Machine Learning Engineer

SAIC is seeking a qualified Machine Learning Engineer to join a dynamic team supporting the US Air Force Agency for Modeling and Simulation (AFMS) program. AFMS is the premier agency responsible for implementation, integration, and development of Modeling and Simulation (M&S) and training and analysis standards that support the US Air Force (USAF), Department of Defense (DoD), and mission partners requiring these capabilities to support the Warfighter in full-spectrum operations. The Machine Learning Engineer will facilitate this effort by working with subject matter experts to document and optimize the processes associated with this effort.

This role is 100% remote!

Responsibilities:

• Perform analysis and provide recommendations pertaining to proposed AI/ML architecture designs and proposals.
• Participate in the daily stand-ups and be an active member of an Agile/Scrum team.
• Apply development expertise towards solving complex problems through the application of Machine Learning.
• Collaborate and provide expertise in the design and development of Machine Learning based solutions. Support integration of Machine Learning solutions through containerization, client interface, database and middleware.
• Document all Machine Learning software designs, which may include context diagrams, data flow diagrams, software module description, etc.
• Provide Tier 3 / 4 engineering support, as needed, for solutions deployed to production.

Required Education, Experience, and Certifications:

• Bachelor’s Degree in technical discipline and 9+ of related experience; a Master’s Degree in technical discipline and 7+ years of related experience required; 4+ years of related experience can be substituted in lieu of education.
• Must be a US Citizen and hold an interim or active Secret Clearance
• Must possess or be able to obtain, within 60 days, a DoD 8570 IAT Level II (CCNA-Security, CySA, GICSP, GSEC, Security+ CE, CND, SSCP,)

Required Skills: 

• Developing Python programming packages and code to include REST APIs and microservices.
• Utilizing machine learning techniques including natural language processing and computer vision.
• Using Linux flavored operating systems and with automating workflows using Bash scripting.
• Performing ETL of structure and unstructured data into pipelines to ensure it is ingested into downstream systems with accuracy, reliability, and consistency of scale.
• Modeling, structuring, cleaning, and conditioning data for multiple sources and in multiple different formats, languages, and encodings.
• Using Elasticsearch and Kibana technologies.
• Using code repositories such as Git.
• Delivering results to stakeholders through written documentation and oral briefings.
• Developing robust documentation for code, Python packages, and data science methodologies.
• Explaining complex technical issues in graphical, verbal, or written formats. 

Desired Skills

• Demonstrated experience with cloud services, such as AWS.
• Demonstrated experience using container frameworks such as Docker or Kubernetes.
• Demonstrated experience using data visualization tools such as IntelliBoard.
• AWS Machine Learning Specialty.