Machine Learning Scientist Jobs in Texas
Machine Learning Scientist jobs in Texas are among the most active in the country, concentrated in artificial intelligence research, energy analytics, defense systems, and financial technology across a seniority range from entry-level research engineer through principal scientist. Austin, Dallas, and Houston account for the largest share of openings, where employers like Dell Technologies, ExxonMobil, and Lockheed Martin maintain deep, sustained demand for applied ML talent. The most sought-after specialties in Texas are natural language processing, computer vision, and reinforcement learning for large-scale industrial and enterprise applications. Find a role that fits below and apply directly.
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INTRODUCTION
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
Locations:
Houston, TX - Onsite
About the job you’re considering:
Capgemini is seeking an enthusiastic and driven Junior AI-Native Consultant to join our dynamic Energy & Utilities sector team. This role is designed for emerging talent passionate about leveraging Artificial Intelligence to solve complex industry challenges. You will contribute to innovative projects, applying advanced AI/ML techniques to optimize operations, enhance decision-making, and drive digital transformation for our clients.
We are looking for individuals who possess a strong foundational understanding of AI concepts and have a minimum of 15 months of professional experience within the Oracle Field Service Cloud (OFSC), Oil & Gas, or broader Utilities domain. This is a client-facing role that requires excellent communication and problem-solving skills.
Your Role:
- Collaborate with senior consultants and client teams to identify business challenges and opportunities for AI-driven solutions in the Energy & Utilities sector.
- Assist in the design, development, and deployment of AI/ML models, including Generative AI and Predictive AI solutions.
- Support data collection, cleaning, and preprocessing activities for AI initiatives.
- Work with leading cloud technologies (Azure, AWS, GCP) and their AI/ML services.
- Utilize platforms such as Databricks, PySpark, and modern AI frameworks.
- Develop agentic AI workflows and intelligent agents to automate tasks and improve operational efficiency.
- Participate in client workshops and presentations, effectively articulating technical concepts to diverse stakeholders.
- Contribute to project documentation, reports, and client deliverables.
- Develop reusable assets, demos, and solution accelerators.
- Stay current with emerging AI technologies and industry trends, particularly within the Energy & Utilities landscape.
- Foster a collaborative environment, actively sharing knowledge and best practices within the team.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related quantitative field.
- Minimum of 15 months of professional (non-internship) work experience in data science, AI, or machine learning roles.
- Demonstrable background in the Energy & Utilities sector, specifically with OFSC (Oracle Field Service Cloud), Oil & Gas, or general Utilities industry knowledge.
- Foundational knowledge of Artificial Intelligence, Machine Learning, and Deep Learning concepts.
- Proficiency in at least one AI-centric programming language (e.g., Python).
- Experience with:
- Generative AI concepts (GPT, Claude, LLMs)
- MLOps, model deployment, and monitoring
- LangChain and Retrieval-Augmented Generation (RAG) concepts
- REST APIs, JSON, Authentication, and Integration patterns
- Deployment tools (Azure DevOps, Docker, AWS ECS/EKS/Fargate) and CI/CD pipelines (AWS CloudFormation, CodeDeploy)
- Data engineering principles, including SQL and NoSQL databases (e.g., MySQL, MongoDB, Redis)
- Strong analytical, problem-solving, and critical thinking skills.
- Excellent communication, presentation, and interpersonal skills, with proven ability to engage effectively in client-facing situations.
- Ability to quickly adapt to new technologies and thrive in a fast-paced, evolving environment.
Preferred Qualifications:
- Familiarity with industry-specific tools such as Seeq and historians (e.g., PHD).
- Experience with any of the following:
- data visualization tools and techniques
- Machine Learning frameworks (TensorFlow, PyTorch, scikit-learn)
- NLP
- computer vision
- graph database technology (Neo4J, Ontotext)
- JIRA / Confluence
- Prior project or internship experience in a consulting environment.
The base compensation range for this role in the posted location is: $46,000 to $111,000.
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
- Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
- Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
- Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
- Life and disability insurance
- Employee assistance programs
- Other benefits as provided by local policy and eligibility
Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini’s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.
Disclaimers
Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.
This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.
Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.
Click the following link for more information on your rights as an Applicant in the United States. http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law
Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.
See All 9 Machine Learning Scientist Jobs in Texas
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Find JobsMachine Learning Scientist Jobs by City in Texas
Where Texas roles are concentrated, by current openings.
Machine Learning Scientist Job Market in Texas
A snapshot from current Texas openings, updated as new roles post.
Who's Hiring



Top Industries Hiring
- Technology & Software
What Texas Employers Look For
The qualifications that appear most often in machine learning scientist jobs across Texas.
- Master's or PhD in computer science, statistics, or a closely related quantitative field
- Hands-on experience building and deploying machine learning models in production environments
- Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or scikit-learn
- Experience with large-scale data pipelines, cloud platforms like AWS or Azure, and distributed computing
- Strong background in statistical modeling, probability theory, and applied mathematics
- Ability to communicate complex model results clearly to both technical and non-technical stakeholders
Machine Learning Scientist Jobs in Texas: Frequently Asked Questions
How do you become a machine learning scientist in Texas?
Machine learning scientist is not a licensed profession in Texas, so no state-issued credential is required to work in the role. The standard path is a bachelor's degree in computer science, mathematics, or statistics followed by a master's or doctoral degree with a research focus in machine learning. Texas universities including UT Austin, Texas A&M, and Rice University offer strong graduate programs that feed directly into in-state hiring pipelines at technology, energy, and defense employers.
How much do machine learning scientists make in Texas?
Machine learning scientists in Texas earn a median of about $122,090 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $64,540 for the lowest 10% to over $170,780 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire machine learning scientists in Texas?
Employers hiring machine learning scientists in Texas right now include Photon, Capgemini, and SentiLink, based on current listings on Migrate Mate as of September 2026. Texas's concentration of energy majors, defense contractors, and financial services firms means demand extends well beyond pure technology companies, making the state's ML job market unusually broad by industry.
Which Texas cities have the most machine learning scientist jobs?
Houston, Austin, and Irving have the most machine learning scientist openings in Texas. Austin drives volume through its dense cluster of technology companies and semiconductor firms, Dallas benefits from large financial services and telecom headquarters, and Houston's openings are concentrated in energy analytics and medical research at institutions affiliated with the Texas Medical Center.
Are there remote machine learning scientist jobs in Texas?
Yes, and more than most fields. About 80% of machine learning scientist openings tied to Texas are remote or hybrid as of September 2026, reflecting the role's fundamentally desk-based and collaborative-by-code nature. Research, model development, and experimentation work transfers well to remote settings, while roles involving proprietary data systems or defense clearance requirements are more likely to require on-site presence.
How can I get hired as a machine learning scientist in Texas with little or no experience?
The most realistic entry path is through a research internship or rotational program during a graduate degree, which Texas employers such as Dell, USAA, and ExxonMobil run specifically to pipeline early-career ML talent. Without a graduate degree, transitioning from a data analyst or data engineer role at a Texas company is a common lateral move, especially when paired with a portfolio of independent projects on GitHub. Completing a capstone or publishing research through a Texas university ML lab also signals readiness to hiring teams that otherwise require prior industry experience.
Where can I find and apply to machine learning scientist jobs in Texas?
Migrate Mate lists current machine learning scientist openings in Texas across industries including technology, energy, finance, and defense. Find the roles that match your background and apply directly to the ones that fit.
See All 9 Machine Learning Scientist Jobs in Texas
Find roles in Texas that match your experience and apply in just a few clicks.
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