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Fall Machine Learning Co Op Jobs in Houston, TX (NOW HIRING)

NobleAI

Lead Machine Learning Engineer

Houston, TX · Remote

$104K - $138K/yr

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI ... Remote-first with co-working access at Industrious offices * 401(k) with employer match * Equity ...

NobleAI

Lead Machine Learning Engineer

Houston, TX · On-site +1

$97K - $128K/yr

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI ... Remote-first with co-working access at Industrious offices * 401(k) with employer match * Equity ...

Turner Construction

Intern - Houston

Houston, TX · On-site

$14.25 - $19/hr

Where applicable, your assignment will support learning that applies to earning educational credits. Essential Duties & Key Responsibilities:Depending on business need and location, the Intern/Co-Op ...

Turner Construction

Intern - Houston

Houston, TX

$14.25 - $19/hr

Where applicable, your assignment will support learning that applies to earning educational credits. Essential Duties & Key Responsibilities:Depending on business need and location, the Intern/Co-Op ...

Visual Comfort & Co.

AI Engineer III

Houston, TX · On-site

$124K - $132K/yr

Visual Comfort & Co. is the premier resource for decorative and architectural lighting, ceiling ... Duties include designing and developing machine learning models and AI capabilities, integrating ...

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All JobsFall Machine Learning Co Op JobsFall Machine Learning Co Op Jobs in Houston, TX

Fall Machine Learning Co Op information

See Houston, TX salary details

$24.4K

$40.7K

$84K

How much do fall machine learning co op jobs pay per year?

As of Aug 14, 2026, the average yearly pay for fall machine learning co op in Houston, TX is $40,666.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,000.00 and $43,900.00 per year, depending on experience, location, and employer.

What is a Fall Machine Learning Co Op?

A Fall Machine Learning Co-Op is a temporary, typically full-time position for students or recent graduates to gain hands-on experience in applying machine learning techniques. These roles usually involve working with data, training models, and optimizing algorithms under the supervision of experienced engineers or researchers. They are offered during the fall semester and can last several months. Companies use these positions to provide practical learning opportunities and assess potential future hires.

What can I expect from the day-to-day experience of a Fall Machine Learning Co Op?

As a Fall Machine Learning Co Op, you'll typically work with a team of data scientists and engineers on real projects that may involve data cleaning, model development, testing, and reporting insights. Your days might include collaborating in meetings, coding, analyzing data, and presenting findings to team members or supervisors. You'll receive mentorship from experienced professionals and have opportunities to participate in code reviews and brainstorming sessions. This structure helps you build technical skills, broaden your professional network, and gain a comprehensive understanding of how machine learning is applied in a business setting.

What are the key skills and qualifications needed to thrive in the Fall Machine Learning Co Op position, and why are they important?

To thrive as a Fall Machine Learning Co Op, you should have a solid background in programming (especially Python), statistics, and machine learning concepts, often supported by coursework or hands-on projects in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, and data analysis libraries such as pandas and scikit-learn is highly valued, while certifications in AI or data science can be a plus. Strong problem-solving skills, eagerness to learn, effective communication, and teamwork help you stand out in this role. These skills are crucial for contributing to real-world projects, collaborating with technical teams, and gaining valuable experience in a fast-paced, innovation-driven environment.

What are popular job titles related to Fall Machine Learning Co Op jobs in Houston, TX?

For Fall Machine Learning Co Op jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching Fall Machine Learning Co Op jobs in Houston, TX look for?

The top searched job categories for Fall Machine Learning Co Op jobs in Houston, TX are:

What cities near Houston, TX are hiring for Fall Machine Learning Co Op jobs?

Cities near Houston, TX with the most Fall Machine Learning Co Op job openings:

Fall Machine Learning Co Op jobs near you
Infographic showing various Fall Machine Learning Co Op job openings in Houston, TX as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $40,666 per year, or $19.6 per hour.

Lead Machine Learning Engineer

NobleAI

Houston, TX • Remote

$104K - $138K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 17 days ago

Job description

At NobleAI, we believe that energy, material science and chemistry are key to building a sustainable world and that artificial intelligence is essential to unlock this potential. NobleAI leverages innovative Science-Based AI technology to revolutionize energy workflows, materials development, and chemical designs. We enable companies to accelerate innovation and reduce costs in developing sustainable technologies and products.

We're a team of excellence-driven individuals who value thoughtfulness and respect while focusing on delivering products that empower engineers and researchers to create better solutions faster.

At NobleAI, we are developing the next generation of intelligent chemical informatics platform. Our goal is to create a seamless, intuitive experience that empowers users to achieve unprecedented productivity in data processing, visualization, and model building. We are seeking a forward-thinking team member who thrives on innovation, collaboration, and rapid iteration, and has the ability to solve challenging problems in science and technology.

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI, you will be responsible for architecting, building, and deploying intelligent features to our VIP platform. This role is ideal for individuals passionate about the cutting edge of LLMs and eager to build AI systems that can reason, plan, and act.

Join us in building a more sustainable world through the power of AI and scientific innovation.

Requirements

  • Design domain specific AI systems and chatbots capable of complex dialogue management and workflow execution via tools, API calls and multi step tasks based on user goals, multi-agent orchestration.
  • Collaborate with scientists to assess, fine-tune, and deploy LLMs on domain specific data to support accuracy measurement for use cases
  • Build and maintain Retrieval-Augmented-Generation (RAG) systems, Reinforcement Learning frameworks, guardrail and assessment mechanisms for end to end lifecycle for customized models.
  • Collaborate with product and software engineers to integrate the features into our platform.
  • Establish prompt engineering and data management best practices for transparency and governance.
  • Establish best practices for monitoring and evaluation of data and models across the model lifecycle (development, testing, and production)
  • Keep a pulse on the latest advancements in NLP, LLMs, and agentic AI research, and act as a subject matter expert on architecture decisions on platform and use cases.


What We’re Looking For

  • MSc (preferred) or BSc in Computer Science, Artificial Intelligence, or a related quantitative field.
  • 5+ years of hands-on experience building and deploying AI/ML systems, with a strong focus on Natural Language Processing (NLP).
  • Proven experience designing and shipping chatbots, virtual assistants, or agentic systems using modern LLM-based architectures.
  • Strong programming proficiency in Python (5+ years) and deep experience with core ML/NLP libraries such as PyTorch, TensorFlow
  • Hands-on experience with LLM agent frameworks for building complex, tool-using applications, multi-agent orchestration, or establishing MCP services for platform capabilities.
  • Demonstrated experience with Retrieval-Augmented Generation (RAG), including the use of vector databases like Pinecone, Weaviate, or ChromaDB.
  • Familiarity with techniques for fine-tuning LLMs (e.g., LoRA/QLoRA) and experience working with open-source models (e.g., Llama, Mistral) or major model APIs (e.g., OpenAI, Anthropic).
  • 5+ years of experience with cloud platforms (Azure preferred) and familiarity with deploying AI models as scalable microservices using Docker and Kubernetes (KFP, KServe).
  • Solid software engineering fundamentals, including version control (Git), automated testing, and CI/CD principles.
  • Excellent communication skills with the ability to articulate complex technical ideas to both technical and non-technical stakeholders.

Benefits

We offer great pay & benefits. 

  • Top-tier health benefits coverage, including medical, dental, vision, disability and life insurance
  • Flexible paid time off & generous holidays
  • Remote-first with co-working access at Industrious offices
  • 401(k) with employer match
  • Equity package
  • Salary Range $190,000 - $205,000 (Depending on experience & Geographic location)
  • Performance-based bonus plan