Machine Learning Engineer

TripleTen; City Of London; Remote; GBP 60,000 - 90,000; Full time

Job summary

A leading educational technology firm is seeking a talented ML engineer to build an AI-powered platform for personalized education. You will define the AI and ML development directions and contribute to shaping how students learn. Candidates should have broad ML expertise and a solid understanding of metrics, as well as experience in production delivery. The position offers full-time remote work with minimal micromanagement.

Benefits

Fully remote work

Professional freedom

Dynamic global team

Qualifications

• Experience training and evaluating ML models for real problems.
• Ability to measure model performance and connect to business outcomes.
• Comfortable working quickly in research and experimentation.

Responsibilities

• Build AI-powered platform for educational personalization.
• Define AI and ML development direction and architectural decisions.
• Prototype solutions and turn successful experiments into production.

Skills

Broad ML expertise

Statistics and ML metrics

Generative AI experience

Prototyping and production delivery

MLOps foundations

Backend engineering and cloud deployment

Tools

MLflow

AWS

GCP

PyTorch

TensorFlow

Airflow

Job description

Were building an AI Tutor a personalized learning system that leverages machine learning to adapt educational content and learning paths for each student.

Were looking for an ML engineer who enjoys fast experimentation and prototyping but also has proven experience delivering end-to-end production solutions with measurable impact. Youll join a cross-functional team of experienced backend and frontend engineers AI developers and UX / UI specialists to create a truly new kind of learning experience.

What you will do

• Build AI-powered platform that personalizes the educational journey for thousands of TripleTen students across the US and Latin America.
• Define the direction of AI and ML development in a new product taking ownership of key architectural and technical decisions.
• Contribute to the content and evolution of the platform itself shaping what and how students learn through data‑driven personalization.
• Prototype quickly validate ideas and transform successful experiments into reliable production systems.

What we can offer you

• Fully remote and full‑time collaboration with professional freedom and minimal micromanagement;
• Dynamic Team: Join a diverse global team with experience across tech, ed‑tech and various industries;
• We use digital tools like Miro, Notion and Google Workspace for seamless collaboration;
• At this time we are unable to offer H‑1B L‑1A / B sponsorship opportunities.
• This job description is not designed to contain a comprehensive listing of activities, duties or responsibilities that are required. Nothing in this job description restricts management’s right to assign or reassign duties and responsibilities at any time.
• TripleTen is an equal employment opportunity / affirmative action employer and considers qualified applicants for employment without regard to race, color, religion, sex, national origin, age, religion, disability, marital status, sexual orientation, gender identity / expression, protected military / veteran status or any other legally protected factor.

Requirements

• Broad ML expertise. Experience training and evaluating different model types to solve real problems such as recommendation, retrieval, ranking or next‑best‑action prediction. Proven depth in one or two specific areas.
• Metrics and evaluation. Strong understanding of statistics and ML metrics; ability to measure model performance and connect it to business outcomes.
• Generative AI experience. Experience building LLM‑based applications that combine models with retrieval or vector databases, external APIs and agentic or workflow‑based approaches (e.g. tool calls MCP).
• Prototyping and production delivery. Comfortable working quickly in research and experimentation with a track record of bringing 12 ML solutions into stable, maintainable production systems.
• MLOps foundations. Experience managing experiments, versioning and monitoring models using MLflow or similar tools.
• Backend and infrastructure. Experience with backend engineering and cloud deployment (AWS, GCP, etc.); understanding how to expose models as scalable services while maintaining code quality, testing and reproducibility.

Nice to have

• Experience with Deep Learning frameworks (PyTorch, TensorFlow, etc.)
• Familiarity with orchestration or data workflow tools (Airflow or similar)

Key Skills

Industrial Maintenance,Machining,Mechanical Knowledge,CNC,Precision Measuring Instruments,Schematics,Maintenance,Hydraulics,Plastics Injection Molding,Programmable Logic Controllers,Manufacturing,Troubleshooting

Employment Type: Remote

Experience: years

Vacancy: 1