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Machine Learning Biomedical Engineer Jobs in Houston, TX

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

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All JobsMachine Learning Biomedical Engineer JobsMachine Learning Biomedical Engineer Jobs in Houston, TX

Machine Learning Biomedical Engineer information

See Houston, TX salary details

$30.1K

$123K

$184.8K

How much do machine learning biomedical engineer jobs pay per year?

As of Sep 15, 2026, the average yearly pay for machine learning biomedical engineer in Houston, TX is $122,971.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,900.00 and $148,000.00 per year, depending on experience, location, and employer.

What does a machine learning biomedical engineer do?

A Machine Learning Biomedical Engineer applies machine learning techniques to solve problems in biology and medicine. They develop algorithms and models to analyze complex biomedical data, such as medical images, genetic information, or sensor readings. Their work supports advancements in diagnostics, treatment planning, and personalized medicine. Typically, they collaborate with clinicians, researchers, and other engineers to design systems that improve healthcare outcomes.

How does a machine learning biomedical engineer typically collaborate with clinicians and researchers in a healthcare setting?

Machine Learning Biomedical Engineers often work closely with clinicians and researchers to develop algorithms that solve real-world medical challenges. Collaboration usually involves understanding clinical needs, translating them into technical requirements, and iteratively refining models based on feedback from medical experts. Regular meetings, interdisciplinary project teams, and direct participation in data collection or validation studies are common. This collaborative environment ensures that technical solutions are both innovative and clinically relevant, making communication and adaptability essential skills.

What are the key skills and qualifications needed to thrive as a machine learning biomedical engineer, and why are they important?

To thrive as a Machine Learning Biomedical Engineer, you need a strong background in biomedical engineering, data analysis, and machine learning, typically supported by a degree in biomedical engineering, computer science, or a related field. Familiarity with programming languages like Python or R, machine learning frameworks (e.g., TensorFlow, PyTorch), and experience with medical imaging or signal processing tools are commonly required. Critical thinking, problem-solving, and the ability to communicate complex technical concepts to interdisciplinary teams are vital soft skills. These abilities are crucial for developing innovative healthcare solutions, ensuring regulatory compliance, and bridging the gap between technology and medicine.

What is the difference between Machine Learning Biomedical Engineer vs Data Scientist in Biomedical Industry?

AspectMachine Learning Biomedical EngineerData Scientist in Biomedical Industry
Required CredentialsDegree in Biomedical Engineering, Computer Science, or related fields; knowledge of machine learning and biomedical dataDegree in Data Science, Statistics, or related fields; proficiency in data analysis and machine learning
Work EnvironmentResearch labs, healthcare institutions, biotech companiesHealthcare analytics firms, research institutions, biotech companies
Employer & Industry UsageDevelops algorithms for medical devices, diagnostics, and treatment planningAnalyzes biomedical data to inform clinical decisions, research, and product development

Both roles require expertise in machine learning and biomedical data, but Machine Learning Biomedical Engineers focus on developing algorithms for medical applications, while Data Scientists analyze biomedical data to support research and clinical decisions.

What are popular job titles related to Machine Learning Biomedical Engineer jobs in Houston, TX?

For Machine Learning Biomedical Engineer jobs in Houston, TX, the most frequently searched job titles are:

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

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

What cities near Houston, TX are hiring for Machine Learning Biomedical Engineer jobs?

Cities near Houston, TX with the most Machine Learning Biomedical Engineer job openings:

Machine Learning Biomedical Engineer jobs near you
Infographic showing various Machine Learning Biomedical Engineer job openings in Houston, TX as of September 2026, with employment types broken down into 8% Internship, 73% Full Time, and 19% Part Time. Highlights an 90% In-person, and 10% Hybrid job distribution, with an average salary of $122,971 per year, or $59.1 per hour.

Senior Machine Learning Engineer

Houston, TX • On-site

Reach Velocity - Emerging Technology ?? ??
See more jobs at Reach Velocity - Emerging Technology ?? ??external

$117K - $154K/yr

Other

Posted 2 days ago

New

Job description

Our client is a large global energy and commodities business operating across international markets.

Technology, data science and machine learning play an increasingly important role across the organisation, and the business is continuing to invest in ML and Generative AI capabilities.

Due to continued growth, they are looking for an experienced Machine Learning Engineer to join their Houston-based Data Science and Machine Learning team.

The Role

This is a hands-on position with exposure across the full machine learning lifecycle.

You will work closely with data scientists, ML specialists, software engineers and commercial teams to identify problems, develop solutions and deploy production-grade machine learning applications.

Projects span machine learning, time-series forecasting, NLP and Generative AI, with the opportunity to work on commercially important problems involving pricing, supply and demand, operational optimisation and other business-critical applications.

You will also play an important role in the continued development and adoption of the organisation's internal Generative AI platform.

Responsibilities
  • Design, develop and deploy end-to-end machine learning and data science solutions.
  • Build production ML systems from data ingestion and feature engineering through model deployment and monitoring.
  • Develop and extend internal GenAI and LLM applications, including integrations, data connectors and prompt engineering.
  • Apply techniques including time-series forecasting, NLP, classification and Generative AI to real-world commercial problems.
  • Build robust, well-tested production-quality Python code.
  • Contribute to ML pipelines, data orchestration and model-serving infrastructure.
  • Integrate ML outputs into existing applications, dashboards and business workflows.
  • Work directly with commercial and operational stakeholders to identify valuable ML opportunities.
  • Communicate model results, assumptions and limitations clearly to non-technical stakeholders.
  • Participate in code reviews, experimentation and technical decision-making.
What We're Looking For
  • 5+ years' industry experience developing and deploying machine learning or statistical models.
  • Strong Python skills for both data science and software engineering.
  • Experience delivering end-to-end ML solutions into production.
  • Strong understanding of supervised and unsupervised learning.
  • Experience with time-series modelling.
  • Experience with NLP, LLMs and Generative AI applications.
  • Experience with frameworks such as PyTorch, scikit-learn and Transformers.
  • Cloud experience, preferably AWS.
  • Experience with modern MLOps practices including Docker/Kubernetes, CI/CD, model deployment and monitoring.
  • Experience with data orchestration tools such as Airflow or Dagster.
  • Strong analytical and problem-solving ability.
  • Comfortable working directly with both technical and non-technical stakeholders.

A Master's degree or equivalent in Computer Science, Statistics, Mathematics, Data Science or another quantitative discipline is preferred.

Experience within energy, commodities trading or financial markets would be beneficial but is not essential.

Additional experience with any of the following would also be valuable:

  • Financial or trading-related time-series modelling
  • Econometric approaches such as ARIMA or cointegration
  • Dash, Streamlit or similar interactive applications
  • Cloud-based ETL/ELT pipelines
The Opportunity

This is an opportunity to join an experienced ML and Data Science team within a large international organisation where machine learning is being applied to complex, commercially important problems.

You will have significant ownership over your work, direct exposure to business stakeholders and the opportunity to help shape how ML and Generative AI are adopted across the organisation.

Location:

Houston, TX

Working Pattern:

5 days per week in the office

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