Omm IT Solutions
Machine Learning Engineer
Please Note:
This is a 100% Onsite Position. Selected candidate must be willing to work on-site in Woodlawn, MD 5 days a week. 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:
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. Required Skills:
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. 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.?
Please Note:
This is a 100% Onsite Position. Selected candidate must be willing to work on-site in Woodlawn, MD 5 days a week. 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:
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. Required Skills:
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. 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.?