Apply to the vacancy...
Unfortunately, something went wrong while opening the page. Please try again.

Loading window...

Apply to the vacancy...
Unfortunately, something went wrong while opening the page. Please try again.

Loading window...

Sign up for Jobbird
An error occurred while opening the sign-up page. Please try again.

Loading window...

Forgot my password
Unfortunately, something went wrong while opening the page. Please try again.

Loading window...

Log out
Unfortunately, something went wrong while signing out. Please try again.

Loading window...

Job application sent
Something went wrong while logging in. Please try again.
Something went wrong while signing up. Please try again.

Loading window...

logo
  • 5 km
  • 10 km
  • 30 km
  • 50 km

  • All
  • 5 km
  • 10 km
  • 30 km
  • 50 km

  • All
Filters
Filters
Location and distance
  • 5 km
  • 10 km
  • 30 km
  • 50 km

  • All
Jobs posted from
Salary from (per month)
Filters
How our sorting works

The order in which job vacancies are displayed is determined by a composite score based on the following factors:

  • Keyword Relevance: How well your search terms match the vacancy details. We prioritize matches found in the job title, followed by job requirements, location names, and educational levels. Matches within general employer information or the organization's name carry a lower weight.
  • Commercial Prioritization (Premium Jobs): Vacancies paid for by employers ('Premium' or 'Sponsored') receive a ranking boost and will appear higher in the search results.
  • Recency (Date Relevance): Newer vacancies are prioritized. The relevance score of a vacancy is reduced by half once the posting is older than 30 days.
  • Proximity (Distance Relevance): Vacancies located closer to your search location are ranked higher. For vacancies located more than 30 km from the search center, the relevance score is halved.
The final ranking is established by multiplying all these individual factors to calculate the total relevance score.

Hyper Recruitment Solutions LTD

Machine Learning Engineer

Hyper Recruitment Solutions LTD King's Cross
32 - 40 hour


Show Recently closed jobs

    Hyper Recruitment Solutions LTD

    Machine Learning Engineer

    Hyper Recruitment Solutions LTD King's Cross
    32 - 40 hour
    Status Open
    Apply now

    Apply on the employer's website


    What we ask

    Education

    No minimum education required

    What we offer

    Salary
    Hours
    32 to 40 hours per week
    Employment type
    permanent

    Job description

    ROLE OVERVIEW:

    We are currently looking for a Machine Learning Engineer to join a leading research organisation based in London. As Machine Learning Engineer, you will be responsible for advancing data-processing, model-building, and deployment capabilities for a pioneering research organisation.

    KEY DUTIES AND RESPONSIBILITIES:

    Your duties as the Machine Learning Engineer will be varied; however, the key duties and responsibilities are as follows:

    1. Develop deep-learning pipelines for nuclear magnetic resonance (NMR) data and innovative machine learning approaches to elucidate and quantify interactions between small molecules and intrinsically disordered proteins.

    2. Enhance the usability of built models by implementing automated, streamlined, and efficient software solutions in line with best practices, and build model-deployment and job-launching systems for internal and external use.

    3. Collaborate closely with other computational and NMR team members, in addition to experimental biophysicists, assisting with experimental data handling and curation, and mentoring the interdisciplinary team in machine-learning and data analysis methods.

    4. Stay current with breakthroughs in machine learning, neural networks, NMR, and computational technologies, contributing to the design and execution of cutting-edge machine learning and NMR research projects.

    ROLE REQUIREMENTS:

    To be successful in your application to this exciting role as Machine Learning Engineer, we are looking to identify the following on your profile and past history:

    1. Relevant degree in a technical field with proven experience in machine learning or model-building.

    2. Proven industry experience in applying machine learning and modelling techniques to graph-based data such as molecules and proteins, as well as time series. An ability to demonstrate innovative ways of working (for example work on disordered proteins and consideration of the next frontier in drug discovery) will be highly advantageous.

    3. A working knowledge and practical experience with Python, and extensive experience with the scientific and machine-learning stack: Numpy, Torch/Tensorflow/Jax, Scikit-learn, Polars, SQL.

    Key Words:
    Machine Learning Engineer / Data Processing / Model Building / NMR / Deep Learning / Computational Biophysics / Drug Discovery / Neural Networks / Scientific Software / Python / Nuclear Magnetic Resonance

    Hyper Recruitment Solutions Ltd (HRS) is an Equal Opportunities employer. We welcome applications from anyone who meets the role requirements. HRS exclusively supports the Life Science sectors, combining recruitment expertise with scientific knowledge to help you advance your career
    Apply now

    Apply on the employer's website

    Apply now

    Apply on the employer's website


    Vacancy actions

    Save as favorite
    Share vacancy
    Or apply later


    King's Cross England

    Jobs

    • Search for jobs
    • Jobs per location
    • Jobs per job profession
    • Jobs per employment
    • Jobs per educational attainment

    Jobbird

    • Switch to different region
    • Terms and Conditions
    © 2026 Jobbird