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Artificial Intelligence Machine Learning Engineer Jobs in Spring, TX

Diablo Convoy

AI Automation Analyst

Spring, TX · On-site

$130K - $150K/yr

Foundational knowledge of artificial intelligence, machine learning concepts, and AI tools * Hands ... Basic understanding of prompt engineering and structured prompting techniques * Strong written ...

Deloitte

Lead AI and Data Science Engineer II

Houston, TX · On-site

$97K - $128K/yr

... machine learning, and application development to solve high-priority people challenges. You will ... Develop full-stack, web-based data and generative artificial intelligence (GenAI) applications that ...

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Artificial Intelligence Machine Learning Engineer information

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$26.7K

$109K

$163.8K

How much do artificial intelligence machine learning engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for artificial intelligence machine learning engineer in Spring, TX is $108,994.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,900.00 and $131,200.00 per year, depending on experience, location, and employer.

What is an artificial intelligence machine learning engineer?

An Artificial Intelligence (AI) Machine Learning Engineer is a professional who designs, builds, and implements machine learning models and AI systems. They work with large datasets, develop algorithms, and use programming languages like Python or R to enable computers to learn from data and make predictions or decisions. Their work is essential in fields such as natural language processing, computer vision, and robotics. These engineers collaborate with data scientists, software developers, and business stakeholders to deploy AI solutions in real-world applications.

What are some common challenges faced by artificial intelligence machine learning engineers when deploying models to production?

One of the main challenges AI/ML engineers encounter is ensuring that models trained in a controlled environment perform reliably in real-world production settings. This often involves handling issues like data drift, scaling models to handle large volumes of requests, and integrating with existing infrastructure. Collaboration with data engineers and software developers is crucial to streamline deployment, monitor model performance, and address any unexpected behavior quickly. Keeping up with evolving tools and best practices is also important for long-term model maintenance and success.

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

AspectArtificial Intelligence Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, AI, ML, or related; certifications like TensorFlow, AWSBachelor's or higher in CS, Statistics, or related; certifications in data analysis or visualization
Work EnvironmentDevelops AI/ML models, coding, deploying algorithms in software environmentsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, consulting firms

While both roles involve working with data and algorithms, Artificial Intelligence Machine Learning Engineers focus on designing, building, and deploying AI/ML models in software systems. Data Scientists primarily analyze data to extract insights and support decision-making. The roles often overlap but differ in their core focus and daily tasks.

What are the key skills and qualifications needed to thrive as an artificial intelligence machine learning engineer, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Engineer, you need strong programming skills (typically in Python or R), a background in mathematics or statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms, and relevant certifications are highly valuable. Problem-solving ability, creativity, and effective communication are important soft skills that distinguish top performers in this role. These competencies are crucial for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technological environments.
What are popular job titles related to Artificial Intelligence Machine Learning Engineer jobs in Spring, TX? For Artificial Intelligence Machine Learning Engineer jobs in Spring, TX, the most frequently searched job titles are:
What job categories do people searching Artificial Intelligence Machine Learning Engineer jobs in Spring, TX look for? The top searched job categories for Artificial Intelligence Machine Learning Engineer jobs in Spring, TX are:
What cities near Spring, TX are hiring for Artificial Intelligence Machine Learning Engineer jobs? Cities near Spring, TX with the most Artificial Intelligence Machine Learning Engineer job openings:
Artificial Intelligence Machine Learning Engineer jobs near you
Infographic showing various Artificial Intelligence Machine Learning Engineer job openings in Spring, TX as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 23% Part Time, 1% Temporary, and 4% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution, with an average salary of $108,994 per year, or $52.4 per hour.

AI Solutions Architect

Cnpc Usa Corporation

Houston, TX • On-site

Full-time

Re-posted 18 days ago

Job description

Company Profile:

CNPC USA is a subsidiary of China National Petroleum Company and serves as the North American headquarters. Our mission is to drive innovation through advanced research and development of next-generation technologies for oil and gas exploration and production.


Job Summary:

CNPC USA is seeking a highly experienced AI Solutions Architect to lead the design, prototyping, implementation, and integration of artificial intelligence, machine learning, generative AI, and industrial analytics solutions for oil and gas technology applications. This position is a key technical role responsible for translating open-ended business and technical challenges into scalable AI system architectures, decision-support tools, digital workflows, and production-ready analytical solutions.

The ideal candidate will have advanced working knowledge of data analytics, modern machine learning algorithms, foundation models, large language models, vision-language models, small language models, optimization methods, operations research, and modern decision science. This role will work closely with subject-matter experts, product champions, product managers, designers, and software engineers to develop AI-enabled solutions that support CNPC USA technology development, product commercialization, and energy-domain digital transformation.

Key Responsibilities:

  • Conduct exploratory and undirected technology development to address open-ended AI/ML problems and questions in the energy domain.
  • Participate in data science, artificial intelligence, machine learning, industrial analytics, decision science, and operations research initiatives.
  • Develop, prototype, and evaluate solutions using modern deep learning methods, foundation models, generative AI, modern NLP, vision-language models, small language models, and time-series analytics.
  • Research and assess next-generation technologies for inference, predictive modeling, general-purpose data-driven modeling, and optimization of complex systems.
  • Engineer appropriate system-level AI solutions in collaboration with subject-matter experts, product champions, product managers, designers, and software engineers.
  • Work with software engineering teams to integrate AI solutions into business workflows, cloud environments, data platforms, and production applications.
  • Prototype end-to-end data solutions across multiple cross-functional teams in high-visibility roles.
  • Generate innovative ideas, establish new technology development directions, and shape and execute technical projects from concept through deployment.
  • Maintain state-of-the-art knowledge and contribute to technical discussions, architecture reviews, project reviews, and expert assessments in related areas of responsibility.
  • Communicate sophisticated AI concepts, plans, recommendations, and results effectively to management, clients, technical stakeholders, and the broader business community.
  • Prepare oral and written reports, presentations, technical memoranda, project documentation, and executive-level summaries.
  • Work effectively with peers, management, operations groups, and outside organizations to advance technology development and deployment.
  • Participate in relevant technical reviews and audits of projects as requested.
  • Review, mentor, and coach junior team members while defining and promoting standards, best practices, reusable architectures, and lessons learned.
  • Actively disseminate knowledge through webinars, talks, tutorials, technical communities, and internal training activities.


Minimum Education & Experience Requirements:

  • Master's degree in Operations Research, Industrial Engineering, Applied Mathematics, Computer Science, or a related STEM field, or foreign equivalent.
  • Three (3) years of post-baccalaureate experience in the job offered or in any AI/data science-related job title.

Applicants must have three (3) years of experience in each of the following:

  • AI and data science in the decision science and operations research space using software implementation technology.
  • Markov decision process methods and applications.
  • Data mining for analytics and decision making.
  • LLM-based generative AI solution development.
  • Vision-language model and small language model system development.
  • Modern NLP development in AI.
  • Computational intelligence and non-convex optimization techniques.
  • Time-series analysis techniques using statistics and AI.
  • Applied mathematics and statistics.
  • Cloud development tools and cloud environments for AI, data mining, and large-scale data systems.
  • Optimization solver tools, including CPLEX.
  • Programming languages and frameworks for modern AI and data science, including Python, R, TensorFlow, and PyTorch.


Preferred Experience:

  • Experience applying AI/ML, optimization, and decision science to oilfield, drilling, completion, reservoir, production, or other oil and gas related domains.
  • Experience architecting end-to-end AI systems, including data pipelines, model development, model serving, evaluation, monitoring, and workflow integration.
  • Experience with generative AI application patterns such as retrieval-augmented generation, domain-specific copilots, multimodal AI workflows, and human-in-the-loop decision support.
  • Experience translating ambiguous business needs into technical roadmaps, architecture options, proof-of-concept demonstrations, and scalable implementation plans.
  • Experience leading cross-functional technical discussions and mentoring engineers or data scientists on AI solution design and best practices.


Physical Demands:

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential job functions.

While performing the duties of this job, the employee is regularly required to talk or hear. This is a sedentary role; however, some filing, bending and the ability to lift 20 lbs. is required.


Travel:

This position requires 5-10% domestic and international travel for internal workshops, project work sessions, technical workshops, conferences, and customer presentations. Local travel between other CNPC USA locations and testing or partner facilities may be required.


Work Arrangement:

Telecommuting is permitted less than 50% per week within the same geographic location as the assigned CNPC USA office location.


Supervisory Responsibility:

This position has no direct supervisory responsibilities; however, it does act as a mentor and technical point of contact for less experienced engineers, data scientists, and AI/ML team members.

CNPC USA is an Equal Opportunity Employer (EOE). Qualified applicants are considered regardless of race, color, age, sex, sexual orientation, religion, disability, ethnicity, national origin, marital status, veteran status, or any other legally protected status.

Disclaimer: The job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee. Other duties, responsibilities and activities may change or be assigned at any time with or without notice.