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Machine Learning Engineer Jobs in Euless, TX (NOW HIRING)

Omni Inclusive

Machine Learning

Dallas, TX · On-site

Machine Learning - Decision Trees, Random Forests, Rule Mining, Clustering, PCA, Support Vector ... Programming & Scripting - Python, R, Unix-Shell scripting, PySpark

Cisco

Principal Machine Learning Engineer

Dallas, TX

$291K - $369K/yr

Partner with executive leadership, engineering, product, and data science teams to ensure AI ... Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) * Experience ...

Performacentric

ML Engineer

Dallas, TX · On-site +1

Machine Learning Engineer (Llama AI Platform) Location: Remote (Preferred U.S. Time Zones) Employment Type: Full-Time Company: Performacentric About Performacentric Performacentric helps small and ...

ClifyX

AI/ML Engineer

Dallas, TX

AI/Client Engineer Further requirements and responsibilities are as follows ... Design Enterprise Machine Learning platforms that are capable of running predictive models.

Resolve Tech Solutions

Senior ML Engineer

Addison, TX

$101K - $138K/yr

Develop machine learning models and algorithms to address business needs. Collaborate with data scientists and software engineers to design and implement scalable and efficient solutions. Clean ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Euless, TX

Machine Learning Engineer information

See Euless, TX salary details

$29.1K

$119.2K

$179K

How much do machine learning engineer jobs pay per year?

As of Jun 14, 2026, the average yearly pay for machine learning engineer in Euless, TX is $119,152.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,900.00 and $143,400.00 per year, depending on experience, location, and employer.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
What job categories do people searching Machine Learning Engineer jobs in Euless, TX look for? The top searched job categories for Machine Learning Engineer jobs in Euless, TX are:
What cities near Euless, TX are hiring for Machine Learning Engineer jobs? Cities near Euless, TX with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Euless, TX as of June 2026, with employment types broken down into 97% Full Time, 2% Part Time, and 1% Contract. Highlights an 88% Physical, 5% Hybrid, and 7% Remote job distribution, with an average salary of $119,152 per year, or $57.3 per hour.
AI and Machine Learning Engineer

AI and Machine Learning Engineer

SynergisticIT

Fort Worth, TX

$109K - $131K/yr

Other

Posted 17 days ago

Job description

Machine Learning And Artificial Intelligence Developer

Synergistic IT is a full-service staffing and placement firm servicing clients in America for the past 12+ years. We are dedicated towards fulfilling the IT needs of our clients. From staffing to full implementation of projects we provide the highest quality IT Services. We don't just help you secure a Tech Job, but we build your solid career in technology.

You will be responsible for Machine Learning and Artificial Intelligence application development through its lifecycle, from concept and design to coding, testing, and maintenance.

You will also play a leading role, as part of a multidisciplinary team, to design and deliver enterprise AI and Client solutions to clients using our proprietary AI Machine.

We develop real-time prediction (regression and classification) and clustering systems. Depending on the type of applications, the AI and Client models operate on daily, hourly, down to 1 minute and millisecond streaming data.

Primary Responsibilities

As an AI team member you are expected to fulfill the following range of responsibilities, depending on the project:

  • Develop, debug and maintain Client and AI software applications written in Python ecosystem, SciKit-Learn, TensorFlow, Keras, PyTorch.
  • Design Client and Deep AI Models for different types of data (time-series, sales, business data, images, etc.) and different output types (Classification, Regression, Clustering).
  • Create stream learning models for forecasting, prediction, classification, anomaly detection, etc.
  • Investigate the behaviour of input and output data numerically.
  • Investigate and optimize models performance.
  • Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.
  • Work within a multidisciplinary team to understand clients business, data, and requirements and develop the appropriate AI or Client solution within our proprietary AI Machine.

Required Candidate Profile

Skills Required:

  • High fluency in English is a must since you will communicate and work with team members and clients in English.
  • Deep understanding of Client algorithms like regression, classification and clustering.
  • Deep understanding of model determination and evaluation.
  • Strong problem-solving mindset and ability to develop creative solutions for difficult problems often requiring detailed investigation of the code and data.
  • Interest in learning and coding within an advanced distributed micro-system architecture.

Education Requirement:

  • Bachelors, Masters in Computer Science/ Computer Engineering/ Information Systems/Information Technology/ Electrical Engineering/ Mechanical Engineering.

Benefits of working with our clients:

  • E-Verified.
  • Filing of H1b and Green Card.
  • Long Term Positions.
  • On Job Technical Support.

Candidates who are missing the required skills, might be provided an option to enhance their skills, so that they can also apply for the role and can make a career in IT industry.

If you do respond via e-mail, please include a daytime phone number so that we can reach you. In considering candidates, time is of the essence, so please respond ASAP. Thank you

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