Senior Machine Learning Engineer

Description

The Senior Machine Learning Engineer will work on cutting‑edge technology that makes a real‑world impact, from developing visual inspection tools to creating autonomous systems operating in challenging environments. You will see your work in action through field trials and deployments while collaborating in a hybrid, team‑oriented setting in central Bristol.

In this role you will design, deploy and optimise machine learning models, prepare data, and build rapid experimentation and MLOps pipelines. You will also monitor model performance, propose improvements and stay up‑to‑date with the latest ML and MLOps advancements.

• Design, deploy, and optimise ML models for robotics applications.
• Build models that meet performance, reliability, and scalability targets.
• Prepare data and develop rapid experimentation infrastructure.
• Contribute to MLOps infrastructure and optimise CI/CD pipelines.
• Monitor deployed models and propose improvements to meet business goals.
• Stay current with ML and MLOps advancements and assess their relevance.

Requirements

We are looking for a creative, self‑reliant and collaborative individual with proven experience delivering production ML models, strong MLOps expertise, and a background in robotics‑focused AI such as image, video, LiDAR, VLMs and LLMs. Proficiency in Python, software engineering best practices and a passion for scalable, reliable systems are essential, while knowledge of autonomous surface/underwater vehicles, edge deployment and cloud platforms is a plus.

• Proven experience delivering production ML models.
• Strong MLOps tooling experience (Docker, GitHub Actions, CI/CD).
• Expertise in ML for robotics (image, video, LiDAR) and VLMs/LLMs.
• Deep knowledge of AI, deep learning, reinforcement learning, and statistics.
• Proficiency in Python and software engineering best practices.
• Knowledge of autonomous surface and underwater vehicles.
• Experience deploying ML on edge devices and generating synthetic data.
• Familiarity with large language models, reinforcement learning, and agentic decision‑making.
• Marine or GIS domain experience.
• Experience with cloud platforms (AWS, Azure) and frameworks (PyTorch, OpenCV, ROS, TensorRT).
• Clear communication of technical concepts to diverse audiences.
• Adaptability to shifting requirements and hybrid work environments.
• Strong time‑management and prioritisation skills.
• Attention to detail and high standards for model quality.
• Curiosity, continuous learning, and mentorship of junior team members.

Benefits

Rosenxt offers flexible hybrid working, 30 days of annual leave plus public holidays, a 10 % employer pension contribution, and company‑sponsored life and private medical insurance. Additional benefits include a cycle scheme, competitive remuneration and funded career and learning development opportunities within a global, innovative group that values progress and sustainability.

• Flexible hybrid working with 2–3 days in office per week.
• 30 days annual leave plus public holidays.
• 10 % employer pension contribution with no employee contribution required.
• Company‑sponsored life insurance and private medical insurance.
• Cycle scheme and competitive remuneration package.
• Funded career development and learning opportunities.

Training + Development

Interview process

Visa Sponsorship

Security clearance