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Remote Senior Machine Learning Engineer Jobs in Leander, TX

YO AI Labs

Machine Learning Engineer - Remote

Austin, TX · Remote

$80 - $120/hr

Senior Software Engineer Job Type: Contractor (~15 hours/week) Location: Remote Job Summary We are ... Create reinforcement learning environments for software engineering tasks. * Design tasks involving ...

PTP

Machine Learning Engineer - REMOTE

Austin, TX · On-site +1

We are looking for a Machine Learning Engineer to help us design and deliver CX solutions that provide our clients with a beautiful customer journey that achieves results. At PTP we value aptitude ...

webAI Inc

Staff Machine Learning Engineer

Austin, TX · On-site +1

We are seeking an experienced Staff Machine Learning Engineer with a strong background in Large Language Models (LLMs) and/or Mixture of Experts (MoEs). The ideal candidate will have a proven track ...

Adobe

2027 Intern - Machine Learning Engineer

Austin, TX · On-site +1

The Opportunity Adobe is looking for Machine Learning Engineer interns to work on some of the most impactful AI systems in the industry - from generative AI features and intelligent agents to search ...

New

YO AI Labs

Senior Software Engineer - Remote

Austin, TX · Remote

$121K - $160K/yr

Senior Software Engineer Job Type: Contract Location: Remote Job Summary: In this role, you'll ... Familiarity with modern AI or machine learning systems is a plus, though not required. * Background ...

Varsity Tutors

Machine Learning Tutor

Austin, TX · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Round Rock, TX · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

ActivTrak

Senior Data Engineer

Austin, TX · Remote

$105K - $142K/yr

... machine learning and analytics work scalable, observable, reliable, and economical. This is a ... Position is remote within US * Minimal travel * Limited physical demands This is an incredible ...

Hired Recruiters

Senior DevOps Engineer

Austin, TX · Remote

$128K - $165K/yr

Remote * Salary $150k - $200k * Seed Company * Skills: Ansible, Bash, Python, Terraform, Docker ... machine learning architecture. * Have an expert level understanding of Terraform and Ansible in ...

Hired Recruiters

Senior DevOps Engineer

Austin, TX · Remote

$128K - $165K/yr

Remote * Salary $150k - $200k * Seed Company * Skills: Ansible, Bash, Python, Terraform, Docker ... machine learning architecture. * Have an expert level understanding of Terraform and Ansible in ...

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All JobsMachine Learning Engineer JobsRemote Senior Machine Learning Engineer JobsRemote Senior Machine Learning Engineer Jobs in Leander, TX

Remote Senior Machine Learning Engineer information

See Leander, TX salary details

$72.1K

$136.9K

$183.5K

How much do remote senior machine learning engineer jobs pay per year?

As of Sep 3, 2026, the average yearly pay for remote senior machine learning engineer in Leander, TX is $136,916.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,000.00 and $154,300.00 per year, depending on experience, location, and employer.

What does a remote senior machine learning engineer do?

A Remote Senior Machine Learning Engineer designs, develops, and deploys machine learning models and systems while working from a location outside the traditional office. They collaborate with cross-functional teams, analyze large datasets, build scalable algorithms, and often mentor junior engineers. Their work helps organizations automate processes, gain insights, and improve products or services using data-driven approaches. Senior engineers are also responsible for ensuring model performance, reliability, and integration into production environments. Working remotely, they use various communication and collaboration tools to stay connected with their team.

How do remote senior machine learning engineers typically collaborate with cross-functional teams despite working remotely?

Remote Senior Machine Learning Engineers often work closely with data scientists, product managers, and software engineers using digital collaboration tools such as Slack, Jira, and video conferencing platforms. Regular virtual meetings and code reviews are standard practices to ensure alignment on project goals and to facilitate knowledge sharing. Clear communication, proactive documentation, and adaptability to different time zones are key to effective teamwork in a remote environment. This structure allows for flexibility while maintaining strong collaboration and project momentum.

What are the key skills and qualifications needed to thrive as a remote senior machine learning engineer, and why are they important?

To thrive as a Remote Senior Machine Learning Engineer, you need deep expertise in machine learning algorithms, statistical analysis, and strong programming skills (often in Python or similar languages), typically supported by a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (AWS, GCP, or Azure), and experience with data engineering pipelines are commonly required, along with certifications like TensorFlow Developer or AWS Machine Learning Specialty. Excellent problem-solving, communication, and self-management skills help you collaborate remotely, lead projects, and explain complex models to stakeholders. These skills and qualities are vital for building scalable ML solutions, ensuring effective teamwork across distributed environments, and delivering impactful results.

What is the difference between Remote Senior Machine Learning Engineer vs Remote Data Scientist?

AspectRemote Senior Machine Learning EngineerRemote Data Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models, collaborates with engineering teamsAnalyzes data, builds statistical models, provides insights
Employer & Industry UsageTech companies, startups, AI-focused firmsResearch institutions, tech companies, finance, healthcare

Remote Senior Machine Learning Engineers focus on designing, building, and deploying ML models, often working closely with engineering teams. Data Scientists analyze data and develop insights, but may not always deploy models. Both roles require strong technical skills and are highly sought after in tech industries, but their core responsibilities differ.

What are popular job titles related to Remote Senior Machine Learning Engineer jobs in Leander, TX?

For Remote Senior Machine Learning Engineer jobs in Leander, TX, the most frequently searched job titles are:

What job categories do people searching Remote Senior Machine Learning Engineer jobs in Leander, TX look for?

The top searched job categories for Remote Senior Machine Learning Engineer jobs in Leander, TX are:

What cities near Leander, TX are hiring for Remote Senior Machine Learning Engineer jobs?

Cities near Leander, TX with the most Remote Senior Machine Learning Engineer job openings:

Remote Senior Machine Learning Engineer jobs near you
Infographic showing various Remote Senior Machine Learning Engineer job openings in Leander, TX as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 22% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $136,916 per year, or $65.8 per hour.

Machine Learning Engineer - Remote

YO AI Labs

Austin, TX • Remote

$80 - $120/hr

Full-time

Posted 8 days ago

Job description

Senior Software Engineer

Job Type: Contractor (~15 hours/week)
Location: Remote

Job Summary

We are seeking experienced Senior Software Engineers to support an AI training project by creating reinforcement learning environments that evaluate AI models on complex software engineering tasks using Model Context Protocol (MCP) tools.

You will design reproducible environments, deterministic verification, and reference solutions for tasks such as bug fixing, feature implementation, codebase refactoring, and performance optimization. No prior AI experience is required.

Key Responsibilities
  • Create reinforcement learning environments for software engineering tasks.
  • Design tasks involving bug fixing, feature development, refactoring, and performance optimization.
  • Build deterministic verification systems and golden reference solutions.
  • Evaluate AI agents' ability to reason through complex codebases and use MCP tools effectively.
  • Develop realistic, reproducible software engineering scenarios.
  • Ensure tasks accurately measure coding ability, problem-solving, and tool usage.
  • Document solutions and provide clear technical feedback.
Required Skills
  • Strong proficiency in Python 3, Java, Rust, C++, or TypeScript.
  • Strong understanding of algorithms and data structures.
  • Experience with bug fixing and debugging complex software issues.
  • Proven experience in feature implementation and codebase refactoring.
  • Strong knowledge of performance optimization and tuning.
  • Excellent written and verbal communication.
  • Strong attention to detail.
Preferred Qualifications
  • Experience working with large-scale or distributed codebases.
  • Familiarity with AI/ML systems is a plus but not required.
  • Experience with rigorous code reviews and software engineering best practices.
  • Experience working effectively in remote or cross-functional teams.
Hiring Process
  1. Submit an application and screening questions.
  2. Complete an AI interview (~30 minutes).
  3. Complete a technical assessment, if required.
  4. Hiring Manager review.
Compensation

Compensation is output-based, with payment provided per task that meets project specifications. Minimum weekly submission requirements may apply.

Availability

Selected experts should be prepared to begin their first tasks within 24–48 hours of completing onboarding.