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Home Based Python Machine Learning Jobs in Washington, DC

Virtual Networx

AI/ML Engineer

Mclean, VA · On-site

Python, Machine Learning, Deep Learning, Scikit-learn, TensorFlow, PyTorch, Pandas, NumPy, SQL, NLP ... Develop and integrate Generative AI and LLM-based solutions where applicable. * Work with OpenAI ...

Venturegloballng

Engineer, Machine Learning

Arlington, VA · On-site

$157K - $185K/yr

The company's Louisiana-based export projects service the global demand for North American natural ... Exceptional skills in data processing languages such as SQL, Python, or Scala. * Exceptional skills ...

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All JobsHome Based Python Machine Learning JobsHome Based Python Machine Learning Jobs in Washington, DC

Home Based Python Machine Learning information

See Washington, DC salary details

$14

$66

$97

How much do home based python machine learning jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for home based python machine learning in Washington, DC is $66.39, according to ZipRecruiter salary data. Most workers in this role earn between $54.71 and $75.43 per hour, depending on experience, location, and employer.

What is the difference between Home Based Python Machine Learning vs Data Analyst?

AspectHome Based Python Machine LearningData Analyst
Required CredentialsPython programming, machine learning certifications, data analysis skillsData analysis certifications, SQL, Excel, Python or R knowledge
Work EnvironmentRemote, home-based, often project-focusedRemote or on-site, business or client-focused
Industry UsageTech, finance, healthcare, e-commerceBusiness, marketing, finance, healthcare
Common Search/ComparisonYesYes

Home Based Python Machine Learning and Data Analyst roles share overlapping skills like data handling and analysis tools. However, Python Machine Learning focuses more on developing algorithms and models using Python, while Data Analysts primarily interpret data to generate reports and insights. Both roles are in demand for remote work and require analytical skills, but Python Machine Learning positions often demand more advanced programming and machine learning expertise.

What are the most commonly searched types of Python Machine Learning jobs in Washington, DC?

The most popular types of Python Machine Learning jobs in Washington, DC are:

What are popular job titles related to Home Based Python Machine Learning jobs in Washington, DC?

For Home Based Python Machine Learning jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Home Based Python Machine Learning jobs in Washington, DC look for?

The top searched job categories for Home Based Python Machine Learning jobs in Washington, DC are:

Home Based Python Machine Learning jobs near you

AI/ML Engineer

Mclean, VA • On-site

Virtual Networx
IT Services • 51 - 200 employees
Learn more about Virtual Networxexternal

Other

Posted 29 days ago

Job description

Role: AI/ML Engineer
Experience: 10+ Years
Duration: 12 months
Location: MC Lean , VA

Skills: Python, Machine Learning, Deep Learning, Scikit-learn, TensorFlow, PyTorch, Pandas, NumPy, SQL, NLP, Computer Vision, Generative AI, LLM, Prompt Engineering, RAG, Vector Databases, REST APIs

Responsibilities:

  • Design, develop, and deploy Machine Learning and AI solutions for business applications.
  • Build and optimize ML models for classification, regression, forecasting, recommendation, and NLP use cases.
  • Develop data preprocessing, feature engineering, model training, and evaluation pipelines.
  • Work with Python, Pandas, NumPy, Scikit-learn, TensorFlow, and/or PyTorch.
  • Develop and integrate Generative AI and LLM-based solutions where applicable.
  • Work with OpenAI/LLM APIs, prompt engineering, embeddings, vector databases, and RAG architectures.
  • Build scalable ML pipelines using MLflow, Kubeflow, Databricks, AWS, Azure, or Google Cloud Platform.
  • Deploy models through REST APIs, Docker, Kubernetes, and cloud platforms.
  • Monitor model performance, data quality, drift, and production issues.
  • Collaborate with Data Engineers, Software Engineers, Data Scientists, Product Owners, and business stakeholders.
  • Perform model tuning, experimentation, validation, and performance optimization.
  • Implement MLOps practices for CI/CD, model versioning, experiment tracking, and automated deployment.
  • Ensure AI solutions meet requirements for security, scalability, reliability, and responsible AI.
  • Document models, architectures, workflows, and technical processes.

Required Skills

  • Python
  • Machine Learning
  • Deep Learning
  • Scikit-learn
  • TensorFlow / PyTorch
  • Pandas / NumPy
  • SQL
  • NLP / Computer Vision as applicable
  • Generative AI / LLM
  • Prompt Engineering
  • RAG
  • Vector Databases
  • REST APIs
  • Docker / Kubernetes
  • Cloud: AWS / Azure / Google Cloud Platform
  • Git
  • MLOps / MLflow

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