hackajob Bristol, England, United Kingdom

Overview

Join to apply for the Machine Learning Engineer role at hackajob. Hackajob is collaborating with Leonardo to connect them with exceptional tech professionals for this role. Leonardo is a global defence company with significant investments across Defence, Transport, Energy, Aerospace, Space and Manufacturing. The Leonardo Cyber & Security Division is focused on delivering technology and services for civil and defence markets, with the Data Practice where this role is positioned.

What you will do as a Machine Learning Engineer

This is a highly rewarding, hands-on role with exposure across traditional and cutting edge enterprise IT as well as bespoke Operational Technology systems. You will work in a dynamic environment with a team focused on delivering innovative solutions to customers within defence, government and commercial sectors. We are seeking creative, technically savvy and collaborative people to help grow our practice and address challenging, critical issues in the UK’s digital landscape.

Skills in Python and machine learning are critical, as well as exposure to the data lifecycle.

The role will include

• Building, integrating, testing and scaling models including NLP and Computer Vision
• Developing, training and productionising machine learning lifecycles, adhering to best practices, security needs and quality assurance
• Development of neural networks
• Implementing and maintaining MLops workflows
• Working with Data Engineers and DevOps Engineers to ensure CI/CD of ML models in production
• Proactive learning and researching new technologies
• Working with cloud technologies and different operating systems
• Collaborating with Data Engineers and DevOps engineers
• Working with big data technologies such as Spark
• Demonstrating stakeholder engagement by communicating requirements of data and products to the team

Essential

What we are looking for:

• UK SC Clearance or the ability to obtain it
• Demonstrable experience developing a variety of machine learning models
• Strong grasp of machine learning frameworks (e.g. PyTorch, Tensorflow)
• Knowledge of machine learning architectures, loss functions, tools and techniques
• Experience training ML models, including hyperparameter tuning and optimizing performance
• Experience with MLops workflows
• Experience with Python
• Experience with SQL
• Critical thinking and problem-solving
• Experience with data warehousing and database systems
• Exposure to CI/CD
• Knowledge of developing data pipelines
• Exposure to ETL (Extraction, Transformation and Load)
• Willingness to learn
• Solid understanding of software engineering principles

Desirable

• UK DV Clearance or the ability to obtain it
• A degree or similar in a STEM, Data, AI or Programming related subject
• Proven track record of AI projects delivering tangible business results
• Experience writing production-level code
• Experience developing neural networks into production
• Experience with Docker
• Experience with NLP and/or computer vision
• Exposure to cloud technologies (e.g. AWS and Azure)
• Exposure to Big Data technologies
• Experience with Apache products (Hive, Spark, Hadoop, NiFi)
• Programming experience in other languages

Security clearance

You must be eligible for full security clearance. For more information visit the UK government site on vetting and clearance levels.

Life at Leonardo

• Flexible working: Hybrid options; part-time opportunities may be discussed
• Company-funded benefits: Private healthcare, dental schemes, Workplace ISA, Go Green Car Scheme, technology and lifestyle options
• Holidays: 25 days plus bank holidays; option to buy/sell leave
• Pension: Employer-contribution pension scheme
• Wellbeing: Employee Assistance Programme and inclusion networks
• Lifestyle: Discounted gym membership; cycle to work
• Training: Access to online courses
• Referral incentives
• Bonus: Applicable at management level and below

For a full list of Company benefits please visit the Leonardo website.

Primary location

GB - Bristol - Coldharbour Lane