Machine Learning Scientist I/II, Multi-Modal Scientific Reasonings in Cambridge

Machine Learning Scientist I/II, Multi-Modal Scientific Reasonings in Cambridge

Cambridge Full-Time 60000 - 80000 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Lead research on multi-modal reasoning systems using vision-language models for scientific data.
  • Company: Join Lila Sciences, a pioneer in advancing scientific superintelligence.
  • Benefits: Competitive salary, equity options, flexible time off, and comprehensive health benefits.
  • Other info: Collaborative environment with opportunities for growth and innovation.
  • Why this job: Make a real impact in science with cutting-edge machine learning technologies.
  • Qualifications: Advanced degree in relevant fields or equivalent experience in multi-modal ML.

The predicted salary is between 60000 - 80000 £ per year.

Your Impact at LILA

We’re hiring a Machine Learning Scientist to advance multi‑modal reasoning with vision‑language models (VLMs) on real‑world scientific data including, but not limited to: figures and plots, microscopy data from diverse sources. You’ll design and build state‑of‑the‑art methods to advance the state of Scientific Superintelligence.

What You’ll Be Building

  • Lead research on multi‑modal reasoning systems that interpret scientific data (images, plots, text, etc) using state‑of‑the‑art and custom VLMs.
  • Design training, adaptation and test‑time methods and strategies (e.g., instruction tuning, supervised learning, RLHF, RAG) for scientific understanding tasks.
  • Build datasets and benchmarks from real scientific artifacts (e.g., microscopy, spectra, protocols) to understand model performance.
  • Develop perception modules (e.g, OCR, table/structure recognition, plot parsing) for multi‑modal data modalities.
  • Collaborate with domain scientists and engineers to scale research into production ready systems for scientific superintelligence.

What You’ll Need to Succeed

  • Advanced degree in a relevant field (CS/AI, Applied Math/Stats, EE) or a physical‑sciences discipline (Materials, Chemistry, Physics) with strong ML focus; or equivalent research/industry experience.
  • Track record in multi‑modal ML or VLMs demonstrated via shipped systems, publications, or open‑source.
  • Understanding of scientific QA/benchmarks and custom evaluation design.
  • Experience with multi‑modal fine‑tuning, document parsing & understanding, dataset curation and benchmarking.
  • Strong engineering skills centered on modern machine learning frameworks (e.g., PyTorch, Huggingface).
  • Clear communication and collaboration in cross‑functional settings.

Bonus Points For

  • Experience with scientific data modalities in real‑world laboratories such as microscopy images.
  • Publications in top ML/CV/NLP venues or tangible impact in applied industrial research.
  • Contributions to open‑source multi‑modal tooling, evaluation suites, or datasets.

Compensation

We offer competitive base compensation with bonus potential and generous early‑stage equity. Your final offer will reflect your background, expertise, and expected impact.

U.S. Benefits

Full‑time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer‑paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.

International Benefits

Full‑time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.

Expected Base Salary Range: $176,000 — $304,000 USD

We’re All In

Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

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Contact Details:

Lilasciences Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Machine Learning Scientist I/II, Multi-Modal Scientific Reasonings in Cambridge

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We think you need these skills to ace Machine Learning Scientist I/II, Multi-Modal Scientific Reasonings in Cambridge

Multi-Modal Reasoning
Vision-Language Models (VLMs)
Scientific Data Interpretation
Training Methodologies (e.g., Instruction Tuning, Supervised Learning, RLHF, RAG)
Dataset Building and Benchmarking
Perception Modules Development (e.g., OCR, Table/Structure Recognition, Plot Parsing)
Machine Learning Frameworks (e.g., PyTorch, Huggingface)

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Lilasciences. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Lilasciences

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