MTS, Machine Learning

Inductive Bio

$120K — $150K *
Pharmaceuticals & Biotech
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 4+ years in machine learning, data science, or related fields
  • Strong foundation in chemistry, biology, physics, or similar discipline, ideally a PhD
  • Expertise in machine learning fundamentals and deep learning architectures
  • Proficient in Python-based ML frameworks like PyTorch, TensorFlow, scikit-learn
  • Experienced in writing reusable code and deploying models in the cloud
  • Strong communication skills, both written and oral
  • Preferred: Graduate-level knowledge in cell/molecular biology or biochemistry

Responsibilities

  • Develop machine learning models to predict molecular properties
  • Create novel algorithms for new molecule generation
  • Build agents to synthesize complex information for optimization
  • Perform deep analysis on proprietary datasets to improve models
  • Collaborate with chemists and engineers to integrate models into software
  • Optimize infrastructure for model training and deployment
  • Gather user feedback to inform product enhancements

Benefits

  • Competitive salary and equity-based compensation
  • Comprehensive healthcare benefits including dental and vision
  • Opportunities for career growth in a scaling company
  • Supportive, kind, and mature team environment
  • Work-life balance for a fulfilling life beyond work
Full Job Description
We are seeking a Member of Technical Staff, Machine Learning to join our talented, ambitious, and kind team. You'll innovate on ML methods, work closely with leading drug discovery scientists, and see your work applied directly to real drug programs. You'll have significant ownership, impact, and opportunity to grow with the company.

What you'll do:
  • Develop machine learning models to predict molecular properties from chemical structures
  • Develop novel algorithms for generating ideas for new molecules
  • Build agents that can synthesize complex information from drug programs and apply that information strategically toward molecular optimization
  • Get your hands dirty by diving deep into our unique, proprietary dataset to iterate on modeling ideas and improve model performance
  • Collaborate closely with chemists and software engineers to integrate models into our software platform, which is used by drug discovery scientists across the industry
  • Build and optimize scalable infrastructure for model training, deployment, and monitoring
  • Engage directly with our scientific users, incorporating their feedback into the product
  • Contribute meaningfully to product strategy and company direction

Who you are:
  • You have 4+ years of experience as a Machine Learning Scientist, Machine Learning Engineer, Data Scientist, or similar role
  • You have a strong scientific background, ideally with a PhD in chemistry, biology, physics, or a related field
  • You have expertise in machine learning fundamentals, deep learning architectures, and evaluation approaches
  • You are proficient in standard Python-based ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn)
  • You are comfortable writing high-quality, reusable code and productionizing models for serving in the cloud
  • You are excited to dive deep into the science and practice of drug discovery
  • You have exceptional written and oral communication skills
  • Preferred experience:
    • You have graduate-level knowledge of cell / molecular biology or biochemistry, and experience collaborating with wet lab scientists
    • Experience with omics modeling (transcriptomics, proteomics, metabolomics, etc)
    • Experience with high-content screening and signal processing from microscopy data

Working at Inductive

At Inductive Bio, we know that the people on the team are what make us great. We offer competitive salary and equity-based compensation; comprehensive healthcare benefits (including dental and vision); and the opportunity to grow along with a rapidly scaling company. We are a passionate, kind, and mature team. Working at a fast growing startup is not always a 9-5 job, but we believe that our employees should have full lives beyond their career.

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