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From Home Embedded Machine Learning Jobs in McKinney, TX

Develop visionโ€‘language models and Mixture of Experts architectures, from experimental design ... Contribute to our machine learning repositories and optimize models for performance, scalability ...

Develop vision-language models and Mixture of Experts architectures, from experimental design ... Contribute to our machine learning repositories and optimize models for performance, scalability ...

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... All from the comfort of your home. Why Join Our Platform? * Earn incrementally higher pay for each ...

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... All from the comfort of your home. Why Join Our Platform? * Earn incrementally higher pay for each ...

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... All from the comfort of your home. Why Join Our Platform? * Earn incrementally higher pay for each ...

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... All from the comfort of your home. Why Join Our Platform? * Earn incrementally higher pay for each ...

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... All from the comfort of your home. Why Join Our Platform? * Earn incrementally higher pay for each ...

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... All from the comfort of your home. Why Join Our Platform? * Earn incrementally higher pay for each ...

Machine Learning Developer

Dallas, TX ยท On-site

$115K - $140K/yr

This individual will create the MLOps framework, development standards, and platform foundation needed to move machine learning models from experimentation into secure, reliable production ...

Machine Learning Developer

Dallas, TX ยท On-site

$115K - $140K/yr

This individual will create the MLOps framework, development standards, and platform foundation needed to move machine learning models from experimentation into secure, reliable production ...

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From Home Embedded Machine Learning information

See McKinney, TX salary details

$65K

$142.3K

$161.5K

How much do from home embedded machine learning jobs pay per year?

As of Sep 12, 2026, the average yearly pay for from home embedded machine learning in McKinney, TX is $142,346.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,000.00 and $160,600.00 per year, depending on experience, location, and employer.

What are the most commonly searched types of Embedded Machine Learning jobs in McKinney, TX?

The most popular types of Embedded Machine Learning jobs in McKinney, TX are:

What job categories do people searching From Home Embedded Machine Learning jobs in McKinney, TX look for?

The top searched job categories for From Home Embedded Machine Learning jobs in McKinney, TX are:

Machine Learning Engineer

Plano, TX โ€ข On-site

Other

This job post hasย expired 1 day ago.ย Applications are no longer accepted.


Job description

Job Title: Machine Learning Engineer
Location: Plano, TX โ€“ 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.