Senior Machine Learning Engineer

$101,400 - $183,300/Yr

Leidos - Remote, OR

posted 3 months ago

Full-time - Senior
Remote, OR
Professional, Scientific, and Technical Services

About the position

Leidos is seeking a Senior Machine Learning Engineer who will leverage their expertise in Artificial Intelligence (AI), Machine Learning (ML), and MLOps to create and implement repeatable workflows for building, training, testing, deploying, and monitoring trustworthy AI capabilities. This role is pivotal in developing solutions for both internal corporate research and client operational environments. The ideal candidate will possess a robust foundation in Machine Learning, experience with DevOps/MLOps tools and processes, and proficiency in Python programming. The position requires the ability to thrive in fast-paced, Agile development teams, collaborating effectively with both junior and senior engineers and researchers. In this role, you will be responsible for designing and implementing tools and processes that facilitate MLOps practices within a scalable cloud infrastructure. You will also design, build, train, and evaluate Machine Learning models, ensuring the creation of repeatable Machine Learning pipelines for model training, evaluation, deployment, and monitoring. Additionally, you will engage in research and development to enhance AI observability and manage cloud resources essential for MLOps infrastructure. Working closely with a team of AI/ML researchers and engineers, you will utilize Agile development methodologies to drive project success. To excel in this position, you should be highly motivated and collaborative, demonstrating the ability to work independently while also contributing to team efforts. Effective documentation of your work and the ability to communicate research and development plans, progress, and results are crucial for success in this role.

Responsibilities

  • Design and implement tools and processes to enable MLOps practices in a scalable cloud infrastructure
  • Design, build, train, and evaluate Machine Learning models
  • Build repeatable Machine Learning pipelines for model training, evaluation, deployment, and monitoring
  • Perform R&D to enable AI Observability
  • Design, implement, and manage cloud resources for MLOps infrastructure
  • Work in a team of AI/ML researchers and engineers using Agile development processes

Requirements

  • Bachelor's degree with 8 years of experience or Master's degree with 6 years of experience in Computer Science, Machine Learning, Artificial Intelligence, or related discipline
  • Practical, hands-on experience with developing machine learning algorithms & models, visualizations, web apps
  • Advanced Python programming skills
  • Experience with AI/ML tools, such as common python packages (e.g., scikit-learn, TensorFlow, PyTorch) and Jupyter notebooks
  • Experience with MLOps tools and frameworks, such as Kubeflow, MLflow, DVC, TensorBoard
  • Experience with Software Development tools, including Git, containerization technologies (e.g., Docker), CI/CD frameworks
  • Strong communication skills
  • Competence in troubleshooting and mitigating issues with prototyped and deployed AI
  • Demonstrated ability to orchestrate a ML pipeline

Nice-to-haves

  • Experience with AI/ML across a broad range of application domains (e.g., NLP, Computer Vision, time series analysis)
  • Experience deploying and using AI Explainability and Monitoring tools
  • Experience deploying, managing, and using Kubernetes and Kubeflow clusters
  • Experience using Infrastructure-as-Code tools (e.g., Terraform, Ansible, CloudFormation)
  • Experience deploying, configuring, and managing DevOps tools (e.g., GitLab, Nexus)
  • Ability and willingness to obtain a Top Secret security clearance
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