Expert ML Software Engineer
Core
Design, build, and maintain ML systems that learn from data to automate decision-making, such as predictive models, recommendation engines, or anomaly detection systems.
Role type
Senior IC ML Software Engineer (MLOps & Backend)
Builds
Production ML systems, APIs, and backend services for national security applications
Domain
National Security / Defense / Machine Learning
Deliverable
production ML models
Required skills
Kubernetes programming, Python, Backend Development (API design, database integration, Docker), MLOps tooling (MLflow, Kubeflow, Argo Workflows, Airflow), ML algorithms (supervised/unsupervised learning, neural networks, NLP), Data Engineering (cleaning, feature engineering), Math & Statistics (linear algebra, probability, calculus)
Preferred skills
Low-latency inference serving (vLLM, TGI, NVIDIA Triton), GPU orchestration (NVIDIA Run:ai, KAI Scheduler, Kueue), Cloud & CI/CD DevOps (AWS, Azure, GCP, SageMaker, Vertex AI)
Technologies
FastAPI, Flask, Django, PyTorch, TensorFlow, scikit-learn, pandas, NumPy, Git, Linux, REST APIs, Kubernetes, Docker, MLflow, Kubeflow, Argo Workflows, Airflow, vLLM, TGI, NVIDIA Triton, NVIDIA Run:ai, KAI Scheduler, Kueue, Volcano, Slurm, AWS, Azure, Google Cloud, SageMaker, Vertex AI
Responsibilities
Create and train ML models for classification, regression, forecasting, or deep learning; Build end-to-end ML pipelines for data preprocessing, feature engineering, model training, and evaluation; Deploy models as APIs or backend services; Track model performance, detect drift, and retrain with new data; Connect ML systems to applications, databases, and cloud platforms
Seniority
Senior, hands-on IC