Key Required Skills:
Machine Learning, Python, NoSQL and Relational Databases, DevOps, CI/CD, and Cloud Platforms (AWS, Azure) and related ML services. |
Position Description:
- Ensure that ML models can be effectively developed, deployed, managed, and monitored in Production environments.
- Productionize ML models integrate trained ML models with Production systems
- Build and manage ML pipelines design, build, and maintain automated pipelines including data ingestion, data preprocessing, model training, validation, and deployment utilizing CI/CD practices.
- Infrastructure management set up and manage infrastructure for ML workloads utilizing cloud platforms and containerization technologies.
- Monitoring and alerting implement monitoring systems to track performance of ML models in Production
- Automation automate various tasks within the ML workflow to improve efficiency and reproducibility
- Performance optimization identify ways to optimize the performance, efficiency, and scalability of ML models and their supporting infrastructure
- All other duties as assigned or directed.
|
Skills Requirements:
FOUNDATION FOR SUCCESS (Basic Qualifications) - Bachelor's Degree and 10+ years experience in Computer Science, Mathematics, Engineering or a related field.
- Masters or Doctorate degree may substitute for required experience
- Minimum 5 years of hands-on experience designing, developing, implementing and maintaining ML pipelines
- Must be able to obtain and maintain a Public Trust. Contract requirement.
*** Selected candidate must be willing to work on-site in Woodlawn, MD 5 days a week. FACTORS TO HELP YOU SHINE (Required Skills) These skills will help you succeed in this position: - Strong foundation in Machine Learning including understanding of concepts, algorithms, model training and frameworks (TensorFlow, PyTorch, scikit-learn).
- Strong programming skills, especially Python, and relevant libraries (scikit-Learn, TensorFlow, PyTorch, NumPy, Pandas).
- Strong understanding of DevOps principles and experience with CI/CD tools (Jenkins, GitHub Actions, Gitlab CI/CD, etc.)
- Proficiency with cloud platforms (AWS preferred) including ML services, compute, storage (S3, EFS), and networking.
- Experience with containerization (Docker) and orchestration (Kubernetes).
- Knowledge of data engineering fundamentals including understanding of data pipelines, data storage (PostgreSQL, MySQL, MongoDB), and data processing frameworks (Apache Spark).
- Familiarity with MLOps platforms and tools (e.g., Sagemaker, MLflow, Kubeflow, DataRobot).
- Strong communication, collaboration, problem-solving, analytical, and critical thinking skills.
HOW TO STAND OUT FROM THE CROWD (Desired Skills) Showcase your knowledge of modern development through the following experience or skills: - Prior experience with federal or state government IT projects.
- Ability to design scalable, reliable, and efficient ML systems.
- Willingness to continuously learn new technologies and best practices.
- Familiarity with other programming languages such as Java and Scala.
- Experience with Natural Language Processing (NLP) for text and language generation.
|