Job Title: Machine Learning & Data Scientist
Location: Reading, UK (Hybrid)
Salary: Up to £80,000 per annum
About Us: We are dedicated to enhancing the global growth and resilience of renewable energy transmission by delivering intelligent, autonomous robotic monitoring solutions for high-voltage assets. Our mission focuses on supporting power transmission operators worldwide with advanced technologies.
Role Overview: We are seeking a Machine Learning & Data Scientist to join our dynamic team. The ideal candidate will have experience in developing multimodal models and a background in condition monitoring, particularly concerning high-voltage assets. This role offers the opportunity to contribute significantly to the development of AI-powered analytics for autonomous robotic systems.
Key Responsibilities:
* Develop and implement machine learning algorithms, focusing on multimodal data integration.
* Design and deploy predictive models for condition monitoring of high-voltage assets.
* Collaborate with cross-functional teams to integrate AI solutions into autonomous robotic systems.
* Analyze large datasets to extract meaningful insights and inform decision-making.
* Stay abreast of the latest developments in machine learning and apply them to ongoing projects.
Qualifications:
* Bachelor's or Master's degree in Computer Science, Data Science, Electrical Engineering, or a related field.
* Proven experience in developing and deploying multimodal machine learning models.
* Familiarity with condition monitoring techniques, especially in the context of high-voltage assets.
* Proficiency in programming languages such as Python or C++.
* Experience with data visualization tools and techniques.
* Strong problem-solving skills and the ability to work collaboratively in a team environment.
Desirable Skills:
* Experience with autonomous robotic systems.
* Knowledge of the energy transmission sector.
* Familiarity with ISO 27001 standards.
Benefits:
Share option plan
All full-time employees become eligible for participation in the share option plan after 6 months of employment. The share option plan gives employees a real opportunity to share in the success of the business in the longer term, over and above the sense of only working for a monthly wage.
Flexible hybrid working
We allow employees to work in the lab or remote with line-manager approval, as best suits the nature of their role and the work they are performing at any time (i.e. physical aspects of mechanical engineering, such as prototype production, tend to be heavily biased towards in-lab, whereas CAD design work, software architecture design, and sales activities are less so).
Paid vacation time
We offer twenty-five days paid holiday, and 'unlimited' additional unpaid leave. This allows our employees to manage a healthy work life balance, contributing to happy, productive, and engaged employees. Managers retain the right of approval for all holidays (paid and unpaid), allowing us to ensure work capacity in times of peak demand or tight deadlines. Our culture and hiring standards help us identify people that are unlikely to abuse the holiday policy, and, in the rare cases where that might occur we have the opportunity to use performance management to correct any potential abuse or part company with the abusive employee.
Contributory Pension
We provide a workplace pension scheme to help our employees save for their retirement. Employees can elect to make a salary sacrifice to benefit from pension tax incentives, and the business complements the employee contribution with a contribution from the company.
Cycle to work scheme
A cycle to work scheme is a great incentive for employees, allowing them to purchase a bike for work-related commuting as well as non-work leisure activities. The monetary savings for the employee can be significant, and the health benefits can increase employee physical and psychological health which improves work and retention. Furthermore, it contributes to lowering our carbon footprint and even creates employer's national insurance cost savings.
How to apply?
Please send a CV to
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