Team:
Tech
Hours:
Full time
Reports to:
Defect Detection Team Lead
Location:
Exeter or Bristol, minimum of 3 days in the office.
Role Overview:
As a Machine Learning Engineer at DeGould you will be responsible for building and maintaining our labelling, training and production inference data pipelines to produce high quality datasets, models and services to power our automated vehicle inspection product. Following MLOps and DevOps best practices you will build and deploy bespoke computer vision ML models using a service-oriented architecture in AWS, GCP and on Edge to process photos from DeGould’s ultra high-resolution imaging photo booths. The objective is to convert this data into useful information that creates value for customers.
DeGould is an exciting, multi-award-winning company, in the software and AI sector. The company develops and delivers innovative vision and damage detection systems to a range of blue-chip corporate clients (including Toyota, Ford, Jaguar Land Rover, Mercedes Benz, Nissan, Honda and Bentley). As the company embarks on an exciting growth phase, it plans to expand the team, further develop existing products, and explore opportunities for new ones.
Our Vision:
DeGould’s vision is to be the standard for new vehicle inspection in the automotive sector.
Key Responsibilities:
The main deliverables of the role are:
Deliver performant machine learning models for customers.
Building capabilities to monitor and evaluate model performance and metrics.
Detailed duties of the role include:
Write production, robust, readable and extendable code to support machine learning pipelines.
Use industry best practices and seek to implement improvements across the machine learning lifecycle.
Continuous evaluation of models in production and system performance analysis.
Proactively seek technical solutions that solve customer problems.
Stay up to date and evaluate opportunities to apply the latest tools, research, methods and technologies.
Work across multidisciplinary teams to deliver against the company’s objectives.
Interpret internal and external business challenges and recommend appropriate system and technology solutions to produce a functional solution.
Identify areas for improvement and development using a full range of software development tools.
Undertaking any other tasks/duties as may be reasonably required to fulfil DeGould’s objectives.
Depending on the individual role, some or all of the following:
Developing and championing robust MLOps frameworks and policies.
Training and maintaining performant vehicle segmentation models.
Labelling tasks and data quality.
Designing and implementing reporting dashboards.
Developing novel approaches from academic and industry research.
Production model deployment and maintenance.
Skills:
Technical expertise in AI for image processing using: deep learning, machine learning, transfer learning, CNNs and transformers, such as Detectron, ConvNext, DETR, DINO or similar.
Technical knowledge of relevant ML performance metrics and how to apply them to monitor models.
Strong knowledge of Python (such as numpy, pandas, matplotlib, streamlit, and opencv).
Strong knowledge of modern programming paradigms (OOP, functional programming etc).
Ability to write clean, robust, readable, error handling and error tolerant code.
Good knowledge of at least one of PyTorch, Keras, or Tensorflow.
Working knowledge of core AWS concepts and services such as EC2, ECS, EKS, and DynamoDB.
Good knowledge of DevOps and MLOps tools, including usage of Git, Bash, UNIX, Docker, containers and CI/CD pipelines (GitHub Actions or similar).
Able to work effectively both as part of a team and individually.
Behaviours:
As an employee of DeGould Ltd, you are required to meet a number of common standards of behaviour, accountabilities and outcomes. In addition, and in relation to this role it is expected that the successful candidate will exhibit these behaviours:
Leadership – leads by example through their own behaviour.
Creative – open to new ideas and unafraid to try new approaches.
Analytical – capable of working through detail and uses data in decision making.
Flexibility – thriving in a fast paced, changing and opportunity rich environment.
Collaborative – enthusiastically works with colleagues and customers alike.
Dependable – deliver on stakeholder commitments in a timely manner.
Benefits:
Competitive salary and benefits including:
25 days holiday per annum (excluding bank holidays).
Additional days holiday for birthday.
Cycle to work scheme.
Pension auto enrolment after 3 months service.
Enhanced maternity, paternity and shared parental leave.
Health insurance with Vitality for employee, spouse and children.
Flexible working can be agreed.
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