Senior ML Engineer — Scale AI for Greener Travel

Trainline; Greater London; Hybrid; GBP 60,000 - 90,000; Full time

Benefits offered by this job

Private healthcare

Dental insurance

Share purchase plans

EV scheme

Work-from-abroad policy

Festive time off

Family-friendly benefits

Job summary

Trainline is seeking a Machine Learning Engineer to join a high-performing, deeply technical team that tackles complex problems by uniting Trainline’s data with cutting-edge algorithms to support sustainability initiatives.

You will collaborate with data scientists, software engineers and product managers to design, deploy and monitor ML models at scale in production environments, using Python, Spark and ML tooling.

Qualifications

• Advanced degree in CS, math, statistics or related field.
• Proficiency with Python and Pandas/NumPy/Scikit-learn.
• Experience productionising ML models and AI solutions.
• Experience with Spark.
• Familiarity with CI/CD and DevOps practices.

Responsibilities

• Collaborate in cross-functional teams with data scientists, software, data and product managers.
• Design and deploy ML models and AI solutions at scale with measurable impact.
• Own end-to-end ML lifecycle: data exploration, feature engineering, evaluation, deployment.
• Partner with stakeholders to create data products leveraging Trainline’s datasets and advanced algorithms.
• Create tools and frameworks to accelerate ML product delivery and improve workflows.
• Take an active role in the AI/ML community and foster a culture of learning and experimentation.

Skills

Python

Pandas

NumPy

Scikit-learn

Spark

Docker

Terraform

MLflow

CI/CD

Data wrangling

Statistical methods

Communication

Education

Advanced degree in Computer Science/Math/Statistics

Tools

MLflow

Terraform

Job description

Trainline is seeking a Machine Learning Engineer to join a high-performing, deeply technical team that tackles complex problems by uniting Trainline’s data with cutting-edge algorithms to support sustainability initiatives.

You will collaborate with data scientists, software engineers and product managers to design, deploy and monitor ML models at scale in production environments, using Python, Spark and ML tooling.