Job Specifications
Job Overview
DeGould requires a communicative Head of Machine Learning to lead the delivery and scaling of our Machine Learning products. The role assists with model quality, MLOps implementation, and the transition from R&D to production, working closely with Product, R&D, and Engineering leadership.
They will lead and support team leads while championing best practices in Machine Learning across the organisation.
Duties & Responsibilities
Improving our Spec Check and Defect Detection Products.
Delivering both above by leading on implementation of our Machine Learning Products through the application of MLOps.
Being responsible for the delivery and quality of the models we deliver to our customers across our Products.
Working closely with the Head of Product and CTO in formation of a new delivery team for Data Science.
Working closely with our R&D and Product teams to make sure there’s a clear delivery path from R&D concept to deliverable product.
To manage your team leaders effectively and provide them with the feedback they need to be accountable leaders of their products.
To build and set best practices for the deployment of pipelines for training detection, segmentation and/or classification machine learning models.
To drive and champion adoption of best practices for Machine Learning across the organisation.
Skills
Ability to communicate effectively about complex technical problems to stakeholders at multiple levels.
To be able to engage with their team and other stakeholders within the business to drive change and improve outcomes (to act as a multiplier beyond their own ability to act).
Strong knowledge of Python (numpy, pandas, seaborn, matplotlib, dvc, streamlit, opencv and more).
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, Tensorflow, Nvidia TAO (TLT).
Working knowledge of core AWS concepts and services such as EC2, ECS, EKS, or Cloudwatch.
Good knowledge of DevOps and MLOps tools, including usage of CI/CD pipelines (e.g. GitHub Actions).
Technical understanding of CNNs including YOLOv4/v5, Detectron2 or similar.
Technical knowledge of relevant ML performance metrics and how to apply them to monitor performance.
About the Company:
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. As the company embarks on an exciting growth phase the company plans to expand the team, further develop existing products, and explore opportunities for new ones.
Benefits:
Competitive salary and benefits including:
Flexible working can be agreed.
25 days holiday per annum (excluding bank holidays).
Life assurance/death in service of 4 times basic salary
Additional days holiday for birthday.
Company sick pay scheme.
Cycle to work scheme.
Pension auto enrolment after 3 months service.
Enhanced maternity, paternity and shared parental leave.
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:
Empathy – able to put themselves in the shoes of others.
Creative – open to new ideas and demonstrates good design skills in their work.
Analytical - capable of working through the detail when required.
Flexible - 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.
We do not require additional support from recruiters, thank you.
About the Company
DeGould Ltd is a privately held British company that has received significant global investment.
In 2012 founder Dan Gould deemed the process of renting a car and the well-known handover and inspection process to be outdated and inconsistent. Using his background in digital imaging he set out to find a solution and developed an automated photo booth.
In 2014 Jaguar Land Rover approached DeGould looking to solve a similar problem in their supply chain, a problem shared by all OEMs both in manufacturing and finished vehicle ...
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