NYC- full onsite (5 days/week office)

Who They Are:

They are a close-knit tribe of scientists and builders exploring the boundaries of how artificial intelligence can benefit humanity. If you share their passion for delving deep into real-world problems and solving them with fully autonomous AI, join them

What they do:

• They empowers businesses across industries to make high frequency, critical path decisions fully autonomous. Their products have helped some of the worlds largest CPG companies transform their sales and supply chains into increasingly autonomous, self-learning systems unlocking efficiencies and resulting in better, more affordable consumer experiences.

• But autonomous selling is just the beginning. They knows that Autonomy can help organisationstackle much more, from delivering critical goods and services more affordably, sustainably, and equitably to the world, to reducing green premiums on renewable energy to compete more effectively with fossil fuels.

How you will contribute:

As a Machine Learning Scientist, your responsibilities will include developing machine learning systems that leverage uncertainty estimation and active learning approaches like Reinforcement Learning to solve real-world problems faced by their customers. Your work will span the spectrum from quick exploratory/experimental models to scaled, production processes.

Your work may start from simple models, but the ultimate goal is to push the boundaries of what is scientifically and technically possible, and share those advances with the greater scientific community via publication and/or open source.

Required qualifications:

• Working full time in the office in NYC

• Deep passion for AI and building machine learning systems

• Interested in the full ML stack from initial R&D through deploying models into production

• Comfortable working with data in Python and SQL

• Passionate about good engineering, clean code, and scalability

• Able to communicate technical concepts clearly at all levels, whether that be engaging deeply on a topic with other Machine Learning Scientists or sharing key insights with business stakeholders

It would be great if you have:

• Experience with active learning, reinforcement learning, causal inference and/or online learning approaches

• Experience with serverless or highly distributed Machine Learning model training on massive datasets

• Expertise in experimental design and Bayesian uncertainty estimation

• Familiarity in deep learning frameworks (e.g. PyTorch/TensorFlow)

Benefits:

• 99% of the monthly premium for Aetna medical insurance, plus vision and dental coverage

• 401(k) Retirement Plan

• Unlimited PTO

• Laptop and monitor of your choice

• Office supplies stipend

• Ramp Company Card

• Continued education allowance (books, e-courses)

• Attendances to top conferences in their fields

• Lunches at company wide meetings (several times a week)

• Snack and self-serve lunch options

• Global WeWork membership