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Remote Machine Learning Engineer Jobs in Keller, 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 ...

Lockheed Martin

AI/ML Engineer

Fort Worth, TX · On-site +1

... machine learning. • Strong background in signal processing theory and application (radar ... Remote work arrangements may also be considered for qualified candidates. #LMLAIC Qualifications ...

Tiger Analytics Inc.

ML Ops Architect

Dallas, TX · Remote

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 ...

Lockheed Martin

AI EW Engineer

Fort Worth, TX · On-site +1

... machine learning. • Strong background in signal processing theory and application (radar ... Remote work arrangements may also be considered for qualified candidates. #LMLAIC Qualifications ...

Photon

AWS Gen AI / ML Engineer - Plano, TX

Plano, TX · On-site +1

AWS Gen AI / ML Engineer We are seeking an AWS Gen AI / ML Engineer to design, deploy, and optimize cloud-native machine-learning systems that power our next-generation predictive-automation platform.

Lockheed Martin

AI RF Engineer

Fort Worth, TX · On-site +1

... machine learning. • Strong background in signal processing theory and application (radar ... Remote work arrangements may also be considered for qualified candidates. #LMLAIC Qualifications ...

Lockheed Martin

Senior AI Engineer

Fort Worth, TX · On-site +1

$117K - $154K/yr

... machine learning. • Strong background in signal processing theory and application (radar ... Remote work arrangements may also be considered for qualified candidates. #LMLAIC Qualifications ...

Lockheed Martin

Senior AI Engineer

Fort Worth, TX · On-site +1

$117K - $154K/yr

... machine learning. • Strong background in signal processing theory and application (radar ... Remote work arrangements may also be considered for qualified candidates. #LMLAIC Qualifications ...

Waabi

Research Engineer

Dallas, TX · On-site +1

$122K - $215K/yr

Qualifications: - Bachelor's in computer science, engineering, machine learning, or a related technical discipline. - Experience working on applied research projects. - Passion for taking research ...

Waabi

Research Engineer

Dallas, TX · On-site +1

$122K - $215K/yr

Qualifications: - Bachelor's in computer science, engineering, machine learning, or a related technical discipline. - Experience working on applied research projects. - Passion for taking research ...

Waabi

Research Engineer

Dallas, TX · On-site +1

$122K - $215K/yr

Qualifications: - Bachelor's in computer science, engineering, machine learning, or a related technical discipline. - Experience working on applied research projects. - Passion for taking research ...

TECHOAUTH SOLUTIONS LLC

Senior Data Engineer

Fort Worth, TX · On-site +1

$70K - $120K/yr

Senior Data Engineer Company: Techoauth Solutions LLC Location: Fort Worth, TX (Hybrid) Job Summary ... machine learning data platforms Work Environment * Hybrid work model (Fort Worth office + remote ...

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 ... Python programming with a focus on writing high-quality, well-structured, and tested code ...

WEX

Sr. Staff AI/ML Engineer

Dallas, TX · On-site +1

$220K - $255K/yr

This is a remote position ; however, the candidate must reside within 30 miles of one of the ... Lead the design, implementation, and production deployment of machine learning and AI-driven ...

eNett

Sr. Staff AI/ML Engineer

Dallas, TX · On-site +1

$220K - $255K/yr

This is a remote position ; however, the candidate must reside within 30 miles of one of the ... Lead the design, implementation, and production deployment of machine learning and AI-driven ...

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 ...

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All JobsRemote Machine Learning Engineer JobsRemote Machine Learning Engineer Jobs in Keller, TX

Remote Machine Learning Engineer information

See Keller, TX salary details

$28.6K

$116.9K

$175.7K

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

As of Jun 16, 2026, the average yearly pay for remote machine learning engineer in Keller, TX is $116,948.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,200.00 and $140,800.00 per year, depending on experience, location, and employer.

What are some typical challenges faced by Remote Machine Learning Engineers, and how are they addressed?

Remote Machine Learning Engineers often face challenges such as coordinating across different time zones, ensuring smooth communication with team members, and accessing large datasets or secure environments remotely. Organizations commonly address these by using robust collaboration tools (like Slack, GitHub, and Jira), establishing clear documentation, and setting regular virtual meetings to maintain alignment. Many companies also provide secure remote environments or VPN access for handling sensitive data and code. Proactive communication and organized workflows help mitigate these challenges, enabling engineers to remain productive and connected to their teams.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $500,000 or more annually, especially in high-cost-of-living areas or within top tech companies. Achieving this level often requires a strong track record, specialized certifications, and sometimes equity or bonuses as part of compensation packages.

Which 5 jobs will survive AI?

Remote Machine Learning Engineers are likely to continue to be in demand as AI advances, since they develop and maintain AI models and systems. Jobs that require complex problem-solving, creativity, and emotional intelligence, such as healthcare professionals, educators, and skilled trades, are also expected to persist. Additionally, roles involving oversight, ethical considerations, and human interaction will remain essential despite automation.

What are the key skills and qualifications needed to thrive in the Remote Machine Learning Engineer position, and why are they important?

To thrive as a Remote Machine Learning Engineer, you need a strong background in computer science, mathematics, and experience with machine learning algorithms, typically supported by a relevant degree and prior project work. Proficiency with programming languages like Python, machine learning frameworks such as TensorFlow or PyTorch, and familiarity with cloud computing platforms is crucial, and certifications like AWS Certified Machine Learning can enhance your profile. Excellent communication, self-motivation, and time-management skills are also essential for collaborating across remote teams and meeting project goals. These combined technical and soft skills are vital for developing effective machine learning solutions while ensuring productivity and collaboration in a virtual work environment.

What is a Remote Machine Learning Engineer job?

A Remote Machine Learning Engineer designs, develops, and deploys machine learning models while working from a remote location. They preprocess data, train and optimize models, and integrate them into production systems. Their role often involves collaborating with data scientists, software engineers, and stakeholders to solve complex problems using AI. Strong programming skills in Python, experience with ML frameworks like TensorFlow or PyTorch, and cloud computing knowledge are essential. Remote ML engineers must also communicate effectively and manage their time efficiently to work asynchronously with teams.

Can ML engineers work remotely?

Yes, many machine learning engineers work remotely, especially in roles that involve programming, data analysis, and model development using tools like Python, TensorFlow, and cloud platforms. Remote work arrangements depend on the employer's policies and project requirements, but it is common in the tech industry for ML engineers to work from home or other locations.

Is ML full of coding?

A remote machine learning engineer role typically involves significant coding, especially in languages like Python or R, to develop algorithms and models. However, it also requires understanding data, model evaluation, and sometimes deploying solutions, making coding a core but not the sole component of the job.
What are popular job titles related to Remote Machine Learning Engineer jobs in Keller, TX? For Remote Machine Learning Engineer jobs in Keller, TX, the most frequently searched job titles are:
What cities near Keller, TX are hiring for Remote Machine Learning Engineer jobs? Cities near Keller, TX with the most Remote Machine Learning Engineer job openings:
Remote Machine Learning Engineer jobs near you
ML Ops Architect

ML Ops Architect

Tiger Analytics Inc.

Dallas, TX • On-site, Remote

Full-time

Posted 19 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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