SENIOR SOFTWARE ENGINEER - DATA SCIENCE PLATFORM

Huntington Ingalls•Newport News, VA

5d•Hybrid

About The Position

Design, develop, and test operating systems-level software, compilers, and network distribution software. Set operational specifications, and formulate and analyze software requirements. May design embedded systems software. We are seeking a Senior Software Engineer to join our Data Science team and play a key role in building and maintaining software solutions that enable machine learning at scale. In this role, you will design and develop robust, production-grade systems that integrate with ML Ops workflows, ensuring models and data pipelines are reliable, secure, and efficient. You will collaborate closely with data scientists, ML engineers, and DevOps professionals to deliver high-quality software that supports the entire machine learning lifecycle. Your work will enable advanced analytics and AI-driven insights that support critical business decisions and innovation across the organization

Requirements

Bachelor's Degree and 9 years of relevant exempt experience; Master's Degree and 7 years of relevant professional experience; Ph.D. and 4 years of experience.
Bachelor’s degree in Computer Science, Software Engineering, or related field.
9 years of experience in software engineering with a focus on backend or systems development.
Strong proficiency in programming languages such as Python, Java, or C++.
Experience with containerization and orchestration (Docker, Kubernetes).
Familiarity with cloud platforms (AWS, Azure, GCP).
Knowledge of CI/CD pipelines and version control systems (Git).
Solid understanding of software architecture, design patterns, and API development.

Nice To Haves

Experience supporting ML Ops workflows and machine learning deployments.
Familiarity with ML frameworks (TensorFlow, PyTorch) and ML Ops tools (MLflow, Kubeflow, Airflow).
Knowledge of distributed systems and large-scale data processing (Spark, Hadoop).
Strong background in building microservices and RESTful APIs.
Experience with security and compliance in cloud-based environments.
Ability to work collaboratively in a fast-paced, cross-functional environment.

Responsibilities

Designing and implementing scalable software solutions for ML pipelines and data workflows.
Developing APIs and services to support model deployment and monitoring.
Building tools and frameworks that improve automation and reproducibility in ML Ops environments.
Ensuring software quality through testing, code reviews, and best practices.
Collaborating with cross-functional teams to optimize performance and reliability.