Who we are at Osmo:
Osmo is a digital olfaction company, on a mission to give computers a sense of smell to improve the health and wellbeing of human life. Why? Our sense of smell both enriches and saves lives, and has a deep and direct connection to our emotions and memory. Vision and hearing have been digitized, but not scent. It's time we solve this. We're bringing an unprecedented combination of software, data, hardware and capital to the historic challenge of giving computers a sense of smell.
We believe in the power of automation and carefully applied AI/ML to solve problems that are beyond what the unaided human mind can tackle on its own. In the first phase of our development, we are using our map of odor along with cutting-edge generative AI to create the next generation of aroma molecules (e.g., the ingredients in the fragrances we wear and the products we use). We're a hybrid company with a laboratory and center-of-mass in Cambridge, MA and New York, NY.
Osmo is looking for a Machine Learning Engineer to join our rapidly growing team. Osmo is building an operating system for smell, and the machine learning (ML) platform plays a very important part of modeling and simulating the molecular properties in the real world. We need you to join our world-class and interdisciplinary team to build our capabilities and drive cutting-edge research that can lead to a different future for humanity. You will be a member of the engineering team, reporting to the Head of Engineering.
What you will be doing:
- Improve the performance (speed/accuracy) of our ML platform that spans on a wide range of molecular chemistry problem, especially concerning olfaction.
- Stay up to date with the machine learning literature, especially for their application in molecular chemistry and olfaction, and quickly prototype ideas from the research field.
- Dive deeply into various datasets, understand their characteristic and derive meaningful train and test data for real-world machine learning models and their deployment.
- Develop innovative model architectures and creative data featurizations to take advantage of available data and unlock new ML capabilities.
- Work closely with software engineers and product managers to strengthen the operating system for scent with our ML platform.
What we need to see:
- A strong software engineer who produce high quality code and take pride in their work.
- Comfortable with linear algebra and statistics.
- Experienced in applying machine learning techniques to real-world problems with frameworks such as PyTorch or TensorFlow.
- Interested in learning about molecular chemistry and the biology of olfaction.
- Experience with Bayesian Statistics and Probabilistic Modeling
- Willingness to work in our New York City office 2-5 days a week or travel to New York ~2+ times a quarter to work with the team in person
- US work authorization
Ways to stand out from the crowd:
- Experiences in graph neural networks and their application in cheminformatics problem.
- Work or educational background in chemistry or neural olfaction.
- Familiar with cloud tooling for machine learning at scale.
Who you are:
You're Curious, Kind, Communicate Clearly, and Get Stuff Done. You have a first-class mind, and you want to stretch it. You want to work on a nearly impossible goal that serves a deep human need, drawing on a wide diversity of knowledge and skill to achieve it. Where there's a gap, we explore it from first-principles and invent pragmatic solutions. You want to work with world-class, passionate teammates on this adventure into the unknown.
If this role inspires you we'd encourage you to apply. We are committed to recruiting, developing, and retaining an incredible team optimized for a diversity of thought, background, and approaches. All employment decisions and responsibilities are determined based on current ability and your ability to grow, without regard to race, color, gender identity, sex, sexual orientation, religion, age, marital status, physical, mental, or sensory disability, or any other characteristic protected by applicable law.