Data & AI

Machine Learning Engineer

Takes machine learning models from prototype to reliable, scalable production systems.

Also known as: ML Ops Engineer, Applied ML Engineer

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What you do

Implements and optimizes machine learning models designed by data scientists or researchers, and builds the training and serving infrastructure around them. Monitors model performance in production, writes production-quality code, and works with standard software engineering practices such as version control, testing, and deployment pipelines.

Typical work environment

Desk-based software engineering environment, typically within a machine learning or AI platform team, working closely with data scientists and backend engineers.

Typical entry point

Junior ML engineer role in a tech company or AI-focused startup, often after some data science or software engineering experience

Relevant subjects

Core

Computer ScienceMathematics

Relevant interests

Core

AI / DataProgramming

Also relevant

Robotics

Useful skills

Python· AdvancedProgramming· AdvancedProblem solving· AdvancedAnalytical thinking· AdvancedData analysis· Intermediate

These are useful, relevant skills to build over time — not a checklist you need to already have.

Common education routes

Bachelor's degree—Computer Science EngineeringPrimary route
Bachelor's degree—Artificial Intelligence & Machine LearningPrimary route
Master's degree—Artificial Intelligence & Machine LearningCommon route
Master's degree—Data ScienceCommon route

These are common routes in, not the only path — and not a university or course recommendation.

Career characteristics

Strong salary potentialDeep technical specialisationHigh job securityGood international mobilityRemote-work friendly

General tendencies for this career, not a guarantee — actual roles vary by employer and location.

Industries

RoboticsSoftwareAIData

Tags

STEMTechnicalHigh-growth

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