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Flexible Remote Machine Learning Engineer Jobs in Irving, TX

Tiger Analytics Inc.

ML Ops Architect

Dallas, TX · On-site +1

We are looking for a motivated and passionate Machine Learning Engineers for our team. As a Senior ML OPS Engineer, you will be joining a team of experienced Machine Learning Engineers that support ...

Waabi

Senior / Staff Perception Engineer

Dallas, TX · On-site +1

$158K - $269K/yr

... machine learning, computer vision, and self-driving technologies, and apply insights from the ... Vacation. - Flexible hours and Work from Home support. - Daily drinks, snacks and catered meals ...

Vytwo

Senior Data Engineer - Remote

Prosper, TX · Remote

$55 - $60/hr

Senior Data Engineer Remote Work *Must be a US Citizen* & have a USA Passport Primary ... Experience supporting machine learning workflows or analytical data science pipelines * Knowledge ...

Crowe LLP

Senior AI Engineer

Dallas, TX · On-site +1

$103K - $142K/yr

We offer unlimited PTO, a flexible remote work policy, and a supportive environment that ... The Senior AI Engineer 1 (Senior Staff) leads the development of advanced AI and machine learning ...

Gigapower

Data Engineer

Dallas, TX · Remote

$117K - $140K/yr

Virtual (Remote) Who We Are Gigapower is building next-generation fiber broadband infrastructure ... machine learning applications. · Establish and maintain standards for data quality, governance ...

Gigapower

Data Engineer

Dallas, TX · On-site +1

$113K - $136K/yr

Virtual (Remote) Who We Are Gigapower is building next-generation fiber broadband infrastructure ... and machine learning applications. • Establish and maintain standards for data quality ...

BNSF Railway

Sr/Staff Data Scientist (Remote - US)

TX · On-site +1

$165K - $300K/yr

Lead the development and deployment of advanced machine learning models to forecast outcomes and ... Advanced proficiency in programming languages such as Python, R, SQL, and Java. * Demonstrated ...

BNSF

Sr/Staff Data Scientist (Remote - US)

TX · Remote

$165K - $300K/yr

Lead the development and deployment of advanced machine learning models to forecast outcomes and ... Advanced proficiency in programming languages such as Python, R, SQL, and Java. * Demonstrated ...

DomainTools

Senior Software Engineer

Dallas, TX · Remote

$125K - $165K/yr

Experience with data mining or machine learning techniques * Experience with text codec, encoding ... flexible PTO and additional well-being benefits. DomainTools embraces diversity, equity and ...

Paradigm

Senior Applied ML Engineer

Irving, TX · Remote

$125K - $183K/yr

We are looking for a Senior Applied ML Engineer to design, implement, and scale machine learning systems that power next-generation construction and digital twin solutions. You will apply advanced ML ...

HedgeServ

Senior ITSMA Observability Engineer

Dallas, TX · On-site +1

$103K - $142K/yr

Our proprietary platform, enhanced by machine learning and robotic process automation, gives ... HedgeServ supports employees through a variety of offerings, including remote and hybrid working ...

Confie

AI Engineer

Addison, TX · On-site +1

$110K - $140K/yr

Flexible work options, including remote and hybrid opportunities, if eligible * Retirement Plan ... You will leverage large language models (LLMs), agentic frameworks, and advanced machine learning ...

Addison Group

Sr. Software Engineer

Dallas, TX · Remote

$170K - $220K/yr

Hybrid (3 days onsite, 2 days remote) Assignment Type: Direct Hire Pay: $170,000-$220,000 base ... AI or machine learning applications related to infrastructure Candidates should have a stable work ...

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All JobsMachine Learning Engineer JobsFlexible Remote Machine Learning Engineer JobsFlexible Remote Machine Learning Engineer Jobs in Irving, TX

Flexible Remote Machine Learning Engineer information

See Irving, TX salary details

$30.2K

$123.7K

$185.8K

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

As of Aug 19, 2026, the average yearly pay for flexible remote machine learning engineer in Irving, TX is $123,650.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,500.00 and $148,800.00 per year, depending on experience, location, and employer.

What is a flexible remote machine learning engineer?

A Flexible Remote Machine Learning Engineer is a professional who designs, builds, and deploys machine learning models while working remotely, often with flexible hours. They use programming, data analysis, and statistical skills to create algorithms that solve real-world problems, collaborating with teams through digital communication tools. This role allows for a better work-life balance and can be performed from anywhere with a reliable internet connection. Flexible remote positions are especially popular in the tech industry, where project-based work and results matter more than strict office hours.

What are the key skills and qualifications needed to thrive as a flexible remote machine learning engineer?

To thrive as a Flexible Remote Machine Learning Engineer, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and typically a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, cloud platforms (AWS, GCP, or Azure), and experience with data pipelines are essential, and certifications in machine learning or cloud technologies can be advantageous. Excellent communication, self-motivation, and time management skills help you collaborate effectively and stay productive in a remote, flexible work environment. These skills ensure you can independently deliver high-quality ML solutions, maintain clear team communication, and adapt to evolving project requirements.

How does a flexible remote work arrangement impact collaboration and project delivery for machine learning engineers?

In a flexible remote setting, Machine Learning Engineers often rely on digital collaboration tools to communicate with team members and manage projects. This setup allows for asynchronous work, enabling engineers to focus deeply on model development and data analysis without constant interruptions. However, it also means proactively scheduling check-ins and maintaining clear documentation are crucial to ensure alignment across distributed teams. While remote work offers autonomy and work-life balance, successful engineers build strong communication habits to keep projects on track and foster effective collaboration with data scientists, product managers, and software engineers.

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

AspectFlexible Remote Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, ML, or related fields; experience with ML frameworksBachelor's or higher in CS, Statistics, or related fields; proficiency in data analysis
Work EnvironmentRemote, collaborative teams, project-basedRemote or on-site, data analysis-focused
Industry UsageTech, finance, healthcare, e-commerceTech, marketing, finance, research
Common Search IntentRoles involving ML model development and deploymentRoles focused on data analysis and insights

The main difference is that a Flexible Remote Machine Learning Engineer primarily develops and deploys machine learning models, while a Data Scientist focuses on analyzing data to generate insights. Both roles often require similar educational backgrounds and can be remote, but their core responsibilities differ in application and focus.

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

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

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

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

What cities near Irving, TX are hiring for Flexible Remote Machine Learning Engineer jobs?

Cities near Irving, TX with the most Flexible Remote Machine Learning Engineer job openings:

Flexible Remote Machine Learning Engineer jobs near you
Infographic showing various Flexible Remote Machine Learning Engineer job openings in Irving, TX as of August 2026, with employment types broken down into 1% As Needed, 67% Full Time, 29% Part Time, and 3% Contract. Highlights an 86% Physical, 1% Hybrid, and 13% Remote job distribution, with an average salary of $123,650 per year, or $59.4 per hour.

ML Ops Architect

Tiger Analytics Inc.

Dallas, TX • On-site, Remote

Full-time

Re-posted 23 days ago

Job description

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.
We are looking for a motivated and passionate Machine Learning Engineers for our team.
Job Description:
As a Senior ML OPS Engineer, you will be joining a team of experienced Machine Learning Engineers that support, build, and enable Machine capabilities across the organization. You will work closely with internal customers and infrastructure teams to build our next generation data science workbench and ML platform and products. You will be able to further expand your knowledge and develop your expertise in modern Machine Learning frameworks, libraries and technologies while working closely with internal stakeholders to understand the evolving business needs. If you have a penchant for creative solutions and enjoy working in a hands-on, collaborative environment, then this role is for you.
Requirements
What you'll do in the role:
  • Implement scalable and reliable systems leveraging cloud-based architectures, technologies and platforms to handle model inference at scale.
  • Deploy and manage machine learning & data pipelines in production environments.
  • Work on containerization and orchestration solutions for model deployment.
  • Participate in fast iteration cycles, adapting to evolving project requirements.
  • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
  • Leverage CICD best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
  • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
  • Collaborate with Data scientists, software engineers, data engineers, and other stakeholders to develop and implement best practices for MLOps, including CI/CD pipelines, version control, model versioning, monitoring, alerting and automated model deployment.
  • Manage and monitor machine learning infrastructure, ensuring high availability and performance.
  • Implement robust monitoring and logging solutions for tracking model performance and system health.
  • Monitor real-time performance of deployed models, analyze performance data, and proactively identify and address performance issues to ensure optimal model performance.
  • Troubleshoot and resolve production issues related to ML model deployment, performance, and scalability in a timely and efficient manner.
  • Implement security best practices for machine learning systems and ensure compliance with data protection and privacy regulations.
  • Collaborate with platform engineers to effectively manage cloud compute resources for ML model deployment, monitoring, and performance optimization.
  • Develop and maintain documentation, standard operating procedures, and guidelines related to MLOps processes, tools, and best practices.

Basic Qualifications:
  • Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.
  • Typically requires 7+ years of hands-on work experience developing and applying advanced analytics solutions in a corporate environment with at least 4 years of experience programming with Python.
  • At least 3 years of experience designing and building data-intensive solutions using distributed computing.
  • At least 3 years of experience productionizing, monitoring, and maintaining models

Must have skills:
  • Understanding of Azure stack like Azure Machine Learning, Azure Data Factory, Azure Databricks, Azure Kubernetes Service, Azure Monitor, etc.
  • Demonstrated expertise in building and deploying AI/Machine Learning solutions at scale leveraging cloud such as AWS, Azure, or Google Cloud Platform.
  • Experience in developing and maintaining APIs (e.g.: REST).
  • Experience specifying infrastructure and Infrastructure as a code (e.g.: Ansible, Terraform).
  • Experience in designing, developing & scaling complex data & feature pipelines feeding ML models and evaluating their performance.
  • Ability to work across the full stack and move fluidly between programming languages and MLOps technologies (e.g.: Python, Spark, DataBricks, Github, MLFlow, Airflow).
  • Expertise in Unix Shell scripting and dependency-driven job schedulers.
  • Understanding of security and compliance requirements in ML infrastructure.
  • Experience with visualization technologies (e.g.: RShiny, Streamlit, Python DASH, Tableau, PowerBI).
  • Familiarity with data privacy standards, methodologies, and best practices.

Benefits
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

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