Data Scientist/Machine Learning Engineer- Bioliberty Edinburgh•Hybrid remote £40,000 – £50,000 a year – Full-time

Full time @Data Science Career in Data Science , in Data Scientist , in Machine Learning
  • Apply Before : March 8, 2024
  • Salary: £40.00 - £50.00 / Annual
  • 3 Application(s)
  • View(s) 46
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Job Detail

  • Job ID 21643
  • Sector Data Science

Job Description


Pulled from the full job description
  • Casual dress
  • Company events
  • Company pension
  • Cycle to work scheme
  • Flexitime
  • Free parking
  • On-site parking

Bioliberty is a multi-award winning technology start up, developing rehabilitative robotic solutions, for those with stroke, hand trauma and degenerative diseases. We are developing our first product, Lifeglov, which is a soft robotic glove to assess hand mobility and perform resistance training for rehabilitation.

Bioliberty have successfully secured public and private investment from some of the UK’s most reputable angel investment groups, family offices and public bodies such as Innovate UK and Scottish Enterprise. We are working with some of the top rehabilitation clinics in the UK and US to drive forward our technology adoption and deliver unparalleled patient outcomes from hospital to home. By joining Bioliberty you will have the opportunity to be part of a high growth start up, working on cutting edge technology, with high impact to humans and society. This role will be based in the National Robotarium, Edinburgh – a world leading centre for robotics and home of global leaders in artificial intelligence and autonomous systems.

Bioliberty is an equal opportunity employer who welcomes applications from all backgrounds. Diversity and inclusion is important to us, as we want to build a workforce that represents all walks of life.

The Role:

As a data scientist/machine learning engineer at Bioliberty, you will play a crucial role in developing and implementing cutting-edge machine learning algorithms for diverse rehabilitation applications. Your focus will encompass classification, regression models, and advanced signal processing. This role necessitates seamless collaboration with firmware, robotics, and software engineers to create cohesive and innovative solutions that positively impact the field of rehabilitation. You will be required to responsibly handle sensitive data, adhering to strict data privacy and security protocols to ensure compliance with relevant regulations.


  • Qualifications: bachelor’s or master’s degree in computer science, data science, artificial intelligence, mathematics, physics software engineering or other related discipline (with a focus on software).
  • Industry Experience: A minimum of 2 years industry experience post university.
  • Programming Skills: Proficiency in programming languages commonly used in machine learning, such as Python, R or C/C++, and with ML libraries such as TensorFlow, PyTorch, or sci-kit- learn.
  • Machine Learning Expertise: Proven experience in developing and implementing classification and regression models, computer vision algorithms, and other machine learning techniques such as Gaussian processes, probabilistic/statistical models, neural networks, Bayesian inference, random forests, or clustering.
  • Hardware Deployment: Demonstrated experience in deploying machine learning algorithms on hardware platforms, such as GPUs, FPGAs, or ASICs.
  • Digital Signal Processing: Familiarity with digital signal processing concepts and techniques for feature extraction and data preprocessing.
  • Embedded Systems: Knowledge of embedded systems and the ability to integrate machine learning models into resource-constrained devices.
  • Data Revision Control: Proficiency in using data revision control systems (e.g., Git) to manage and version datasets, model configurations, and code changes.
  • Collaboration: Demonstrated ability to work collaboratively with firmware engineers, robotics engineers, and software engineers to create cohesive solutions.
  • Communication: Excellent communication skills, both verbal and written, to articulate complex technical concepts to non-technical stakeholders.

Nice to have:

  • Relevant Experience in robotics, data fusion, tracking/estimation, pattern discovery & recognition, statistical inference, optimisation and machine/deep learning algorithms along with real-time implementation, and/or validation & verification is a strong advantage.
  • Experience Handling Sensitive Medical Data: Prior experience working with sensitive medical data and a strong understanding of data privacy and security protocols, such as HIPAA.
  • Computer Vision Experience: experience working with computer vision algorithms e.g. structure from motion, image based navigation, SLAM, pose estimation/recovery.
  • ML Ops: strong understanding of software development lifecycles and engineering practices (Data pipelines, API workflows, CI/CD, containerisation) specifically ML Ops principles, techniques and tooling. Hands-on experience in implementing, deploying and maintaining machine learning models at scale in Python or similar languages.
  • Industry-Specific Experience: Experience in the medical or healthcare industry, robotics, or related fields, enhancing your understanding of domain-specific challenges and opportunities.
  • Cloud Computing: Familiarity with cloud computing platforms and services, allowing the deployment of machine learning models at scale.

What we offer

  • A competitive salary and benefits package (depending on experience).
  • A passionate and highly skilled team, always ready to help you grow your skills.
  • Part of a team working on an innovative R&D project collaborating with world-leading specialists from University of Edinburgh, Heriot Watt University, Bioliberty and our wider KOL network.
  • Flexible vacation and working hours and the flexibility to work from home.
  • State of the art office located in the National Robotarium, Edinburgh.
  • Company laptop.


  • Salary: competitive depending on experience.
  • Private health insurance.
  • Cycle to work scheme.
  • Flexible working environment and hours: hybrid working and flexi schedule.
  • Holidays: 32 days paid leave including public holidays.
  • Pension contribution: 3% employer, 5% employee.
  • Company events.
  • Opportunities to travel for work to conferences, suppliers, customers, events as required.

Join our team and be part of an exciting journey to revolutionize the world with cutting-edge machine learning solutions while collaborating with experts from different engineering disciplines and making a significant impact in the medical and robotics domains.

To apply for this position please respond to this listing with your CV and a short cover letter to Ross O’Hanlon, Founder and CTO, including any links to previous work or portfolio projects.

Job Type: Full-time

Salary: £40,000.00-£50,000.00 per year


  • Casual dress
  • Company events
  • Company pension
  • Cycle to work scheme
  • Flexitime
  • Free parking
  • On-site parking
  • Private medical insurance
  • Work from home


  • Monday to Friday

Application question(s):

  • Do you have the legal right to work within the UK?

Ability to Relocate:

  • Edinburgh: Relocate before starting work (preferred)

Work Location: In person

Application deadline: 22/01/2024
Expected start date: 19/02/2024

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