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Home Based Python Machine Learning Jobs in Alexandria, VA

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 ...

Proficiency in Python and the Python Data Stack, including pandas, NumPy, scikit-learn, PyTorch ... Machine Learning Engineering Leadership * Production Deployment Experience * Python Proficiency

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 ...

Work with text, image, embedding-based, and structured or semi-structured features to improve ... Strong command of Python and common data science and machine learning libraries. Hands-on ...

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

Strong Python skills and experience with ML frameworks such as PyTorch or JAX. * Hands-on ... Bonus : Performance-based annual bonus * Professional Development : Support for conferences ...

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Home Based Python Machine Learning information

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

As of Aug 21, 2026, the average hourly pay for home based python machine learning in Alexandria, VA is $62.74, according to ZipRecruiter salary data. Most workers in this role earn between $51.73 and $71.25 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 popular job titles related to Home Based Python Machine Learning jobs in Alexandria, VA?

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

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

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

What cities near Alexandria, VA are hiring for Home Based Python Machine Learning jobs?

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Other

Posted 10 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