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Python Ml Developer Jobs in College Park, MD (NOW HIRING)

Interon IT Solutions

AI/ML Engineer

Reston, VA · On-site

AI/ML Engineer Location: Reston VA - In person interviews so need Local In EAST coast only​ Core ... Develop high-performance Python microservices (FastAPI/Flask) enabling scalable data pipelines ...

System One

AI/ML Engineer

Mclean, VA · Remote

The ideal candidate combines strong Python software engineering skills with hands-on experience building scalable AI/ML applications using large, complex structured and unstructured datasets.

System One Holdings, LLC

AI/ML Engineer

Mclean, VA · On-site

The ideal candidate combines strong Python software engineering skills with hands-on experience building scalable AI/ML applications using large, complex structured and unstructured datasets.

System One

AI/ML Engineer

Mclean, VA · Remote

The ideal candidate combines strong Python software engineering skills with hands-on experience building scalable AI/ML applications using large, complex structured and unstructured datasets.

System One

AI/ML Engineer

Mclean, VA · On-site

The ideal candidate combines strong Python software engineering skills with hands-on experience building scalable AI/ML applications using large, complex structured and unstructured datasets.

Synergy ECP

AI/ML Engineer

Annapolis Junction, MD · On-site

S. degree in a technical field and 3+ years of experience • Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn) • Experience with data processing and feature engineering • ...

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Python Ml Developer information

See College Park, MD salary details

$13

$57

$85

How much do python ml developer jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for python ml developer in College Park, MD is $57.95, according to ZipRecruiter salary data. Most workers in this role earn between $47.74 and $65.82 per hour, depending on experience, location, and employer.

What does a Python ML Developer do?

A Python ML Developer designs, builds, and deploys machine learning models using the Python programming language. They work with large datasets, clean and process data, select appropriate algorithms, and use libraries like TensorFlow, PyTorch, or scikit-learn to implement solutions. Their work often involves collaborating with data scientists and engineers to integrate machine learning models into applications. Additionally, they may be responsible for testing, tuning, and optimizing models to achieve the best possible performance in real-world scenarios.

What are some common challenges Python ML Developers face when deploying machine learning models to production?

Python ML Developers often encounter challenges such as ensuring model scalability, managing dependencies, and maintaining reproducibility when deploying models into production environments. Integrating machine learning models with existing systems can require close collaboration with DevOps and software engineering teams to streamline workflows and automate deployment pipelines. Additionally, monitoring model performance over time and handling data drift are crucial responsibilities to ensure continued accuracy and reliability of deployed solutions.

What are the key skills and qualifications needed to thrive as a Python ML Developer?

To thrive as a Python ML Developer, you need strong programming skills in Python, a solid understanding of machine learning algorithms, and a background in mathematics or statistics, often supported by a degree in computer science, engineering, or a related field. Familiarity with tools and libraries such as TensorFlow, scikit-learn, PyTorch, and version control systems like Git is essential, along with experience using data visualization and cloud platforms. Critical soft skills include problem-solving, adaptability, and effective communication to collaborate with cross-functional teams and explain complex models to stakeholders. These skills ensure the successful development, deployment, and maintenance of machine learning solutions that drive business value.

What is the difference between Python Ml Developer vs Data Scientist?

AspectPython Ml DeveloperData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; Python, ML certificationsBachelor's/Master's in Data Science, Statistics, or related; Python, ML certifications
Work EnvironmentSoftware development teams, AI/ML projectsResearch, data analysis, modeling teams
Employer & Industry UsageTech companies, startups, AI firmsFinance, healthcare, tech, research institutions
Common Search & ComparisonYesYes

Python ML Developers focus on building and deploying machine learning models using Python, often working closely with software engineering teams. Data Scientists analyze data, create models, and generate insights, often using Python along with statistical tools. While both roles require Python and ML knowledge, Python ML Developers are more involved in implementation and deployment, whereas Data Scientists focus on data analysis and research.

What job categories do people searching Python Ml Developer jobs in College Park, MD look for? The top searched job categories for Python Ml Developer jobs in College Park, MD are:
What cities near College Park, MD are hiring for Python Ml Developer jobs? Cities near College Park, MD with the most Python Ml Developer job openings:
Python Ml Developer jobs near you
Infographic showing various Python Ml Developer job openings in College Park, MD as of August 2026, with employment types broken down into 2% Internship, 81% Full Time, 11% Part Time, and 6% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution, with an average salary of $120,531 per year, or $57.9 per hour.

AI/ML Engineer

Interon IT Solutions

Reston, VA • On-site

Contractor

Re-posted 6 days ago

Job description

#W2 only
 
Job title: AI/ML Engineer 
Location: Reston VA - In person interviews so need Local In EAST coast only​
 
Job Description 
Core Responsibilities (AI/ML, Python, AWS, GenAI) 
Design and implement end-to-end AI/ML and Generative AI solutions using Python, including 
model training, evaluation, optimization, and deployment. 
Build and maintain cloud-native applications on AWS using services such as Lambda, 
ECS/Fargate, S3, API Gateway, DynamoDB, RDS/Aurora, SageMaker, and Bedrock. 
Develop high-performance Python microservices (FastAPI/Flask) enabling scalable data 
pipelines, model inference, and real-time analytics. 
Architect and operationalize RAG pipelines, embeddings, vector databases, and LLM-powered 
automation (chatbots, summarization, semantic search, anomaly detection). 
Implement CI/CD pipelines (GitHub/GitLab/CodePipeline) and infrastructure-as-code 
(Terraform/CloudFormation) for reliable, automated deployments. 
Build robust MLOps workflows, including model versioning, containerized training/inference, 
automated retraining, monitoring, and performance tuning.