Machine Learning Engineer

Job Title: Machine Learning Engineer 

Reporting To: VP Data and AI 

Location: Bristol - Hybrid 2+ days in office per week

Salary: £60,000 - £80,000 Depending on skills and experience

As a Machine Learning Engineer at Beam you'll report to Cate Seale, our VP of Data and AI. You'll be responsible for designing, developing, and deploying advanced ML models, primarily in the marine and renewable energy domains.

This role involves building robust, scalable, and high-performing ML systems, with an emphasis on computer vision, autonomy, and edge ML applications.

As a key contributor, you are responsible for innovation across the model lifecycle, from data preparation and rapid experimentation to deployment and monitoring.

In addition to model development, ML Engineers help optimize and enhance our MLOps infrastructure and CI/CD pipelines. Staying at the forefront of advancements in ML and MLOps is a vital aspect of your work, as you integrate emerging techniques and tools to maximise impact on business objectives.

You will make a significant impact by delivering efficient and accurate data processing and interpretation, enabling next-generation capabilities in autonomy and computer vision, and helping to establish Beam as a leader in sustainable marine and renewable technologies.

We’ll welcome your ideas & input and support your development, In addition, this is an incredible opportunity to help further the transition to renewable energy.

Beam is an exciting and dynamic environment meaning these are likely to change as we grow. Upon joining your objectives and responsibilities will include: 

• Deploy and Manage ML Products – Maintain and optimize CI/CD pipelines, ensuring continuous integration and safe, reliable model releases.
• Monitor and Improve Model Performance – Proactively evaluate deployed models, identify issues, and implement enhancements.
• Drive Innovation and Experimentation – Stay updated with ML/AI advancements, prototype new concepts, and integrate emerging techniques.
• Hands-on ML Engineering – Develop model architectures, data pipelines, and leverage containerization/orchestration (e.g., Docker, Kubernetes).
• Ensure Code Quality and Best Practices – Conduct code reviews, advocate performance optimizations, and mentor team members
• Collaborate in Agile Environments – Work cross-functionally, participate in Agile workflows, and refine processes for better ML solution delivery.

You should apply if you have:

• Proven experience designing, training, and deploying ML models in production environments
• Strong experience with MLOps practices and tooling (e.g., Docker, GitHub Actions, DVC/CML, CI/CD pipelines).
• Strong experience with ML for unstructured data, such as image, video, point cloud, sonar, radar, magnetometer, or seismic data.
• Technical expertise in AI: Deep Learning, Machine Learning, Statistics.
• Strong proficiency with Python (or similar), with a commitment to high-quality coding standards
• Excellent awareness of software engineering and coding best practices
• Passion for building scalable and reliable ML systems

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.

Grow together with Beam where you may learn or build on your expertise in these skills:

• Knowledge or experience with Autonomous Surface Vehicles and Autonomous Underwater Vehicles
• Deploying ML on edge devices
• Real-time inference and Edge ML
• Working with large language models
• Reinforcement learning
• Marine or geospatial domains
• AWS or other cloud platforms
• PyTorch, PyTorch Lightning, OpenCV, CVAT, Docker, ROS
• Edge computing frameworks like TensorRT

About Beam

At Beam, we bring the technology to transform offshore wind through AI and robotic automation, alongside the determination to tackle the significant challenges ahead. We’re committed to making the transition to renewable energy a reality.

Through industry-defining R&D and transformative partnerships, we’re reshaping what it means to work in offshore wind. Beam is making wind farm development more efficient, reducing risk, complexity and cost, while helping to cure an unsustainable dependence on oil and gas.

Check out the Latest Beam Updates

Together, we are Beam. And we’re leading the charge towards a sustainable future.

Benefits

People join Beam because they are excited by the possibility of leaving their own mark on the world and developing solutions that solve real world problems. Although we share the same vision, we value varied perspectives and adapt to fit different people from all walks of life. Not only does that make for a genuinely awesome team of colleagues, but it also makes day-to-day life more interesting, and it’s how we keep evolving and getting better at what we do.

We believe in flexibility, career growth, and a work culture that empowers you. Here’s what you get at Beam:

• Flexible & hybrid working (up to 3 days from home).
• 33 days annual leave, increasing 2 days a year up to 43 days after 6 years.
• Private medical insurance (including Dental & Optical and 4X Life Assurance).
• Up to 10% company bonus & pension contributions up to 6%.
• Curiosity Fund – £500 annually for personal development outside of work.
• Volunteering day to give back to your community.
• Enhanced Maternity & Adoption leave previous time with a new family
• Cycle to work and get yourself a new bike.
• Recognition & rewards for great work and living our values

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

Interview Process

Our process is straightforward and transparent. We use anonymized recruitment to ensure fairness.

1. Apply: Submit your application & answer key questions.
2. Aptitude Test: Showcase your critical thinking & problem-solving skills
3. Talent Partner Interview: Learn more about the role & discuss your experience.
4. Team Interview: Meet team members & discuss technology, skills, and challenges. 
5. Executive Conversation: Meet with an executive leader to discuss expectations.
6. Offer! Join Beam and be part of something bigger. 

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