Machine Learning Engineer

Key Skills

Apache NiFi, AWS, Docker, Elasticsearch, ETL frameworks, Kibana, Kubernetes-K8s, Linux Operating system, Machine learning techniques, Python Programming, REST API, SPARK Programming

Job Description

SAIC, a leading provider of systems development and deployment, targeting and intelligence analysis, systems engineering and integration, and training capabilities and solutions for the Intelligence Community (IC), is seeking creative and dedicated professionals to fulfill their career goals and objectives, while delivering mission excellence on programs of national importance. 

SAIC’s National Intelligence Community (NIC) Business Unit, USG Mission and Information Technology Division, is seeking a Machine Learning Engineer to develop Python programming packages and data engineering pipelines to support cross-enterprise needs. This will include high technical skills in programming and common data engineering tools, as well as high levels of collaboration, communication, and requirements solicitation. 

Responsibilities include: 

• Creating data science and data engineering products that include data models, data ingestion/transform, analytics which includes machine learning, and some form of output as either a machine-readable format, a user interface, or dashboard 
• Developing data engineering pipeline utilizing Apache Nifi and Python to include use and development of REST APIs and microservices
• Cleaning, parsing, and transforming data from multiple files types into database architecture (e.g., SQL, NoSQL, and Graph) 
• Ensuring technical solutions leverage industry best practices, designing for security and excellences while minimizing the total cost of ownership 

Qualifications

Required Qualifications:

• Active TS/SCI with polygraph 
• Bachelor’s Degree (B.S.) in Computer Science, Software Engineering, Information Management Systems, or a related discipline. Note that years of experience can be substituted in lieu of degree. 
• Five (5) or more years of demonstrated experience in the following: 

• 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 work flows usng Bash scripting
• Using data engineering tools such as Apache Nifi to preprocess, modify, aggregate, load, index, and archive large data collections
• Performing ETL of structured and unstructured data into pipelines to ensure it is ingested into downstream systems with accuracy, reliability, and consistency at 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 Qualifications:

• Demonstrated experience with cloud services, such as AWS. 
• Demonstrated experience using big data processing tools such as Apache Spark or Trino. 

• Demonstrated experience using container frameworks such as Docker or Kubernetes. 
• Demonstrated experience using data visualizations tools such as Tableau.