:ai, KAI Scheduler, Kueue, Volcano, or Slurm).
• Expert experience with Cloud & CI/CD DevOps Pipelines, including AWS, Azure, Google Cloud ML services, SageMaker, and Vertex AI.

Pay

Virginia Pay Range: $150,000—$165,000 USD.

Benefits

• Robust health plan including medical, dental, and vision.
• Health Savings Account with company contribution.
• Annual Paid Time Off and Paid Holidays.
• Paid Parental Leave.
• 401k with generous company match.
• Training and Development Opportunities.
• Award Programs.
• Variety of Company Sponsored Events.

About GRVTY

The toughest national security challenges demand vision and ingenuity, not just resources. We deliver mission and technical expertise to outpace our adversaries. We’re purpose-built to tackle the most entrenched, systemic national security issues around the world. We partner with our customers to help them overcome challenges in every corner of technology and defense—including the ones still being explored. Our growing capabilities create complementary advantages, giving on-the-ground operations the edge they need to succeed. We muster everything we have to answer every challenge presented, every day.

At GRVTY, we believe that when our employees thrive, our company thrives. That’s why we offer a comprehensive and competitive benefits package designed to support your well-being, growth, and work-life balance.