Omm IT Solutions
Job Description
Please Note:
This is a 100% Onsite position and 5 days a week
Selected candidate must be willing to work on-site in Woodlawn, MD
Key Required Skills:
Machine Learning, ML model deployment, Python, CI/CD for ML (Jenkins, Sagemaker), Cloud Platforms (AWS) and related ML services, and data pipeline management. 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. Requirements
Skills Requirements:
Basic Qualifications
Bachelor's Degree and 12+ 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 workflows and data pipelines Must be able to obtain and maintain a Public Trust. Contract requirement. Required Skills
Strong foundation AI, ML and LLMs 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 MLOps principles and experience with MLOps platforms and tools (e.g., AWS Sagemaker, MLflow, Kubeflow, DataRobot). Experience with CI/CD tools (Jenkins required), and containerization (Docker) and orchestration (Kubernetes) for managing and scaling applications. Proficiency with cloud platforms (AWS preferred) including ML services, Infrastructure as Code (CloudFormation, Terraform), compute, storage (S3, EFS), and networking. Knowledge of data engineering fundamentals including understanding of data pipelines, data storage (PostgreSQL, MySQL, MongoDB), and data processing frameworks (Apache Spark). Strong communication, collaboration, problem-solving, analytical, and critical thinking skills. Desired 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.
Machine Learning, ML model deployment, Python, CI/CD for ML (Jenkins, Sagemaker), Cloud Platforms (AWS) and related ML services, and data pipeline management. 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. Requirements
Skills Requirements:
Basic Qualifications
Bachelor's Degree and 12+ 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 workflows and data pipelines Must be able to obtain and maintain a Public Trust. Contract requirement. Required Skills
Strong foundation AI, ML and LLMs 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 MLOps principles and experience with MLOps platforms and tools (e.g., AWS Sagemaker, MLflow, Kubeflow, DataRobot). Experience with CI/CD tools (Jenkins required), and containerization (Docker) and orchestration (Kubernetes) for managing and scaling applications. Proficiency with cloud platforms (AWS preferred) including ML services, Infrastructure as Code (CloudFormation, Terraform), compute, storage (S3, EFS), and networking. Knowledge of data engineering fundamentals including understanding of data pipelines, data storage (PostgreSQL, MySQL, MongoDB), and data processing frameworks (Apache Spark). Strong communication, collaboration, problem-solving, analytical, and critical thinking skills. Desired 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.