Senior Machine Learning Engineer

Description

Senior Machine Learning Engineer

About Hitachi Social Innovation

The Social Innovation Business (SIB) addresses the world’s most challenging social and environmental challenges. By focussing on more efficient usage of assets and systems, we extract value to reach outcomes that matter for business and society – what we call the double bottom line. Combining 100+ years of experience in operational technology (OT) and 60+ years in IT, we harness Hitachi’s broad capabilities in R&D to deliver cutting edge AI and IOT solutions in the core areas of transport, manufacturing and energy.

The Mobility Accelerator is part of Hitachi’s Social Innovation Business and is set-up to develop new socially beneficial technologies in the area of future mobility.

This role is for a Senior Machine Learning Engineer to join the ‘Intelligent Infrastructure’ team inside of the Mobility Accelerator. This team is developing a portfolio of products which leverage Hitachi’s existing rail capabilities, turning passenger trains into mobile monitoring systems capable of predicting and diagnosing faults in the railway. In doing so, we aim to increase the safety for those working on the railway and reduce unscheduled delays. Starting in the UK, it is envisaged that successful trials will result in a global roll-out.

Of particular focus is the use of train-mounted video cameras for a range of use cases including to assess the health of the railway tracks, overhead electrification equipment, and vegetation incursion.

Role Overview

We are looking for a Senior Machine Learning Engineer to join our video analytics delivery team, with experience in deploying and maintaining our analytics solutions in production at scale.

Responsibilities:

Define and implement analytics infrastructure and tools for deployment

• Design and develop deployment agnostic analytics solutions, whether it is distributed at scale, edge, or on individual compute nodes
• Write production-level code, including testing
• Research and implement best practices, including MLOps, code standards, model test strategies, etc.

Deploy models and algorithms to production

• Improve and/or optimize existing models and algorithms for production
• Implement algorithm libraries and code structures
• Schedule and monitor workflows
• Version control code, models, experiments, and metadata
• Monitor model performances and drifts

Develop analytics solutions and ML models

• Engage in problem solving and data science workstreams

Essential skills and experiences for this role:

• Track record of project experience in applying, scaling, and productionizing data science techniques to solve business/research problems
• Experience in productionizing deep learning and time series analytics solutions
• Proficient at Python software engineering, including experience in code standards, code profiling, code optimization and testing
• Proficient at PySpark, Structured Streaming, Delta Tables
• Proficient at relevant data science libraries (e.g. Sklearn, Pandas, Scipy, Statsmodels, OpenCV)
• Proficient at relevant deep learning libraries (e.g. PyTorch, Keras, TensorFlow)
• Proficient in database technologies, including SQL
• Competent in Azure and DataBricks
• Competent in Docker and Kubernetes
• Competent in Linux
• Competent in Git
• Competent in agile development
• Understanding of machine learning, deep learning, and statistics
• Proficient in English

Nice to have skills and experiences for this role:

• Competent in Cython and C++
• Competent in Spark and Scala
• Experience with TorchServe, ONNX
• Experience with MLflow
• Understanding of computer vision techniques

Expected characteristics for this role include:

• Self-going
• Proactive
• Open-minded
• Driven
• Speaks up
• Eager to learn

Benefits Package

Company Funded Benefits

Along with a market competitive salary and discretionary bonus scheme, employees have the option to work flexibly in line with our hybrid working model and we would be happy to discuss this with you during the hiring process.

• Generous holiday entitlement - with the option to buy up to an additional 5 days per year
• A Holiday Banking scheme allowing you to bank untaken holiday to use another year
• Group Personal Pension
• Private Medical Insurance with self-funded option to cover family members
• Employee Assistance Programme available to all employees
• Personal Accident Insurance

Voluntary Benefits (funded by employee) including;

• Cycle To Work scheme
• Gym Membership
• Dental Insurance with option to include dependent children
• Health screening
• Dining card

Along with a market competitive salary and discretionary bonus scheme, employees have the option to work flexibly in line with our hybrid working model and we would be happy to discuss this with you during the hiring process.