ZipRecruiter

Log In

1

Quantitative Researcher Machine Learning Jobs in Washington, DC

Ametek

Machine Learning Engineer

Herndon, VA · Hybrid

... closely related quantitative field. * This is a hybrid role in Herndon, VA and no relocation ... research, internships, or realworld projects involving applied machine learning. #LI-WA1 #LI-HYBRID

10a Labs

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... You will collaborate closely with researchers, software engineers, red teamers, and subject-matter ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... You will collaborate closely with researchers, software engineers, red teamers, and subject-matter ...

Ametek

Machine Learning Engineer

Herndon, VA · On-site

... closely related quantitative field. * This is a hybrid role in Herndon, VA and no relocation ... research, internships, or real-world projects involving applied machine learning. #LI-WA1 #LI ...

Full Scope

Machine Learning Engineer

Reston, VA

Stay current with the latest research and advancements in machine learning and AI. * Participate in code reviews, team meetings, and contribute to a collaborative development environment. * Document ...

Kitware

Machine Learning Engineer

Arlington, VA · Hybrid

Kitware is a leader in advanced research and algorithm development in artificial intelligence (AI ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Kitware

Machine Learning Engineer

Arlington, VA · Hybrid

$110K - $160K/yr

Kitware is a leader in advanced research and algorithm development in artificial intelligence (AI ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Kitware

Machine Learning Engineer

Arlington, VA · On-site

$110K - $160K/yr

Kitware is a leader in advanced research and algorithm development in artificial intelligence (AI ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

next page

Showing results 1-20

All JobsQuantitative Researcher Machine Learning JobsQuantitative Researcher Machine Learning Jobs in Washington, DC

Quantitative Researcher Machine Learning information

See Washington, DC salary details

$59.5K

$135K

$222.6K

How much do quantitative researcher machine learning jobs pay per year?

As of Jun 26, 2026, the average yearly pay for quantitative researcher machine learning in Washington, DC is $134,966.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,900.00 and $172,700.00 per year, depending on experience, location, and employer.
What are popular job titles related to Quantitative Researcher Machine Learning jobs in Washington, DC? For Quantitative Researcher Machine Learning jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Quantitative Researcher Machine Learning jobs in Washington, DC look for? The top searched job categories for Quantitative Researcher Machine Learning jobs in Washington, DC are:
Quantitative Researcher Machine Learning jobs near you
Machine Learning Engineer USC

Machine Learning Engineer USC

Connexions Data Inc

Arlington, VA • On-site

Other

Posted 14 days ago

Job description

Machine Learning Engineer

Start: IMMED

Duration: 06 - 12 months + Extension

Location: Arlington, VA

Type: W2 only

***Active Secret Clearance Required***

Position Overview

The Machine Learning Engineer will develop and validate quantitative models that translate organizational workload drivers into defensible Full-Time Equivalent (FTE) requirements across military, civilian, and contractor workforces. This role will work closely with Data Scientists, AI Engineers, and functional stakeholders to build scalable workforce planning and forecasting solutions using advanced statistical and machine learning techniques.

Education

Bachelor s Degree Required

Advanced degree preferred in:

  • Mathematics
  • Statistics
  • Econometrics
  • Economics

Required Skills

  • Machine Learning Modeling
  • Econometrics
  • Classical Regression Modeling
  • Statistics
  • Python

Preferred Skills

  • Palantir
  • Workforce Forecasting
  • Workload Modeling
  • AI and Data Testing

Day-to-Day Responsibilities

  • Build and validate quantitative workforce planning and forecasting models.
  • Translate organizational workload drivers into FTE requirements across military, civilian, and contractor populations.
  • Collaborate with Senior Data Scientists and AI Engineers to explore, analyze, and prepare data.
  • Perform feature engineering using Army personnel systems, including:
    • IPPS-A
    • DAPES
    • TAADS-R
  • Develop and calibrate regression models and plausibility banding logic.
  • Integrate scenario-planning model parameters into front-end applications.
  • Ensure model outputs are traceable, explainable, and defensible during client validation reviews.
  • Support AI and workforce analytics initiatives through statistical analysis and model testing.
  • Work with functional leads to validate assumptions, methodologies, and outputs.

Expected Deliverables

  • Automated manpower requirement determination models.
  • Data-driven workforce forecasting solutions.
  • Quantitative workforce planning outputs supported by defensible statistical methodologies.
  • Validated machine learning and regression-based forecasting models.
  • Reporting and analytics outputs supporting manpower and resource planning decisions.

Ideal Candidate Profile

  • Experience developing machine learning and statistical forecasting models.
  • Strong background in regression analysis, econometrics, and workforce analytics.
  • Proficiency in Python for data science and machine learning applications.
  • Ability to explain complex modeling approaches to both technical and non-technical stakeholders.
  • Experience working with large government or enterprise workforce datasets is highly preferred.

Apply