Rovco

Machine Learning Engineer

Rovco Bristol, England, United Kingdom

Are you driven by innovation and a bias for action? Vaarst is the place for you. We're a tech company committed to making a real impact through ground-breaking solutions. Join us and be part of a team that turns ideas into reality.
  
Location: Bristol, Hybrid role with 2+ Days per week in the office

Salary: Up to £75,000 if you have all of the skills & experience we are looking for

Vaarst focuses on making the world a cleaner, greener and safer place by deploying technology for good. We’re using techniques in artificial intelligence, autonomy, computer vision and marine robotics to create a difference in the world with underwater technology for our clients in offshore wind and the subsea industry.

Take a look at one of our products in action

 SubSLAM X2 - Unlocking the Future of Marine Robotics - YouTube

Founded in 2021 by our sister company Rovco, we’ve announced funding of more than £20 million, been voted one of the most innovative and sustainable companies working towards net zero and won awards for Best Use of AI and Best Technology Innovation.

Discover your place in a hybrid team of 120+ people that celebrates diversity knowing that every perspective is a valuable part of our success and that empowers you to achieve a fulfilling work-life balance.  

 

Machine Learning Engineer 

Vaarst is seeking a Machine Learning Engineer to join our Applied ML team. This role is for you if you are passionate about both training ML models and implementing robust, scalable, repeatable practices at all stages of the ML lifecycle.

You will be a key team member helping to deliver ML in production and strategic MLOps initiatives.  

In addition, this is an incredible opportunity to help further the transition to renewable energy.

Objectives & Responsibilities:

Vaarst is an exciting and dynamic environment meaning these are likely to change as we grow, upon joining your objectives and responsibilities will include:

  • Design, develop, and deploy machine learning models in the marine sub-surface domain for computer vision, autonomy, and Edge ML applications.
  • Work on advancing cutting-edge tech in AI, Machine Learning, Computer Vision, and Autonomy.
  • Build ML models that meet performance, reliability, and scalability expectations.
  • Prepare data for ML processing and develop rapid experimentation infrastructure.
  • Contribute to MLOps infrastructure and optimize CI/CD pipelines for efficient ML model deployment and testing.
  • Monitor deployed models for performance, proposing improvements to meet business objectives.
  • Stay up to date with ML and MLOps advancements, assessing their applicability to our goals.


You should apply if you have: 

(we know it’s tough, but please try to avoid the confidence gap. You don’t have to match all the listed requirements exactly to be considered for this role):

  • Proven background designing and deploying ML models in production.
  • Experience with MLOps practices and tooling (e.g., Docker, GitHub Actions, DVC/CML, CI/CD pipelines).
  • Ability to work with ML for image and/or video processing.
  • Technical expertise in AI: Deep Learning, Machine Learning, Statistics.
  • Proficiency with Python and writing high quality code, or strong experience in other languages and a willingness to learn Python.
  • Excellent awareness of software engineering and coding best practices.
  • A Passion for building scalable and reliable ML systems.

 

Grow together with Vaarst, you may have some knowledge of the following, if you don't these are areas you'll develop in. 

  • Knowledge or experience of Autonomous Surface Vehicles and Autonomous Underwater Vehicles.
  • Deployment of ML on edge devices.
  • Previous experience of working with ML for video processing.
  • Experience with large language models.
  • Experience with reinforcement learning.
  • A background in the marine or GIS domains.
  • Exposure to working with AWS or other cloud platforms.
  • Knowledge of PyTorch, PyTorch Lightning, OpenCV, CVAT, Docker, ROS.
  • An understanding of edge computing frameworks like TensorRT.


Benefits

At Vaarst, we’re committed to creating a diverse and inclusive workplace where everyone can thrive. Our hybrid-remote approach and state-of-the-art Bristol Office Hub provide a welcoming space designed to nurture your creativity, productivity and well-being.

In addition, you’ll get an extensive range of benefits so you can focus on doing your very best work:

  • Flexible, hybrid working so you can work when is best for you
  • 25 days annual leave to start with increasing to 35 days after 6 years + bank holidays
  • Private medical insurance, including Dental, optical which can be extended to your family
  • Career and learning development through paid courses, conferences and events
  • Curiosity fund – up to £500 to spend on learning which is not role related
  • Up to 10% company bonus
  • Pension up to 6% company contribution
  • Life assurance 4X base salary
  • Volunteering day, to give back to your local community
  • Enhanced maternity and adoption leave
  • Cycle to work scheme
  • Recognition & rewards for doing great work and living our values and behaviours
  • Flexible working options including, reduced hours, job share, phased return to work, term time working, compressed hours
  • We’re a sociable, tight-knit team with monthly socials
  • Hybrid working, Most teams work in our offices 2+ days a week to collaborate and be hands on with our technology. When you do visit our Bristol office is 10 minute walk from the train station, with a balcony, fresh fruit, snacks and drinks in the office

Join Vaarst in our mission to make the world a cleaner, greener and safer place by deploying technology for good.

Interview Process

At Vaarst, we've designed a straightforward interview process to ensure the best fit for both you and the company. We have adopted anonymised recruitment. This means that your name, date of birth and other personal details will not be seen by the hiring team.

  • Application: Begin by submitting your application with your CV, highlighting your skills and experience relevant to the job. Answer key questions on elements that are important to the role.
  • Talent Partner Interview: We will tell you more about the role, the team and Vaarst’s mission. This is a two-way conversation; we want to learn about your motivation, what you can bring to Vaarst, and provide answers to your questions.
  • Aptitude Test: Demonstrate your critical thinking, problem-solving abilities, and workplace personality through an aptitude test. It includes a timed cognitive exercise and a workplace personality questionnaire.
  • Team Interview: Engage in a 1-hour interview with a few team members. Experience the role firsthand and share your skills and experience. We'll discuss our technologies, key skills, and team dynamics. As always, feel free to ask any questions you may have.
  • CTO Conversation: Meet with our CTO for a 30-minute discussion. This is your opportunity to express your thoughts on the role and ask any final questions. We'll clarify expectations and ensure this role aligns with your aspirations.
  • Offer! If you are successful in the process, you'll receive an offer to join Vaarst and become part of our team.

 

We value the diversity of our teams and are committed to supporting and welcoming individuals from all backgrounds, knowing that every perspective is a valuable part of our success. Should you require any reasonable adjustment throughout the recruitment process, please do not hesitate to let a member of the Talent team know.

Be part of a technology company making a positive impact, apply now

  • Seniority level

    Not Applicable
  • Employment type

    Full-time
  • Job function

    Engineering and Information Technology
  • Industries

    Services for Renewable Energy

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