Maritime ML Engineer: Production AI for ships (Equity)

Ceto AI Limited; Greater London; Hybrid; GBP 54,000 - 66,000; Full time

Benefits offered by this job

Equity options

Holiday allowance

Birthdays off

Medical insurance

Cycle to work

Home office stipend

Conference budget

Job summary

Ceto AI Limited in London is seeking a Data Scientist / ML Engineer to turn vessel data into actionable insights. You will work across the full data science pipeline, from data cleaning to feature engineering, model training and deployment, helping current customers and new ones.

You will build production data science pipelines, apply time-series and supervised/unsupervised modelling, and collaborate with engineering to improve the analytics stack. Hybrid working in London offered.

Qualifications

• Physics or physics-based degree required.
• Proven production ML experience with CI/CD.
• Strong background in time-series and supervised learning.
• Startups experience and fast-paced environment.
• Experience building production data pipelines.
• Ability to map models to physical maritime problems.

Responsibilities

• End-to-end data science pipelines: cleaning, feature engineering, model training, deployment.
• Maintain production pipelines and experiment tracking.
• Collaborate with engineering for analytics stack improvements.
• Apply time-series models and anomaly detection.
• Explore predictive maintenance ideas and production features.
• Work with cross-functional team and communicate results.

Skills

Production ML

Time-series ML

Supervised learning

Unsupervised learning

CI/CD

DevOps

Feature engineering

Model deployment

Experiment tracking

Version control

Communication

Education

Physics degree

Tools

Azure

AWS

GCP

MongoDB

MLflow

Job description

Ceto AI Limited in London is seeking a Data Scientist / ML Engineer to turn vessel data into actionable insights. You will work across the full data science pipeline, from data cleaning to feature engineering, model training and deployment, helping current customers and new ones.

You will build production data science pipelines, apply time-series and supervised/unsupervised modelling, and collaborate with engineering to improve the analytics stack. Hybrid working in London offered.