Junior AI/ML Engineer

Responsibilities

• Create utilities and ensure seamless function of orchestration capabilities to support the AI/ML environment
• Develop and implement infrastructure for training, validating, and deploying machine learning models
• Create reusable components and libraries to accelerate AI/ML development and use of Generative AI capabilities
• Build model serving platforms for efficient inference
• Implement automated machine learning pipelines and MLOps practices for continuous integration and deployment (CI/CD) of models
• Implement version control for models and datasets, and develop robust testing frameworks for AI/ML components

Requirements

• Bachelor's degree in Computer Science, Statistics, Engineering or other related discipline
• 2+ years of experience
• 3+ years of software engineering experience with deep proficiency in Python
• Proven experience operationalizing Machine Learning models in production environments
• Familiarity with MLOps frameworks such as AWS SageMaker, MLflow, Kubeflow, or Airflow
• Expertise in scalable model serving platforms such as TensorFlow Serving, TorchServe, or ONNX runtime
• Advanced knowledge of cloud platforms (e.g., AWS, Azure, or GCP) and DevOps practices including Terraform or Helm

Preferred Qualifications

• Hands-on experience with Kubernetes and deploying containerized ML services
• Experience working with feature stores
• Experience utilizing Databricks or similar cloud-native ML tooling
• Experience working with feature stores and distributed data frameworks (e.g., Spark)
• Proficiency in model interpretation tools like SHAP or LIME
• Foundational understanding of linear algebra, calculus, and numerical computation to support algorithm optimization

Clearance Requirements

US Citizenship with a DoD Secret clearance.

Physical Requirements

Must be able to remain in a stationary position 50%. Frequently communicates with co-workers, management, and customers, which may involve delivering presentations.