Senior Machine Learning Engineer - Arlington, United States - Leidos Inc

Description

Description

Looking for the opportunity to work on problems that matter, with colleagues that share your interest and expertise in applied Artificial Intelligence and Machine Learning?

Leidos is looking for a Senior Machine Learning Engineer to apply their expertise in Artificial Intelligence, Machine Learning, and MLOps to develop repeatable workflows that build, train, test, deploy, and monitor trustworthy AI capabilities. The Machine Learning Engineer will create solutions for internal and corporate research and client's operational environments. This role requires a strong foundation in Machine Learning, experience with DevOps/MLOps tools and processes, Python programming experience, and the ability to work in fast-paced, Agile development teams.

To be successful in this role, you should be highly motivated and collaborative, working well independently and within a team of junior and senior engineers & researchers. You should be effective and documenting your work and comfortable creating and communicating R&D plans, progress, and results.

Primary 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

Basic Qualifications

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

Preferred Qualifications

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

Original Posting Date:

While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

The Leidos pay range for this job level is a general guideline onlyand not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.