Machine Learning Engineer

Rapid Cycle Solutions is seeking to fill a Machine Learning Engineer for our customer in Chantilly, VA. Rapid Cycle Solutions LLC (RCS) is an innovative small business providing IT and management consulting services to the U.S. Federal Government and commercial clients. We have unique strengths in complex, cross-organizational solution analysis, design, development, implementation, and change management supporting enterprise requirements.
We need a Machine Learning Engineer for a Full-time position.
Position: Machine Learning Engineer
Location: Chantilly,VA
Position Type: Full-time position
Clearance: TS/SCI with FSP
Description
The Contractor Team shall develop robust data engineering pipelines utilizing Apache Nifi and Python to include use and development of REST APIs and microservices.
The Contractor Team shall create data science and data engineering products that include data models, data ingestion/transform, analytics which may include machine learning, and some form of output as either a machine-readable format (e.g. file output, database output, standard/streaming output) or a user interface or dashboard.
The Contractor Team shall clean, parse and transform data from multiple file types into appropriate database architectures (e.g. SQL, noSQL, and graph) which perform at scale.
T

he Contractor Team shall develop, deploy and provide feature enhancements using Python for data science products and services, to include Python packages, code documentation, notebooks, and microservices.
The Contractor Team shall ensure that all technical development and content complies with Sponsor’s security policies and regulations.
The Contractor Team shall work closely with the Sponsor to review and track data science and data engineering requirements and provide regular updates to clearly explain the project status and results in both written and verbal or multimedia briefings.
The Contractor Team shall consult with stakeholders to determine present and future user needs for Sponsor consideration.
The Contractor Team shall be required to communicate and collaborate across organizational boundaries, to include other staff and contractor teams.
The Contractor Team shall work with Sponsor staff and contractor personnel, as well as external stakeholders on mission-based projects.
The Contractor Team shall implement data science and data engineering requirements as defined by the Sponsor.
The Contractor Team shall determine how requirements are satisfied. Project priorities are managed by the staff manager of the business unit. Planned activities shall be coordinated with all stakeholders and approved by the Sponsor.
The Contractor Team shall utilize project management systems such as Confluence and JIRA to define and track requirements.
The Contractor Team shall ensure that technical solutions leverage industry best practices, designing for security and excellence while minimizing the total cost of ownership.
Required Qualifications:
Demonstrated on-the-job experience developing Python programming packages to include REST APIs and microservices.
Demonstrated experience developing and testing reusable Python code.
Demonstrated experience with machine learning techniques including natural language processing and computer vision.
Demonstrated on-the-job experience using Linux flavored operating systems (OS) and with automating work flows using Bash scripting.
Demonstrated experience using data engineering tools such as Apache Nifi to preprocess, modify, aggregate, load, index, and archive large data collections.
Demonstrated experience performing the extraction, transformation, and loading (ETL) of structured and unstructured data into pipelines to ensure it is ingested into downstream systems with accuracy, reliability, and consistency at scale.
Demonstrated experience modeling, structuring, cleaning, and conditioning data from multiple sources and in multiple different formats, languages, and encodings.
Demonstrated experience using Elasticsearch and Kibana technologies.
Demonstrated experience using code repositories such as Git.
Demonstrated experience developing robust documentation for code, Python packages and data science methodologies.
Demonstrated experience explaining complex technical issues to more junior data scientists, in graphical, verbal, or written formats.
Demonstrated experience delivering results to stakeholders through written documentation and oral briefings.
Demonstrated experience working with multiple stakeholders.
Demonstrated experience with Nutanix or NetApps.

#J-18808-Ljbffr