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Home Based Python Machine Learning Jobs in Texas

Develop and integrate Generative AI and LLM-based applications * Work with Python, machine learning, and AI frameworks * Build and test AI/ML models and APIs * Work with LLMs, Prompt Engineering, RAG ...

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Python API Developer

Irving, TX · On-site

$48.25 - $66.50/hr

Machine Learning (SDV). * Apache Spark. * Apache Kafka. * Power Bi, Tableau, QlikView. * PostgreSQL. Manikanth Sarian Solutions, Inc. Ph: 732-790-2266 X 105 manikanth.d@sariansolutions.com

Experience in using Python, R or Matlab is required * Industry experience as a Machine Learning Engineer * Knowledge of or experience in building production quality and large-scale deployment of ...

New

The role involves developing and optimizing machine learning models, managing large-scale datasets ... based algorithms, including data collection, training, and deployment. • Proficiency in Python ...

Work with Generative AI, LLMs, prompt engineering, or RAG-based applications. * Deploy and monitor ... Python * Machine Learning * Deep Learning * TensorFlow / PyTorch * Scikit-learn * NumPy * Pandas

Degree in Computer Science, Machine Learning, or Related disciplines; and 2+ years of relevant experience • Excellence in Python • Deep expertise in algorithms and data structures • Exposure to ...

As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and ... using Python, PySpark, and Azure-based technologies. * Process, analyze, and manipulate large ...

As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and ... using Python, PySpark, and Azure-based technologies. * Process, analyze, and manipulate large ...

As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and ... using Python, PySpark, and Azure-based technologies. * Process, analyze, and manipulate large ...

As a Performance Assurance Machine Learning Engineer, you will work under the coaching of Senior ... You will utilize skills to query databases to extract data, use skills in Python or R to analyze ...

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Home Based Python Machine Learning information

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 Texas?

The most popular types of Python Machine Learning jobs in Texas are:

What cities in Texas are hiring for Home Based Python Machine Learning jobs?

Cities in Texas with the most Home Based Python Machine Learning job openings:

Machine Learning Engineer

Plano, TX • On-site

Other

Posted 2 days ago

New


Job description

Job Title: Machine Learning Engineer
Location: Plano, TX – Onsite/Hybrid
Job Type: Contract
Work Authorization: STRICTLY ON W2

Job Summary

We are looking for a Machine Learning Engineer with a strong engineering and model-development mindset. The ideal candidate will have hands-on experience with Python, machine learning model development, deployment, troubleshooting, and production support across Windows and Linux environments.

This is not primarily a DevOps or SRE position. We are looking for someone who understands the engineering side of machine learning, including model development and lifecycle, while also being comfortable supporting ML applications in production.

Key Responsibilities
  • Develop, maintain, deploy, and troubleshoot machine learning applications and models.

  • Work closely with Data Scientists and ML Engineers to take models from development through production.

  • Develop and maintain Python-based ML applications and services.

  • Support ML applications running on Windows and Linux environments.

  • Manage and troubleshoot Kubernetes clusters and Docker containers supporting ML workloads.

  • Deploy and manage machine learning models throughout their lifecycle.

  • Debug complex production issues using Python, logs, monitoring, and troubleshooting tools.

  • Implement monitoring and alerting using Datadog to ensure application and model health.

  • Automate repetitive engineering and operational tasks using Python and other scripting technologies.

  • Work with CI/CD pipelines to support reliable ML application and model deployments.

  • Collaborate with engineering, data science, and infrastructure teams.

  • Ensure ML applications meet requirements for performance, security, scalability, and availability.

  • Document architecture, deployment processes, model workflows, and troubleshooting procedures.

Required Skills
  • Strong hands-on Python programming experience.

  • Strong understanding of Machine Learning concepts and workflows.

  • Experience with ML model development and/or model engineering.

  • Hands-on experience with ML model deployment and lifecycle management.

  • Experience supporting applications in both Windows and Linux environments.

  • Experience with on-premises servers and production environments.

  • Hands-on experience with Kubernetes and Docker.

  • Experience troubleshooting distributed applications and production issues.

  • Experience with Datadog or similar monitoring/observability tools.

  • Experience with CI/CD pipelines for ML applications.

  • Familiarity with AWS cloud services.

  • Understanding of DevOps/SRE practices as they relate to supporting ML applications.

  • Strong problem-solving and debugging skills.

  • Excellent communication and collaboration skills.

Ideal Candidate Profile

We are specifically looking for an engineering-oriented Machine Learning Engineer who can understand and contribute to model development, not just infrastructure or operations.

Strong candidates will have:

  • Machine Learning + Python development experience

  • ML model development/deployment experience

  • Production application troubleshooting experience

  • Kubernetes/Docker experience

  • Windows/Linux administration experience

  • Experience working closely with Data Scientists

The candidate should be stronger on ML engineering and application/model development than pure infrastructure or operations.