Machine Learning Engineer (NYC)

Output Biosciences • New York, NY

5d

About The Position

Join our team and help build the world's first biological reasoning model. Work with us to build generative foundational models that decode biological systems across scales - from molecules to organisms - enabling us to predict, understand, and program living systems in ways never before possible.
Output is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI x Bio, and backed by top-tier VCs including Y Combinator.

As a Machine Learning Engineer, you'll work alongside our founders and team members to develop and implement cutting-edge AI systems capable of complex biological reasoning across multiple scales.

Requirements

• You have a Bachelor's in Computer Science, Machine Learning, or a related technical field
• You have 3+ years of experience in developing and implementing deep generative learning models
• You have experience pre-training models and are proficient in distributed computing environments
• You are proficient in Python and have expertise in at least one major deep learning framework (PyTorch, TensorFlow, or JAX)
• You have experience with deep learning and generative architectures such as transformers, diffusion models and autoencoders
• You are skilled in working with terra-scale datasets and scaling models to billions of parameters
• You have a strong understanding of machine learning fundamentals, including various model architectures, optimization techniques, and evaluation metrics
• You have experience in designing and implementing efficient data pipelines for processing and managing large datasets
• You are experienced in developing robust evaluation frameworks and ensuring data integrity in machine learning projects
• You are experienced in code organization, version control, and collaborative software development practices.

Nice To Haves

• You have experience applying machine learning to biology or chemistry
• You have contributed to open-source machine learning projects or published research papers in the field of AI/ML
• You have experience optimizing machine learning models for high-performance computing environments
• You are familiar with ML-Ops practices and tools for managing ML experiments and deployments

Responsibilities

• You will build foundational models for biology capable of reading and writing biology at scale
• You will develop deep generative models for biological applications, exploring innovative architectures to capture the complexities of multi-scale biological systems
• You will work on distributed training systems to scale our models to billions of parameters, optimizing for performance and efficiency across multi-GPU and multi-node setups while handling large-scale biological datasets
• You will engineer efficient data pipelines to manage and process massive biological datasets, addressing challenges in data loading, splitting, and memory optimization
• You will develop and implement robust evaluation frameworks for complex biological models, ensuring data integrity and preventing leakage across dataset splits

Benefits

• We encourage new and different ideas, creativity and contrarian thinking
• Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you
• You own your day-to-day management. What we care about is that we all hit our milestones
• Competitive salary and equity in a growing, well-funded startup
• Excellent medical, dental, and vision coverage

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level