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Remote Machine Learning Jobs in Dallas, TX (NOW HIRING)

Trilogy

Senior Software Engineer

Irving, TX · On-site +1

$117.60K - $155.10K/yr

Hybrid -- Trilogy NextGen office (3 days on-site / 2 days remote) Employment: Full-Time -- Direct ... MACHINE LEARNING & AI • Hands-on experience with ML libraries: scikit-learn, XGBoost, LightGBM ...

Vytwo

Senior Data Engineer Remote

Prosper, TX · Remote

$55 - $60/hr

Experience supporting machine learning workflows or analytical data science pipelines * Knowledge of distributed computing concepts and performance tuning This is a remote position.

Ethos Risk Services

IT AI Solution Architect

Irving, TX · Remote

$58 - $76.50/hr

Design and implement scalable AI and machine learning solutions using AWS (including Amazon Bedrock ... This is a primarily remote position working in a home office environment, with a preference for ...

TECHOAUTH SOLUTIONS LLC

Senior Data Engineer

Fort Worth, TX · On-site +1

$70K - $120K/yr

Experience working with AI or machine learning data platforms Work Environment * Hybrid work model (Fort Worth office + remote work) * Standard business hours with occasional on-call support for data ...

PNC Bank

Fraud Model Analyst

Farmers Branch, TX · On-site +1

$45K - $103.50K/yr

... remote work in select geographic locations, subject to approval by PNC. If approved, work must be ... machine learning to predict business outcomes. * Assists with analytical experiments in a ...

UVeye

Team Lead, Customer Support

Dallas, TX · On-site +1

$100K - $120K/yr

... vision, machine learning, and generative AI within the automotive sector. With over $380M in ... The position is fully remote and the working hours are 12:00 PM - 8:00 PM PST. A day in the life ...

New

WEX

Sr. Staff AI/ML Engineer

Dallas, TX · On-site +1

$220K - $255.80K/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 - $255.80K/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 ...

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Remote Machine Learning information

See Dallas, TX salary details

$25.2K

$42.1K

$87.1K

How much do remote machine learning jobs pay per year?

As of May 29, 2026, the average yearly pay for remote machine learning in Dallas, TX is $42,125.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,200.00 and $45,500.00 per year, depending on experience, location, and employer.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

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

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

What are some effective strategies for collaborating with team members while working remotely as a Machine Learning Engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

Is ML full of coding?

Machine Learning (ML) roles often involve significant coding, especially in programming languages like Python or R, to develop algorithms and models. However, some positions focus more on data analysis, feature engineering, or model evaluation, which may require less coding but still involve technical skills and understanding of ML concepts.

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

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

More about Remote Machine Learning jobs
What are the most commonly searched types of Machine Learning jobs in Dallas, TX? The most popular types of Machine Learning jobs in Dallas, TX are:
What job categories do people searching Remote Machine Learning jobs in Dallas, TX look for? The top searched job categories for Remote Machine Learning jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Remote Machine Learning jobs? Cities near Dallas, TX with the most Remote Machine Learning job openings:
Remote Machine Learning jobs near you
Infographic showing various Remote Machine Learning job openings in Dallas, TX as of May 2026, with employment types broken down into 1% Internship, 1% As Needed, 52% Full Time, 42% Part Time, 1% Temporary, and 3% Contract. Highlights an 75% Physical, and 25% Remote job distribution, with an average salary of $42,125 per year, or $20.3 per hour.

ML Architect/ Data Scientist (Inventory Forecasting) - R01563519

Brillio

Dallas, TX • On-site, Remote

$150K - $160K/yr

Part-time

Posted 9 days ago

Job description

About Brillio:

Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction.
Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work certification year after year.

Architect
Primary Skills
  • Azure API Management, Solution Architecture - Azure, Azure DevOps, Azure Storage Queues, Azure PaaS Services, Azure Networking, Azure Logic Apps, Azure Content Delivery Network, Azure App Service, Azure SQL, Azure AD, Azure Virtual Machines
Specialization
  • Azure Architecture: Architect
Job requirements

Job Title: Machine Learning Engineer / Data Scientist (Inventory Forecasting)

Location: Florida (FL) 

Job Summary:
We are seeking a skilled Machine Learning Engineer / Data Scientist with strong experience in classical machine learning techniques and inventory forecasting. The ideal candidate will have hands-on expertise in time series modeling and a good understanding of modern cloud-based ML platforms, particularly Azure AutoML. Experience working with or building agentic (AI-driven autonomous or semi-autonomous) solutions is highly desirable.

Key Responsibilities:

  • Develop and implement forecasting models for inventory and demand planning using classical time series techniques such as ARIMA, SARIMA, and related methods.
  • Analyze large datasets to identify trends, seasonality, and patterns impacting inventory and supply chain performance.
  • Build, train, and deploy machine learning models using Azure AutoML and other Azure-based services.
  • Design and implement scalable, production-ready ML solutions in a cloud environment.
  • Collaborate with cross-functional teams including business stakeholders, data engineers, and product teams to deliver actionable insights.
  • Explore and contribute to agentic AI solutions, including automation and intelligent decision-making systems.
  • Monitor model performance and continuously improve accuracy and efficiency.

Required Skills & Qualifications:

  • Strong experience in classical machine learning and time series forecasting (ARIMA, SARIMA, etc.).
  • Solid understanding of inventory forecasting, demand planning, or supply chain analytics.
  • Hands-on experience with Azure AutoML and Azure ML ecosystem.
  • Proficiency in Python and common ML libraries (e.g., pandas, scikit-learn, statsmodels).
  • Experience with data preprocessing, feature engineering, and model evaluation.
  • Knowledge of deploying ML models in production environments.

Preferred Qualifications:

  • Experience in building or working with agentic/AI-driven autonomous systems.
  • Familiarity with MLOps practices and CI/CD pipelines.
  • Experience with big data technologies and distributed computing frameworks.
  • Strong problem-solving skills and ability to work in a collaborative environment.

Work Model:

  • Hybrid work setup based in Florida (FL).

Nice to Have:

  • Experience in retail, e-commerce, or supply chain domains.
  • Exposure to advanced forecasting techniques or deep learning-based time series models.

#LSR1

$150,000 - $160,000 a year
 
Know what it's like to work and grow at Brillio: Click here
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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