MLOps Engineer

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 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.
• Automation automate various tasks within the ML workflow to improve efficiency and reproducibility.

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.

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.

Education:

• Bachelor's Degree and 10+ years experience in Computer Science, Mathematics, Engineering or a related field.
• Must be able to obtain and maintain a Public Trust. Contract requirement.