Senior ML Engineer – Scientific Analytics

Houston Dose; Houston (TX); Hybrid; USD 130,000 - 180,000; Full time

Job summary

Houston Dose is looking for a Senior Machine Learning Engineer to join its technology team focused on applying AI/ML to analytical laboratory workflows. You will design and deploy ML models to enhance chromatography data interpretation and analytics, collaborating with scientists, software engineers and lab personnel.

You’ll work at the intersection of machine learning, data science and analytical chemistry, building robust data pipelines and keeping up with advances in ML and scientific

Qualifications

• Bachelor’s/Master’s/PhD in a technical field.
• Several years of commercial ML development experience.
• Strong Python programming skills.
• Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).

Responsibilities

• Design, develop and deploy ML models for analytical/lab data challenges.
• Collaborate with scientists and engineers to understand workflows.
• Build data processing pipelines for laboratory-generated data.
• Translate scientific requirements into scalable ML applications.
• Evaluate model performance and improve through testing and optimization.

Skills

Python

Machine learning

Data analysis

ML pipelines

Education

Bachelor's/Master's/PhD in CS/Math/Engineering

Tools

TensorFlow

PyTorch

Scikit-learn

Job description

We are partnering with a global leader in scientific testing and laboratory services to appoint a Senior Machine Learning Engineer to join a growing technology team focused on applying artificial intelligence and machine learning to analytical laboratory workflows.

This is a unique opportunity to work at the intersection of machine learning, data science and analytical chemistry, developing innovative solutions that enhance scientific processes and unlock greater value from laboratory data.

The successful candidate will collaborate closely with analytical scientists, software engineers and laboratory teams to build machine learning models that improve the interpretation and analysis of chromatography data. While this is not a chemistry role, an understanding of analytical laboratory data and a genuine interest in learning laboratory workflows will be essential.

Key Responsibilities

• Design, develop and deploy machine learning models to solve complex analytical and laboratory data challenges.
• Work closely with scientists and laboratory personnel to understand existing workflows and identify opportunities for AI-driven improvements.
• Analyse large scientific datasets, including chromatography outputs, to develop predictive and automated analytical solutions.
• Develop robust data processing pipelines for laboratory-generated data.
• Collaborate with cross-functional teams including software engineering, laboratory operations and scientific leadership.
• Translate complex scientific requirements into scalable machine learning applications.
• Evaluate and improve model performance through continuous testing and optimisation.
• Support the integration of machine learning solutions into existing laboratory systems and software platforms.
• Stay informed of emerging developments in machine learning, artificial intelligence and scientific computing.

Required Experience

• Bachelor's, Master's or PhD in Computer Science, Data Science, Machine Learning, Engineering, Applied Mathematics or a related technical discipline.
• Several years of commercial experience developing and deploying machine learning solutions.
• Strong programming skills in Python.
• Experience with machine learning frameworks such as TensorFlow, PyTorch or Scikit-learn.
• Experience working with large and complex datasets.
• Knowledge of statistical modelling, feature engineering and predictive analytics.
• Experience building production-ready data pipelines and machine learning workflows.
• Strong communication skills with the ability to work across both technical and scientific teams.

Preferred Experience

Experience working with scientific or laboratory data, particularly within industries such as:

• Pharmaceuticals
• Biotechnology
• Clinical Diagnostics
• Contract Research Organisations (CROs)
• Laboratory Testing
• Chemical Manufacturing
• Scientific Instrumentation

Knowledge or exposure to analytical chemistry concepts including:

• Chromatography
• HPLC/UHPLC
• GC or LC-MS
• Chromatograms
• Peak integration
• Retention times
• Analytical laboratory workflows

Experience with cloud platforms (AWS, Azure or GCP) and MLOps practices would also be advantageous.

What We're Looking For This role requires someone who enjoys solving real-world scientific problems and is excited by working alongside laboratory teams. The ideal individual is naturally curious, willing to spend time in the laboratory to understand how data is generated, and able to translate those insights into practical machine learning solutions.

Success in this position comes from combining strong engineering capability with a collaborative mindset and an interest in applying AI to scientific research and laboratory operations.

If you're passionate about using machine learning to transform laboratory science and want to work on highly impactful, data-driven projects within a world-class scientific environment, we'd love to hear from you.