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DevOps Engineer

Jua

Jua

Software Engineering
Zürich, Switzerland
Posted on Friday, June 28, 2024

Overview

Jua is on a mission to achieve artificial general intelligence (AGI) by delving deeply into physics, the universe, and their relationship with human civilization. We are operating a foundational earth systems model. Our first model is capable of predicting atmospheric physics globally, with state-of-the-art performance in comparison to existing weather models.

As we scale the model, more applications like wildfire, flood or vegetation prediction become possible. Our flagship product is an API designed for weather-dependent power and energy traders, offering superior accuracy, lower latency, and a higher refresh rate, especially during critical events like hurricanes and cyclones.

With substantial venture capital backing at a sensible valuation, our first objective will be to provide businesses and countries with several orders of magnitude better and faster weather forecasts. Our multidisciplinary team combines expertise in machine learning, physics, aerospace, data processing, and UX design to create a crucial component for a sustainable world amidst changing climate patterns and increasing extreme weather events.

Joining our team means collaborating with individuals who have built successful companies and worked on technologies used by millions. You'll contribute to our culture of ambition, transparent communication, rapid iteration, and humility. We offer exciting challenges, creative freedom, a talented and enthusiastic team, fair compensation, and generous shares in the company.

What we are looking for

At Jua, our mission is to create the world’s most accurate foundational physics model for the Earth. We see this as an important step on the journey towards AGI. Critical to the success of this mission is the ability to run model training, evaluation and inference at a massive scale. The greater the scale we operate at, the better our model becomes. We are looking for a motivated distributed systems engineer who can tackle these problems we encounter as we scale.

Jua is a research-led company with a focus on solving hard engineering problems as well as product excellence. The ideal candidate will be motivated by the prospect of working for an early-stage startup and excited to have the opportunity to play a leading role in the journey of scaling our infrastructure from hundreds of nodes to multiple orders of magnitudes. Machine learning is a core competency of Jua, however, we also know that many of our challenges are engineering-focused. With this in mind, we aren’t necessarily looking for candidates with previous ML experience. Still, we are looking for candidates who are excited about the prospect of upskilling in the area.

Responsibilities and tasks

  • Foster a culture of distributed systems excellence across the organisation
  • Be a hands-on contributor to the code base, both writing code as an individual contributor as well as coaching and mentoring the team on distributed systems best practices
  • Profiling and monitoring the performance of our systems. Optimising from the highest level, such as holistic systems architecture, down to the lowest level, such as CUDA operators optimisation
  • Participate in system design across engineering

Need-to-have

  • Strong background in Software Engineering, able to code in one or more languages, such as Python, Java, C/C++, and Golang, proven track record with developing for production
  • Experience in distributed application development, including experience with distributed storage technologies such as blob storage, NoSQL/NewSQL databases, distributed file systems
  • A proactive approach to identifying problems, performance bottlenecks, and areas for improvement
  • Experience working in multidisciplinary teams
  • Experience working on production systems that meet one or more of the following characteristics
    • Low latency (such as sub 10ms)
    • High throughput (> GB/s)
    • Large datasets (e.g. petabyte scale)
  • Appreciation of the tradeoffs typically encountered when working in distributed environments such as consistency vs availability and throughput vs latency
  • 8+ years working in an Engineering role

Nice-to-have

  • Experience working with geospatial datasets
  • ML experience
    • Running large-scale distributed ML training
    • Working with ML communication protocols such as NCCL or MPI
    • Working with ML frameworks such as PyTorch, Tensorflow or JAX
  • Experience leading/managing projects

At Jua, we foster a performance culture and value people who embody our beliefs of service and adventure. We prioritize agility, operating at the highest clock speed to adapt quickly to change. We innovate on behalf of our users and leverage data supremacy to maintain our competitive edge. Through clear communication and fact-based decision-making, we ensure alignment in our pursuit of excellence. With these principles, we aim to create a customer-focused, value-centric organization that sets new standards in the industry. We value the unique perspectives that each individual brings to the table and believe that embracing diverse backgrounds and experiences enriches our collective journey towards growth and success.