Machine Learning Engineer 615
Reads like a Data Operations role: data operations and migrations.
Chantilly, VA
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingBuild a repeatable process to collect skills from performance reviews
Create an access-controlled database for jobs, competencies, KSAs and proficiency levels
Write a data migration plan to export skills and competencies into the client's systems
Run a gap analysis comparing data sets against HR and talent systems
Evaluate the client's chatbot and ML/AI offerings and write an integration report
From the employer’s posting
Establish a repeatable process to periodically “scrape” and collect skills from a collection of Sponsor performance reviews.
Create an access-controlled database to store collected jobs, competencies, KSAs, and proficiency levels.
Create a data migration plan to export collected skills and competencies into the Sponsor’s systems.
Compare data sets against information contained in various HR and Talent Sponsor systems.
Evaluate the Sponsor's current Chatbot and Machine Learning (ML), Artificial Intelligence (AI) offerings, and integration methods, and provide a report on opportunities to integrate with the Sponsor's systems.
What you’ll bring
All qualificationsCore experience
- Demonstrated experience designing, creating tables, views, relationships, and scripting (SQL) with database systems (e.g., Oracle, MySQL, PostgreSQL, SQL, NOSQL, and/or structured and unstructured data).
- Demonstrated experience with implementing and using extract, transform, and load (ETL) tools.
- Demonstrated experience implementing, using, and creating Data Application Programming Interfaces (APIs) or data services.
- Demonstrated experience with Python, Java, and Scala programming languages.
- Demonstrated experience implementing, using, and creating data visualizations.
- Demonstrated experience implementing, using, or creating ML/AI software, tools, and services.
Preferred experience
- Demonstrated experience with using and creating Tableau visualizations.
- Demonstrated experience with using and creating workspaces in Bluescape.
- Demonstrated experience working with data services in the Sponsor’s cloud environment.
- Demonstrated experience with the Sponsor’s HR data and database environment.
Qualification wording
Demonstrated experience designing, creating tables, views, relationships, and scripting (SQL) with database systems (e.g., Oracle, MySQL, PostgreSQL, SQL, NOSQL, and/or structured and unstructured data).
Demonstrated experience with implementing and using extract, transform, and load (ETL) tools.
Demonstrated experience implementing, using, and creating Data Application Programming Interfaces (APIs) or data services.
Demonstrated experience with Python, Java, and Scala programming languages.
Demonstrated experience implementing, using, and creating data visualizations.
Demonstrated experience implementing, using, or creating ML/AI software, tools, and services.
Demonstrated experience with using and creating Tableau visualizations.
Demonstrated experience with using and creating workspaces in Bluescape.
Demonstrated experience working with data services in the Sponsor’s cloud environment.
Demonstrated experience with the Sponsor’s HR data and database environment.
Tools in this posting
- Java
- Python
- Scala
- SQL
- AWS
- Hadoop
- MySQL
- NoSQL
- Oracle
- PostgreSQL
- Tableau
Source — Tool mentions in context
- Demonstrated experience implementing, using, and creating Data Application Programming Interfaces (APIs) or data services. - Demonstrated experience with Python, Java, and Scala programming languages. - Demonstrated experience implementing, using, and creating data visualizations.
Required Skills: - Demonstrated experience designing, creating tables, views, relationships, and scripting (SQL) with database systems (e.g., Oracle, MySQL, PostgreSQL, SQL, NOSQL, and/or structured and unstructured data). - Demonstrated experience with implementing and using extract, transform, and load (ETL) tools.
- Demonstrated experience implementing, using, or creating ML/AI software, tools, and services. - Demonstrated experience using or creating Amazon Web Services (AWS)-based analytic tools and services. - Demonstrated experience using and implementing Apache Hadoop.
- Demonstrated experience using or creating Amazon Web Services (AWS)-based analytic tools and services. - Demonstrated experience using and implementing Apache Hadoop. Desired Skills:
Desired Skills: - Demonstrated experience with using and creating Tableau visualizations. - Demonstrated experience with using and creating workspaces in Bluescape.
Posting record
Report an errorOpen 5 monthsWe first saw this posting 151 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 2, 2026 · 151 days ago
- Recorded sightings
- 100
- Last seen by us
- Oct 31, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
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Job description
Freedom Technology Solutions Group is looking for a Machine Learning Engineer to lead an effort to bring its enterprise services into compliance with Federal data standards and formats. We are seeking analytical support to review, compare, and make recommendations for actions (data cleansing and transformation), as well as support data migration planning and coordination efforts. The right candidate will build a skills inventory, which will eventually integrate with other Sponsor’s systems, capturing both position skill requirements and competency levels, as well as personnel skill and competencies. The project manager will manage priorities.
The team shall work closely with systems engineers, database administrators, HR and Talent management, subject matter experts (SMEs), and project managers. The team shall perform a gap analysis of the following sub-tasks to include analyzing the current state, creating a baseline, identifying the gaps between what is known and what is needed, and developing an action plan to mitigate the gaps.
a) Review the Sponsor’s analysis of data sets.
b) Compare data sets against information contained in various HR and Talent Sponsor systems.
c) Review and map the Sponsor’s knowledge, skills, and abilities (KSAs) data sets to a variety of data sets pulled from various sources and identify structural differences between the fields in the various data sets.
d) Review the Sponsor’s data cleansing status.
e) Preview mock cleansing to show previous and desired end states.
Responsibilities:
- Establish a repeatable process to periodically “scrape” and collect skills from a collection of Sponsor performance reviews.
- Comply with the Sponsor’s guidance and policies regarding the collection, analysis, and use of personal identifiable Information (PII).
- Create an access-controlled collection of disparate data sources.
- Create an access-controlled database to store collected jobs, competencies, KSAs, and proficiency levels. The portable database will be transferrable to the process owner upon the completion of the implementation.
- Create a data migration plan to export collected skills and competencies into the Sponsor’s systems.
- Scrape, collate, and perform analysis of skill sets from open source, commercially available, and existing Sponsor databases and applications for addition to the skills repository.
- Scrape, gather, and analyze onboarding data to enrich the skill and competencies repository.
- Review and analyze all Sponsor service competency data for addition to the skill and competencies repository.
- Collaborate with other internal Sponsor offices to review, analyze, and update competency data from open source, commercially available, existing Sponsor databases, and applications, in addition to the skill and competencies repository.
- Evaluate the Sponsor's current Chatbot and Machine Learning (ML), Artificial Intelligence (AI) offerings, and integration methods, and provide a report on opportunities to integrate with the Sponsor's systems.
- Evaluate and assess the Sponsor’s planned system restructuring and its data integration impacts with a new external service provider.
- Work with the Sponsor's team supporting the system restructure to understand data standards required and the impact on the Sponsor’s OPM standardization efforts.
- Create a transition guide or Standard Operating Procesdures (SOPs) of activities.
- Create and maintain documentation for a Skills Taxonomy Gap Analysis Report to include an assessment of the current state, proposed baseline of competencies and KSAs, identification of missing data, and an action plan for gap mitigation.
- Create and maintain documentation of methodologies and tools used to accomplish the Scope of Work (SOW).
- Create and maintain documentation related to system access to database(s), systems used, and databases accessed to perform the work.
- Create and maintain a list of Internal and External Key Contacts, to include names and contact information.
- Create and maintain documentation regarding concerns, risks, and issues regarding data, storage, tools, and access.
- Create and maintain documentation regarding the status of deliverables and open actions
Required Skills:
- Demonstrated experience designing, creating tables, views, relationships, and scripting (SQL) with database systems (e.g., Oracle, MySQL, PostgreSQL, SQL, NOSQL, and/or structured and unstructured data).
- Demonstrated experience with implementing and using extract, transform, and load (ETL) tools.
- Demonstrated experience implementing, using, and creating Data Application Programming Interfaces (APIs) or data services.
- Demonstrated experience with Python, Java, and Scala programming languages.
- Demonstrated experience implementing, using, and creating data visualizations.
- Demonstrated experience implementing, using, or creating ML/AI software, tools, and services.
- Demonstrated experience using or creating Amazon Web Services (AWS)-based analytic tools and services.
- Demonstrated experience using and implementing Apache Hadoop.
Desired Skills:
- Demonstrated experience with using and creating Tableau visualizations.
- Demonstrated experience with using and creating workspaces in Bluescape.
- Demonstrated experience working with data services in the Sponsor’s cloud environment.
- Demonstrated experience with the Sponsor’s HR data and database environment.
- Demonstrated experience using SharePoint, and adding and integrating content.
- Demonstrated knowledge of Agile Project Management Methodology.
Source details
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Chantilly, VA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
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