Who we are:
Our name is inspired by Theodore Roosevelt’s ‘Citizenship in a Republic’ speech, which pays homage to the ‘(hu)man in the Arena’. To us, entering the Arena means committing oneself fully and accepting the risk of failure in the pursuit of an audacious, worthy cause.
We’re a close-knit tribe of scientists and builders exploring the boundaries of how artificial intelligence can benefit humanity. If you share our passion for delving deep into real-world problems and solving them with fully autonomous AI, join us in the Arena.
What we do:
Our collective future is being built in the physical world, but the builders of tomorrow’s technology can no longer rely on yesterday’s tools. At Arena, we’re building the world’s first AI industrial engineer designed to solve the most complex hardware and manufacturing challenges. Our product, Atlas, is built with an understanding of the behavior of physical systems, powered by a superior knowledge of core domains of physics. Paired with its ability to reason about multimodal industrial data, Atlas can test, debug, optimize, and repair physical systems and products in the real world. Arena is already trusted by some of the most advanced industrial companies in the world (AMD, Bausch & Lomb), and we're rapidly already scaling into the defense, automotive, and pharmaceuticals industries, and we’re just getting started.
How you will contribute:
As a Machine Learning Scientist at Arena, your responsibilities will include developing ML systems that power closed loop automated decision making for large enterprises. Our technology encompasses large transformer based models that feed multi-modal data in addition to Reinforcement learning based smart exploration/exploitation systems. 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 our office in NYC
- Model training, deployment and maintenance experience in a production environment
- Strong skills in deep learning and related frameworks (ie. Pytorch, Tensorflow, DeepSpeed, Ray, Pytorch Lightning)
- Experience in dealing with high performance, large scale ML systems
- Strong high-level programming skills and passionate about good engineering, clean code, scalability
- Deep passion for AI and building machine learning systems
- Interested in the full ML stack from initial R&D through deploying models into production
- Strong written and verbal communication skills to operate in a cross functional team environment
It would be great if you have:
- Experience with active learning, reinforcement learning, causal inference and/or online learning approaches
- Expertise in experimental design and Bayesian uncertainty estimation
Benefits:
- 99% of the monthly premium for Aetna medical insurance, plus vision and dental coverage
- 401(k) Retirement Plan
- Unlimited PTO
- Lunch every day from local restaurants via Sharebite
- Laptop and monitor provided
The base salary range for this position is $135,000 - $200,000 yr. However, base pay offered may vary depending on job-related knowledge, skills, and experience. In addition to base salary, we also offer competitive equity and benefits packages.
Top Skills
What We Do
We're building domain specific multimodal foundation models for of the largest scale enterprise problems in the world, starting with consumer goods and advanced manufacturing. We combine an on-the-ground approach working directly with our customers to deploy AI that makes an immediate impact. For consumer goods enterprises (like ABInbev) we automate components of their sales operations to make incredibly complex autonomous and intelligent. For advanced manufacturing customers (like AMD) we automate components of performance testing, optimization, and tuning for their GPUs.
Why Work With Us
Arena builds technology that hasn't been built yet - multi-modal transformers that perform at enterprise scale, for domain specific use cases. We're taking a new approach to multi-modality, building new types of data sets (e.g. thermal profiles and power curves for GPUS). We're scientists and engineers that want to build a generational AI company.
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