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Python Ai Ml Jobs in Texas (NOW HIRING)

... Python and AI/ML libraries (OpenAI, Hugging Face, Azure AI) 4 Required Experience integrating LLMs via APIs Knowledge of AI governance, model lifecycle management, and evaluation 4 Required ...

Develop, train, and optimize ML models using Python, PySpark, MLflow, and Databricks Machine ... engineering, or AI/ML architecture roles. * Deep expertise in Databricks on AWS, including:

Key Responsibilities AI/ML & Advanced Analytics Develop, train, and optimize ML models using Python ... PySpark, MLflow, and Databricks Machine Learning. Conduct exploratory data analysis (EDA) to ...

AI ML Developer 1 Key Responsibilities: - Design, develop, and deploy machine learning models for ... in Python and core machine learning libraries (e.g., scikit-learn, PyTorch, TensorFlow ...

AI/ML Engineer

Dallas, TX · On-site

$113K - $136K/yr

About the Role:- We are seeking a talented and innovative AI/ML Engineer to design, develop, and ... Strong programming skills in Python. Experience with Machine Learning libraries such as: TensorFlow ...

AI/ML Engineer

Dallas, TX · On-site

$113K - $136K/yr

About the Role:- We are seeking a talented and innovative AI/ML Engineer to design, develop, and ... Strong programming skills in Python. Experience with Machine Learning libraries such as: TensorFlow ...

AI/ML Engineer

Dallas, TX · On-site

$113K - $136K/yr

About the Role:- We are seeking a talented and innovative AI/ML Engineer to design, develop, and ... Strong programming skills in Python. Experience with Machine Learning libraries such as: TensorFlow ...

AI/ML Engineer

Dallas, TX · On-site

$113K - $136K/yr

About the Role:- We are seeking a talented and innovative AI/ML Engineer to design, develop, and ... Strong programming skills in Python. Experience with Machine Learning libraries such as: TensorFlow ...

They are seeking an AI/ML Scientist responsible for building generative AI and large language ... Python and machine learning frameworks such as PyTorch, TensorFlow, Hugging Face, and libraries ...

Java with AI ML ENgineer

Dallas, TX · On-site

$51.25 - $70.25/hr

Develop and maintain backend microservices using Python, Java and Spring Boot * Build and integrate ... RESTful ML APIs, TensorFlow Serving or Vertex AI Endpoints) * Experience working with structured ...

Role: Principal Consultant - AI/ML Location - Houston, TX (Hybrid, Needs to be able to travel to ... Python (NumPy, Pandas, scikit-learn, TensorFlow/PyTorch) * Experience with real-time and batch ...

New

Senior AL/ML Engineer

Texas City, TX · On-site

$89K - $122K/yr

Mandatory Skills Strong hands-on experience in AI/ML development and implementation. Proficiency in Python, R, or Java. Expertise in deep learning frameworks: TensorFlow, PyTorch, or Keras.

Showing results 41-60

Python Ai Ml information

What is a Python AI ML engineer?

Python AI/ML engineers are professionals who use Python programming language to design, develop, and implement artificial intelligence (AI) and machine learning (ML) algorithms and models. Their work involves analyzing data, building predictive models, and deploying machine learning solutions to solve real-world problems. They are skilled in libraries such as TensorFlow, PyTorch, and Scikit-learn, and often collaborate with data scientists and software engineers. These engineers play a key role in transforming data into actionable insights and AI-powered applications.

What are the key skills and qualifications needed to thrive as a Python AI ML engineer, and why are they important?

To thrive as a Python AI/ML Engineer, you need strong proficiency in Python programming, a solid background in mathematics and statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), version control systems, and cloud platforms is typically required, along with relevant certifications being advantageous. Analytical thinking, problem-solving, and effective communication are essential soft skills that help translate business needs into technical solutions. These skills ensure the development of accurate, scalable, and efficient AI/ML models that deliver value to organizations.

How does a Python AI ML engineer typically collaborate with data engineers and domain experts during a project?

Python AI/ML professionals frequently work closely with data engineers to ensure data pipelines are robust, clean, and optimized for modeling. They also collaborate with domain experts to understand business needs, refine problem statements, and interpret results in the context of real-world applications. Effective communication and regular meetings are essential, as these collaborations help bridge technical and business perspectives, ensuring that machine learning solutions are both technically sound and aligned with organizational goals.
What job categories do people searching Python Ai Ml jobs in Texas look for? The top searched job categories for Python Ai Ml jobs in Texas are:
What cities in Texas are hiring for Python Ai Ml jobs? Cities in Texas with the most Python Ai Ml job openings:
Infographic showing various Python Ai Ml job openings in Texas as of August 2026, with employment types broken down into 80% Full Time, 17% Part Time, and 3% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution.

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 4 days ago


Job description

Nelnet is a diversified and innovative company committed to enriching lives through the power of service as a student loan servicer, professional services company, consumer loan originator and servicer, payments processor, renewable energy solutions, and K-12 and higher education expert. For over 40 years, Nelnet has been serving its customers, associates, and communities.

The perks of working at Nelnet go beyond our benefits package. When you join the Nelnet team, you're part of a community invested in the success of each individual. That support comes through in our work, as we are united by our mission of creating opportunities for people where they live, learn, and work.

At Nelnet, we believe in the transformative power of data and technology to drive business innovation. Our AI / ML Engineer role sits at the center of that work: building, operating, and scaling the AI agents that automate processes, surface insights, and help our teams make better decisions faster. If you're passionate about taking agentic systems from prototype to dependable production capability, we invite you to join our team and help shape how AI gets used across our business.
This posting covers multiple levels within the AI / ML Engineer role. We are currently seeking candidates at the equivalent of a Level I or II AI / ML Engineer. The responsibilities and qualifications below describe the full scope of the role; expectations for depth, autonomy, and scope of ownership will vary by level. Level and corresponding compensation are determined during the interview process based on demonstrated experience. We encourage you to apply if you meet the core qualifications, even if you don't match every item listed.Role Overview

As an AI / ML Engineer at Nelnet, you'll be at the intersection of applied AI and software engineering. Your primary focus will be twofold: keeping our existing fleet of deployed agents healthy, evaluated, and improving over time, and designing new agentic capabilities that extend what those systems can do. Beyond building, you'll help expand the agentic approach across the organization, partnering with business stakeholders to identify high-value use cases, establishing reusable patterns and guardrails, and raising the bar for how teams evaluate and ship AI systems. You'll collaborate closely with Data Scientists, Product, Software Engineers, and business partners to move solutions from concept to production.

Job Responsibilities

1. Agent Development: Design, build, and deploy LLM-powered agents to solve concrete business problems. This includes tool use, multi-step reasoning, orchestration, and human-in-the-loop patterns.
2. Operating the Existing Fleet: Own the day-to-day health of agents already in production: monitor behavior, diagnose failures, tune prompts and tooling, and manage model and dependency upgrades without regressing quality.
3. Evaluation: Build and maintain evaluation suites for agent systems, including offline test sets, LLM-as-judge scoring, regression testing, and online metrics.
4. Observability and Monitoring: Instrument agents end to end, including traces, tool calls, token usage, latency, cost, and outcome quality and act on what the data shows.
5. Context and Retrieval Engineering: Design retrieval and context strategies (RAG, structured data access, caching, chunking, ranking) that give agents the right information at the right time.
6. Tooling and Integrations: Build and maintain the tools, APIs, and connectors agents rely on, ensuring safe and reliable interaction with internal systems and data.
7. Scalability and Infrastructure: Design and implement scalable AI pipelines and services on AWS, using infrastructure as code (Terraform) and CI/CD to automate deployment and maintenance.
8. Guardrails and Responsible AI: Implement safety controls, input/output validation, access boundaries, and audit trails appropriate to a regulated environment.
9. Expanding Agentic Adoption: Partner with teams across the organization to identify where agents add real value, prototype quickly, and turn one-off wins into reusable frameworks and standards.
10. Documentation: Maintain clear documentation of agent architectures, prompts, tool contracts, data flows, evaluation results, and known limitations.
11. Innovation: Track the fast-moving foundation model and agent tooling landscape, and bring what's genuinely useful into our stack.
12. Mentorship: Provide guidance to team members on agent design, evaluation practices, and applied AI best practices.

Key Competencies

1. Strong programming skills in Python.
2. Working knowledge of AWS services for AI workloads (e.g., Bedrock, Lambda, ECS/Fargate, S3, OpenSearch, Step Functions).
3. Familiarity with agent frameworks and orchestration tooling, and sound judgment about when a framework helps versus when to build directly.
4. Practical prompt and context engineering skill, with an evaluation-driven approach to improving them.
5. Experience with infrastructure as code (IaC) tools like Terraform.
6. Proficiency using CI/CD pipelines to automate testing and deployment of AI workflows.
7. Experience with containerization technologies like Docker and orchestration tools like Kubernetes.
8. Solid grounding in machine learning fundamentals and statistical reasoning, sufficient to evaluate systems rigorously and know when a non-LLM approach is the better answer.
9. Excellent problem-solving skills and the ability to work in a collaborative environment.
10. Strong critical thinking, analytical, and quantitative problem-solving ability.
11. Strong organization, time management, and coordination skills to drive projects to completion.
12. Ability to communicate AI capabilities and limitations clearly to non-technical stakeholders.
13. Ability to lead end-to-end development of new products.

Nelnet believes in a hybrid work environment that accommodates both in-office and remote work. This model promotes a positive work-life balance and culture, enabling in-person collaboration when possible while also providing benefits associated with remote work. The standard hybrid work schedule includes a 24/16 hour (in-office/work-from-home) split for associates that reside within 30 miles of an office.This is subject to change, based on manager discretion.

At this time, we are unable to consider external candidates that reside in these states: Alabama, California, Connecticut, Hawaii, Illinois, Maine, Massachusetts, Michigan, New Jersey, New York, Oregon, Rhode Island, Vermont, Washington.

Qualifications

Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field (or equivalent experience).

U.S. Citizenship AND the ability to obtain a U.S. 6C Security Clearance.

Minimum of 2 years of experience in machine learning engineering, AI engineering, software engineering, or related roles.

Demonstrated experience building agentic systems with large language models. Examples include tool calling, orchestration, multi-step workflows - not just single-turn prompting.

Hands-on experience evaluating LLM and agent systems, including designing eval sets and interpreting results to drive iteration.

Experience deploying and supporting AI or ML systems in production environments.

Experience with retrieval-augmented generation and other approaches to grounding models in enterprise data.

Starting Salary Range for this Role: $95k - 130k

Our benefits package includes medical, dental, vision, HSA and FSA, generous earned time off, 401K/student loan repayment, life insurance & AD&D insurance, employee assistance program, employee stock purchase program, tuition reimbursement, performance-based incentive pay, short- and long-term disability, and a robust wellness program. Click here to learn more about our benefits: Benefits & Perks - Nelnet Inc.


Nelnet is committed to providing a welcoming and respectful workplace where all associates have the opportunity to succeed. As an Equal Opportunity Employer, we ensure that all qualified applicants are considered for employment. Employment decisions are made without regard to race, color, religion/creed, national origin, gender, sex, marital status, age, disability, use of a guide dog or service animal, sexual orientation, military/veteran status, or any other status protected by federal, state, or local law. We value the unique contributions of every team member and believe that a positive work environment benefits everyone.


Qualified individuals with disabilities who require reasonable accommodations in order to apply or compete for positions at Nelnet may request such accommodations by contacting Corporate Recruiting at 402-486-5725 orcorporaterecruiting@nelnet.net.


Nelnet is a Drug Free and Tobacco Free Workplace.


Use of Artificial Intelligence in Hiring


We may use automated or artificial intelligence enabled tools to assist with the initial review of applications, such as identifying relevant skills or experience. These tools are used to support human review and do not make hiring decisions. A recruiter reviews applications and determines which candidates move forward in the hiring process. For more information, see our Privacy Policy and Pre-Use Notice: Automated Tools in Hiring