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Associate Machine Learning Government Jobs in Pennsylvania

Air

Senior Machine Learning Engineer

Pittsburgh, PA · On-site

$118K - $156K/yr

... for government agencies and industrial suppliers. By revealing true capacity, exposing real ... Keep up to date with Machine Learning best practices and evolving open-source frameworks

Air

Senior Machine Learning Engineer

Pittsburgh, PA · On-site

$118K - $156K/yr

... for government agencies and industrial suppliers. By revealing true capacity, exposing real ... Keep up to date with Machine Learning best practices and evolving open-source frameworks

Air

Senior Machine Learning Engineer

Pittsburgh, PA · On-site

$118K - $156K/yr

... for government agencies and industrial suppliers. By revealing true capacity, exposing real ... Keep up to date with Machine Learning best practices and evolving open-source frameworks

Air

Senior Machine Learning Engineer

Pittsburgh, PA · On-site

$101K - $139K/yr

... for government agencies and industrial suppliers. By revealing true capacity, exposing real ... We are seeking an experienced Senior Machine Learning Engineer to join our AI/ML team and build the ...

Air

Senior Machine Learning Engineer

Pittsburgh, PA · On-site +1

$101K - $139K/yr

... for government agencies and industrial suppliers. By revealing true capacity, exposing real ... We are seeking an experienced Senior Machine Learning Engineer to join our AI/ML team and build the ...

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All JobsAssociate Machine Learning Government JobsAssociate Machine Learning Government Jobs in Pennsylvania

Associate Machine Learning Government information

What is the difference between Associate Machine Learning Government vs Data Scientist Government?

AspectAssociate Machine Learning GovernmentData Scientist Government
Required CredentialsBachelor's degree in CS, Data Science, or related field; some roles may require certifications in ML or AIBachelor's or Master's in Data Science, Statistics, or related; certifications like CAP or DASCA are common
Work EnvironmentGovernment agencies, research labs, or defense sectors; focus on ML model development and deploymentGovernment agencies, policy analysis, research; focus on data analysis, modeling, and insights
Employer & Industry UsageFederal, state, or local government; defense, intelligence, or public servicesGovernment departments, research institutions, public policy agencies

Associate Machine Learning Government and Data Scientist Government roles often overlap in credentials and work environment, but the former emphasizes ML model development, while the latter focuses on broader data analysis and insights within government sectors.

What are the most commonly searched types of Machine Learning Government jobs in Pennsylvania?

The most popular types of Machine Learning Government jobs in Pennsylvania are:

What are popular job titles related to Associate Machine Learning Government jobs in Pennsylvania?

For Associate Machine Learning Government jobs in Pennsylvania, the most frequently searched job titles are:

What job categories do people searching Associate Machine Learning Government jobs in Pennsylvania look for?

The top searched job categories for Associate Machine Learning Government jobs in Pennsylvania are:

What cities in Pennsylvania are hiring for Associate Machine Learning Government jobs?

Cities in Pennsylvania with the most Associate Machine Learning Government job openings:

Associate Machine Learning Government jobs near you
Infographic showing various Associate Machine Learning Government job openings in Pennsylvania as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution.

Principal Machine Learning Engineer

Philadelphia, PA • On-site

Delan Associates, Inc
Engineering Professional Services • 51 - 200 employees
Learn more about Delan Associates, Incexternal

Contractor

Re-posted 27 days ago

Job description

Principal Machine Learning Engineer to serve as a hands-on technical leader for machine learning, predictive modeling, scoring, decisioning, and applied AI initiatives. This role will primarily focus on building, validating, deploying, and improving machine learning models, while also bringing principal-level judgment to problem definition, model design, stakeholder engagement, and production readiness.

Hands-On Model Development

Build, test, validate, and improve machine learning models for scoring, prediction, prioritization, risk detection, engagement, intervention targeting, and decision support.

Perform exploratory data analysis, data quality assessment, feature engineering, model training, model selection, and performance evaluation.

Develop practical ML models that balance predictive performance, explainability, stability, maintainability, and business usefulness.

Work with structured, semi-structured, and operational data to create model-ready datasets and reusable features.

Use tools such as Python, SQL, Spark, Databricks, MLflow, scikit-learn, XGBoost, or similar platforms and libraries.

Move quickly from data exploration to prototype to validated model to production-ready capability.

Required Qualifications

Professional experience in machine learning, data science, software engineering, analytics engineering, applied AI, or related technical fields.

5+ years of hands-on machine learning model development experience, including feature engineering, model training, validation, evaluation, and iteration.

3+ years of experience deploying, operationalizing, or supporting models in production or business-critical environments.

Strong hands-on experience with Python and SQL.

Experience with modern ML and data platforms such as Databricks, Spark, MLflow, Snowflake, Azure, AWS, or similar technologies.

Strong understanding of model evaluation, calibration, thresholding, score interpretation, monitoring, drift, retraining, and production ML lifecycle management.

Experience translating ambiguous business problems into concrete ML designs, model requirements, validation plans, and measurable outcomes.

Ability to explain model behavior, model performance, assumptions, limitations, and tradeoffs to both technical and non-technical stakeholders.

Strong engineering discipline, including clean code, reproducibility, versioning, testing, documentation, and maintainability.

Ability to work independently as a senior hands-on contributor while also providing technical leadership and modeling judgment.

Scoring, Scorecards, and Transparent Models

Production ML and MLOps

Product and Rapid-Build Execution

Generative AI and AI Automation

Requirement Shaping and Stakeholder Partnership

Employment Type: CONTRACTOR

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