Machine Learning Scientist - Automated Image Analysis

🚀 About Lila

Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science.  We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method.  We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at  www.lila.ai

If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, we encourage you to apply.

🌟 Your Impact at Lila

As a Machine Learning Scientist focused on Automated Image Analysis, you will design and deploy cutting-edge computer vision models to unlock insights from diverse image types related to complex chemistry and materials science phenomena. Your work will accelerate discovery by understanding structure, morphology, and property information from experimental data at scale, enabling Lila’s scientific superintelligence to learn faster and more deeply from the physical world.

🛠️ What You'll Be Building

• Develop and optimize ML models for analyzing microscopy and spectroscopy image data (e.g., SEM, TEM, AFM, optical imaging).
• Automate feature extraction to quantify morphology, structure, defects, and diverse material properties.
• Collaborate with chemists, physicists, and software engineers to integrate imaging pipelines into Lila’s platforms.
• Build scalable data preprocessing, augmentation, and labeling workflows for diverse scientific image datasets.
• Validate model performance against experimental benchmarks and continuously improve interpretability.

🧰 What You’ll Need to Succeed

• Advanced degree (PhD or MS) in Computer Science, Physics, Materials Science, Chemistry, or related field.
• Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, or JAX).
• Hands-on experience with state-of-the-art computer vision techniques spanning diverse tasks (classification, object detection, segmentation) and architectures (CNNs, transformers, diffusion models).
• Familiarity with scientific imaging data (microscopy, spectroscopy, or similar).
• Strong track record of deploying ML models for real-world image analysis tasks.

✨ Bonus Points For

• Experience with multimodal ML (combining imaging with spectroscopy or tabular data).
• Familiarity with self-supervised or foundation models for vision tasks.
• Knowledge of scientific data formats (HDF5, NetCDF, TIFF stacks) and scalable pipeline development.
• Contributions to open-source ML or scientific imaging projects.

🌈 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.

🤝 A Note to Agencies

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.