BTI360 is a data discovery company using AI/ML to transform proprietary data into actionable insights. They are seeking a Senior Machine Learning Engineer to drive innovative solutions that apply advanced AI techniques to solve complex problems, making a tangible impact by leveraging cutting-edge technology, data, and a deep understanding of mission-driven challenges.
Requirements
- 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
- 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.
- Hands-on experience with MLOps tools such as MLflow, SageMaker, or Kubeflow
Responsibilities
- 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
Other
- Active TS/SCI with Polygraph
- Effective written and verbal communication skills necessary to perform job duties and collaborate with team members
- Contributions to open-source libraries or community projects or personal projects
- Experience integrating models into software applications via APIs
- Understanding of model governance, versioning, and interpretability practices
