AI Trainer - STEM (Life Sciences)

Planet Pharma; Coalville; On-site; GBP 55,000 - 90,000; Full time

Job summary

Planet Pharma is seeking an experienced AI Coder / AI Response Evaluator to review and improve AI-generated outputs across STEM disciplines. The role is fully remote with self-directed scheduling and no fixed hours.

The ideal candidate has 5+ years of substantive STEM experience, strong analytical and data interpretation skills, and familiarity with MATLAB, Python, and engineering tools. Master’s or PhD is preferred.

Qualifications

• Five or more years of substantive applied experience in a STEM field.
• Experience in industry, government research, or advanced academic settings.
• Advanced training or publications in a STEM discipline are advantageous.

Responsibilities

• Evaluate AI-generated responses within your STEM area for accuracy and practicality.
• Assess technical accuracy, reasoning, and applicability of outputs.
• Review analyses, engineering solutions, and experimental methodologies.
• Compare AI outputs and identify best matches to professional standards.
• Provide clear written feedback and recommendations for improvement.
• Apply domain expertise to ensure alignment with scientific principles.
• Work independently in a fully remote environment following project guidelines.

Skills

Analytical thinking

Experimental design

Data interpretation

Statistical reasoning

Domain expertise in STEM

Education

Master's degree

PhD (preferred)

Tools

MATLAB

Python

RSolidWorks

AutoCAD

SPICE

GIS platforms

Chromatography software

Spectroscopy software

Job description

About the Company

We are seeking experienced Science, Technology, Engineering, and Mathematics (STEM) professionals to support the development of next-generation Artificial Intelligence systems.

About the Role

As an AI Coder / AI Response Evaluator, you will use your professional expertise to review, assess, and improve AI-generated responses across a range of scientific and engineering disciplines. This project is designed for professionals with real-world industry or advanced research experience who can apply technical judgment to evaluate the accuracy, quality, and practicality of AI-generated outputs. The assignment is fully remote, offers self-directed scheduling, and does not involve shift work, patient care responsibilities, or fixed working hours.

Responsibilities

• Evaluate AI-generated responses within your area of scientific or engineering expertise.
• Assess the technical accuracy, completeness, logical reasoning, and practical applicability of AI outputs.
• Review scientific analyses, engineering solutions, calculations, experimental methodologies, and technical explanations.
• Compare multiple AI-generated responses and determine which solution best meets professional standards.
• Identify inaccuracies, methodological flaws, statistical errors, and unsupported conclusions.
• Provide clear written feedback explaining evaluation decisions and recommended improvements.
• Apply domain expertise to ensure responses align with accepted scientific and engineering principles.
• Collaborate with project guidelines while working independently in a fully remote environment.

Qualifications

• Professional Experience: Five or more years of substantive applied experience in a STEM field such as:
• Mechanical Engineering
• Electrical Engineering
• Civil Engineering
• Chemical Engineering
• Materials Science
• Environmental Science or Engineering
• Energy Engineering
• Physics
• Applied Sciences
• Related scientific, technical, or engineering disciplines
• Industry experience, government research, laboratory experience, product development, field engineering, consulting, or advanced academic research are all considered relevant. Undergraduate study alone does not count toward the minimum experience requirement.

Required Skills

Technical Expertise: Hands-on experience working with real-world scientific or engineering data, including:

• Instrumentation and test data
• Measurement and sensor outputs
• Laboratory records and experimental datasets
• CAD models and engineering drawings
• Simulation and modelling outputs
• Scientific or analytical software outputs

Experience using one or more relevant technical tools such as:

• MATLAB
• Python
• RSolidWorks
• AutoCAD
• SPICE
• GIS platforms
• Chromatography software
• Spectroscopy software
• Other discipline-specific engineering or scientific analysis tools

Analytical Skills: Strong understanding of:

• Experimental design
• Measurement uncertainty and error analysis
• Statistical reasoning
• Data interpretation
• Scientific methodology
• Common analytical and statistical pitfalls

The entrance assessment will evaluate these skills.

Preferred Skills

• Master's degree, PhD, or equivalent advanced training in a STEM discipline.
• Experience publishing scientific or technical research.
• Experience reviewing technical reports, engineering documentation, scientific publications, or research outputs.
• Familiarity with modelling, simulation, validation, verification, or quality assurance activities.
• Previous exposure to AI-assisted workflows or machine learning technologies.

Pay range and compensation package

Compensation: Paid Entrance Assessment (3-4 Hours) + Paid Hours Worked Throughout the Assignment.

Equal Opportunity Statement

We are committed to diversity and inclusivity in our hiring practices.