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Freelance Full Stack Machine Learning Engineer Jobs in Houston, TX

Lead Machine Learning Engineer

Houston, TX ยท Remote

$104K - $138K/yr

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 ...

Lead Machine Learning Engineer

Houston, TX ยท On-site +1

$97K - $128K/yr

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 ...

Full Stack Engineer

Houston, TX ยท On-site

$100K - $130K/yr

Full Stack Engineer - WhiteWater Express Car Wash (Houston, TX) - Fullโ€‘Time - Onโ€‘Site Location: 106 Vintage Park Blvd., Houston, TX 77070 Reports to: Senior Director of Data Engineering Salary ...

If so, Alliance HCM is looking for a full-time Full Stack Developer to join our team in The Woodlands, TX. This is your opportunity to play a key role in the continued growth and evolution of ...

If so, Alliance HCM is looking for a full-time Full Stack Developer to join our team in The Woodlands, TX. This is your opportunity to play a key role in the continued growth and evolution of ...

As a Full Stack Developer, you will be responsible for developing and maintaining our company's web and mobile applications. This is a full-time, permanent position with the opportunity for growth ...

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training project by creating reinforcement learning environments that evaluate AI models on complex software ...

Showing results 41-60

Freelance Full Stack Machine Learning Engineer information

See Houston, TX salary details

$42.5K

$128.7K

$181.9K

How much do freelance full stack machine learning engineer jobs pay per year?

As of Sep 10, 2026, the average yearly pay for freelance full stack machine learning engineer in Houston, TX is $128,702.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,000.00 and $150,900.00 per year, depending on experience, location, and employer.

What is the difference between Freelance Full Stack Machine Learning Engineer vs Freelance Data Scientist?

AspectFreelance Full Stack Machine Learning EngineerFreelance Data Scientist
CredentialsProficiency in programming, machine learning, and full stack developmentStrong statistical, analytical, and programming skills, often with data analysis certifications
Work EnvironmentDevelops and deploys ML models, works on both front-end and back-end systemsAnalyzes data, builds models, and provides insights, mainly focusing on data analysis
Industry UsageUsed in tech, finance, healthcare for deploying ML solutionsUsed across industries for data analysis, reporting, and predictive modeling

Freelance Full Stack Machine Learning Engineers focus on building and deploying machine learning models within full stack applications, combining software development with ML expertise. Freelance Data Scientists primarily analyze data and create models for insights. While both roles require programming skills, the engineer's role emphasizes deployment and integration, whereas the data scientist's role centers on analysis and interpretation.

What are the most commonly searched types of Full Stack Machine Learning Engineer jobs in Houston, TX?

The most popular types of Full Stack Machine Learning Engineer jobs in Houston, TX are:

What job categories do people searching Freelance Full Stack Machine Learning Engineer jobs in Houston, TX look for?

The top searched job categories for Freelance Full Stack Machine Learning Engineer jobs in Houston, TX are:

What cities near Houston, TX are hiring for Freelance Full Stack Machine Learning Engineer jobs?

Cities near Houston, TX with the most Freelance Full Stack Machine Learning Engineer job openings:

Infographic showing various Freelance Full Stack Machine Learning Engineer job openings in Houston, TX as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 75% Full Time, 22% Part Time, and 1% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $128,702 per year, or $61.9 per hour.

Lead Machine Learning Engineer

Houston, TX โ€ข Remote

NobleAI
IT Servicesย โ€ขย 11 - 50 employees

$104K - $138K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 15 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