Machine Learning Engineer

  • CHANTILLY, VA
  • Posted 12 days ago | Updated 11 hours ago

Overview

On Site
Full Time

Skills

Natural language processing
Machine Learning (ML)
Information Technology
Supply chain management
Technical Support
Data Science
Data engineering
Python
UI
Apache NiFi
Project management
Computer vision
Operating systems
Unstructured data
Cloud computing
Big data
Apache Spark
Systems engineering
Security clearance
Network
Usability
Procurement
Evaluation
Software development
Collaboration
Communication
Data
Analytics
Database
Streaming
Dashboard
Microservices
SQL
NoSQL
Documentation
Policies
Multimedia
Confluence
JIRA
Oracle Linux
Testing
Linux
Automation
Workflow
Bash
Scripting
Collections
Extraction
Transformation
Extract
transform
load
Modeling
Elasticsearch
Kibana
Git
Amazon Web Services
Docker
Kubernetes
Tableau
SAP BASIS
FOCUS

Job Details

Job ID: 2406373

Location: CHANTILLY, VA, US

Date Posted: 2024-05-06

Category: Software

Subcategory: SW Engineer

Schedule: Full-time

Shift: Day Job

Travel: No

Minimum Clearance Required: TS/SCI with Poly

Clearance Level Must Be Able to Obtain: None

Potential for Remote Work: No

Description

INTRODUCTION: The Sponsor conducts technical assessments and provides technical guidance on the use of various enterprise and mission enabling technologies supporting the Sponsor's Information Technology (IT) systems and network infrastructures to enhance the security posture and usability. The Sponsor also provides critical review and guidance on procurement and supply chain issues, conducts digital forensic systems evaluation and analysis, and delivers technical support to investigations and insider threat issues. The Sponsor leverages technology, combined with subject matter expertise, to conduct these activities in support of its corporate office as well as external mission partners and stakeholders. In support of the above activities, the Sponsor delivers data science and data engineering services across the department. The Sponsor's office provides short-term and long-term data science support, which requires technical expertise to deploy verified mathematical and scientific techniques programmatically. The Sponsor's office also provides short-term and long-term data engineering support. The work is performed within a team environment and requires constant iteration with stakeholders. Work will include development of python programming packages and data engineering pipelines to support cross-enterprise needs. Work will include high technical skill in programming, primarily python, and common data engineering tools, as well as high levels of collaboration, communication, and requirements solicitation.

WORK REQUIREMENTS: Data Science Support - HRR: YES

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.

Develop robust data engineering pipelines utilizing Apache Nifi and Python to include use and development of REST APIs and microservices.

Clean, parse and transform data from multiple file types into appropriate database architectures (e.g., SQL, NoSQL, and graph) which perform at scale.

Develop, deploy, and provide feature enhancements using Python for data science products and services, to include Python packages, code documentation, notebooks, and microservices.

Ensure that all technical development and content complies with Sponsor's security policies and regulations.

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.

Consult with stakeholders to determine present and future user needs for Sponsor consideration.

Communicate and collaborate across organizational boundaries, to include other staff and contractor teams.

Work with Sponsor staff and contractor personnel, as well as external stakeholders on mission-based projects.

Implement data science and data engineering requirements as defined by the Sponsor.

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.

Utilize project management systems such as Confluence and JIRA to define and track requirements.

Ensure that technical solutions leverage industry best practices, designing for security and excellence while minimizing the total cost of ownership.

Qualifications

Required Skills
  1. Demonstrated experience with Nutanix or NetApps.
  2. Demonstrated on-the-job experience developing Python programming packages to include REST APIs and microservices.
  3. Demonstrated experience developing and testing reusable Python code.
  4. Demonstrated experience with machine learning techniques including natural language processing and computer vision.
  5. Demonstrated on-the-job experience using Linux flavored operating systems (OS) and with automating workflows using Bash scripting.
  6. Demonstrated experience using data engineering tools such as Apache Nifi to preprocess, modify, aggregate, load, index, and archive large data collections.
  7. 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.
  8. Demonstrated experience modeling, structuring, cleaning, and conditioning data from multiple sources and in multiple different formats, languages, and encodings.
  9. Demonstrated experience using Elasticsearch and Kibana technologies.
  10. Demonstrated experience using code repositories such as Git.
  11. Demonstrated experience developing robust documentation for code, Python packages and data science methodologies.
  12. Demonstrated experience explaining complex technical issues to more junior data scientists, in graphical, verbal, or written formats.
  13. Demonstrated experience delivering results to stakeholders through written documentation and oral briefings.
  14. Demonstrated experience working with multiple stakeholders.

Desired Skills:
  1. Demonstrated experience with cloud services, such as AWS.
  2. Demonstrated experience using big data processing tools such as Apache Spark or Trino.
  3. Demonstrated experience using container frameworks such as Docker or Kubernetes.
  4. Demonstrated experience using data visualizations tools such as Tableau.


SAIC accepts applications on an ongoing basis and there is no deadline.

Covid Policy: SAIC does not require COVID-19 vaccinations or boosters. Customer site vaccination requirements must be followed when work is performed at a customer site.


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