AI/ML Software Engineer
BT-158 – AI/ML Software Engineer
Location: Dulles (fully on-site, no remote option)
**MUST HAVE A POLY CLEARANCE TO APPLY. Those without a Poly clearance will not be considered.**
Bespoke Technologies is seeking a Software Engineer/Developer with expertise in Python object-oriented development, and systems skills (i.e. Cloud and containers). The ideal candidate will have the expertise, creativity, and leadership to drive innovative solutions that apply advanced AI techniques to solve complex problems. This is an opportunity to make a tangible impact by leveraging cutting-edge technology, data, and a deep understanding of mission-driven challenges. In this role, you will:- Work closely with teammates and stakeholders in a Lean Agile environment to build mission-critical applications focused on data discovery and analysis
- Participate in code reviews, system design discussions, and continuous improvement initiatives
- Leverage modern build tools, testing frameworks, and CI/CD pipelines to ensure quality and delivery speed
- Build and deploy machine learning models using containerization and cloud services
- Design and maintain data pipelines and model-serving infrastructure
- Monitor model performance and ensure reliability in production environments
- Collaborate with cross-functional teams to deliver end-to-end ML solutions
- Experience with source control (e.g. Git) and CI/CD pipeline tools such as AWS CodeBuild (preferred), Jenkins, GitLab CI, or GitHub Actions
- Strong Python development skills with experience in ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch)
- Experience deploying models with tools like Docker, Kubernetes, and cloud ML services
- Ability to manage structured and unstructured data using SQL and scripting tools
- Effective written and verbal communication skills necessary to perform job duties and collaborate with team members
- Familiarity with monitoring and observability stacks such as Prometheus/Grafana (preferred), CloudWatch, or ELK/EFK
- Experience designing and implementing scalable, maintainable, and OOP based software in a containerized cloud environment (AWS preferred) leveraging foundational services for computing, identity management, and networking.
- Contributions to open-source libraries or community projects or personal projects
- Hands-on experience with MLOps tools such as MLflow, SageMaker, or Kubeflow
- Experience integrating models into software applications via APIs
- Understanding of model governance, versioning, and interpretability practices
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