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

Master's degree in Computer Science or a related discipline with a focus on AI or machine learning is preferred. • 3 to 5 years of software engineering experience, including hands-on development of ...

DevOps Engineer

Tyler, TX · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

Software Engineer

Tyler, TX · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

Frontend Engineer

Tyler, TX · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

Mobile Software Engineer

Tyler, TX · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

Staff Software Engineer

Tyler, TX · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

Senior Software Engineer

Tyler, TX · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

Full Stack Engineer

Tyler, TX · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

QA Engineer - AI Trainer

Tyler, TX · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

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Showing results 1-20

Machine Learning Engineer information

See Tyler, TX salary details

$29.7K

$121.3K

$182.3K

How much do machine learning engineer jobs pay per year?

As of Jun 8, 2026, the average yearly pay for machine learning engineer in Tyler, TX is $121,343.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,600.00 and $146,100.00 per year, depending on experience, location, and employer.

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.

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.

What jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.
What cities near Tyler, TX are hiring for Machine Learning Engineer jobs? Cities near Tyler, TX with the most Machine Learning Engineer job openings:
AI Engineer - Full Stack

AI Engineer - Full Stack

Fortegra

Jacksonville, TX • On-site

Full-time

Posted yesterday


Job description

Job Summary:
Fortegra is seeking an Internal AI Forward Deployed Software Engineer to stay ahead of cutting-edge AI developments and advise on integrating AI solutions into their platforms. The role involves rapidly prototyping proofs-of-concept and collaborating with various technology teams to enhance their AI capabilities.
Responsibilities:
• Monitor and stay current with the AI technology landscape, including new models, frameworks, tools, and research across areas such as LLMs, multimodal AI, agentic systems, and orchestration platforms, to inform internal recommendations and solution design.
• Operate with flexibility across software and data initiatives, contributing where business needs and priorities are most critical. Adapting readily to support both software engineering and data-focused projects as priorities and requirements shift will be integral to the role. Data-focused projects involve supporting our data infrastructure in terms of platform enhancements or building new data processes to support business needs.
• Engage with internal stakeholders to identify high-value AI opportunities, define use cases, and rapidly prototype tailored solutions that integrate with our APIs, data pipelines, and internal platforms for workflows such as analytics, automation, and decision support.
• Advise teams on the selection and implementation of AI solutions by assessing trade-offs across accuracy, latency, scalability, security, and cost, and guide the evolution of prototypes into production-ready applications.
• Own end-to-end delivery of AI initiatives, from ideation and scoping through prototyping, testing, deployment, monitoring, and iterative optimization in internal production environments. Build a sharp eye for continuously validating AI-driven processes and evaluating their outputs for accuracy, effectiveness, and trustworthiness.
• Identify reusable patterns, shared components, and platform enhancement opportunities emerging from AI projects, and partner with core engineering teams to improve maintainability, scalability, security, and operational resilience.
• Conduct workshops, demos, and knowledge-sharing sessions to educate teams on AI best practices, emerging tools, and Fortegra's evolving AI capabilities, helping drive organization-wide adoption and responsible usage.
• Operate effectively across multiple high-priority initiatives, contributing as an engineer, technical advisor, researcher, and communicator in a fast-moving and often ambiguous environment.
Qualifications:
Required:
• Bachelor’s degree in Computer Science or a related field required; Master’s degree in Computer Science or a related discipline with a focus on AI or machine learning is preferred.
• 3 to 5 years of software engineering experience, including hands-on development of AI-enabled applications and solutions using modern cloud-based AI platforms such as Azure Machine Learning or Azure AI Studio. Experience with Azure is strongly preferred.
• Proven track record of rapidly building POCs and advising on AI integration strategies, with strong knowledge of current AI trends, leading model families, evaluation approaches, and practical enterprise use cases.
• Experience with developer tooling such as Claude Code, GitHub Copilot, and Cursor is required.
• Strong full-stack engineering skills, including proficiency in React-based web development and the ability to review, understand, and refine AI-generated code. Experience designing or implementing agentic workflows is highly valued. Familiarity with FastAPI is preferred.
• Experience working with frontier models from providers such as OpenAI, Anthropic, and Google within a Git-based development environment. Familiarity with GitHub-based CI/CD workflows and the use of AI tools for automated testing, including tools such as Playwright, is strongly preferred.
• Demonstrated ability to work with speed and flexibility across multiple priorities, debug complex AI-driven systems, and deliver effective solutions under tight timelines.
• Strong communication and stakeholder management skills, with the ability to work effectively in matrixed organizations and translate complex technical concepts for both technical and non-technical audiences.
• Clear commitment to continuous learning, with an established habit of staying current on AI developments through research papers, newsletters, hands-on experimentation, and industry forums.
Preferred:
• Insurance or Financial Services domain experience
• Experience building AI-enabled products or developer tooling
• Familiarity with LLMs, AI agents, and prompt engineering
• Experience with serverless and cloud-native architectures
Company:
For more than 45 years, Fortegra and its subsidiaries have delivered risk management solutions that help people and businesses succeed in the face of uncertainty. Founded in 1978, the company is headquartered in Jacksonville, Florida, US, , with a team of 501-1000 employees. The company is currently Late Stage.