Optimal

Machine Learning Research Engineer at Optimal

Rotterdam · Full Time

We are a team of AI scientists and engineers from the University of Oxford, Google Deepmind and MIT. Backed by world-leading deep technology funds, including Founders Fund.

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Job Description

THE MISSION

Since the Green Revolution sixty years ago, the combination of new lab-made fertilisers and pesticides has been saving our rapidly growing population from starvation - significantly increasing the efficiency of our agricultural system at the expense of food quality. At Optimal, are are deploying large-scale AI-controlled indoor farms outside every city on earth to grow safer, healthier food - enabling a longer-living population and not just a larger one.

THE TEAM

We are a team of AI scientists and engineers from the University of Oxford, Google Deepmind, MIT and others - including a chair of ICML, a DeepMind research scientist who reduced the cooling bill of a Google data centre by 40%, and a grower who started as a vegetable picker 40 years ago and now runs one of the most advanced indoor farming operations in the world.

We are backed by world-leading deep technology VC funds, including Founders Fund, who have backed companies such as SpaceX, Palantir and Square from the very start. We are well capitalised for the future.

YOUR ROLE

Machine Learning breakthroughs follow the availability of high-quality datasets, well-defined benchmarks and innovative algorithmic approaches.

You will be designing and developing our internal Kaggle/OpenAI Gym environments and creating predictive models within them, exploiting our deep, proprietary datasets to improve upon the metrics needed to grow safer, healthier food most efficiently.

You will be working in a multidisciplinary team across machine learning, reinforcement learning and software engineering on a wide variety of important problems.

YOUR RESPONSIBILITIES

- Design and develop data pipelines and predictive models to improve the performance of our AI agents.
- Improve our simulation, training and benchmarking environments (internal Kaggle/OpenAI Gym).
- Create visualisation and monitoring tools to ensure the integrity and performance of our datasets, environments and algorithms.
- Work with our professor-level research supervisors to analyse results and iterate approaches.
- Work closely with our reinforcement learning and software engineers.
- Continually learn and self-improve, helping others to do the same. Reject the natural talent hypothesis.

YOUR SKILLS AND EXPERIENCE

- Strong foundations in probability, statistics and linear algebra.
- Strong programming skills in python and its machine learning stack: numpy, pandas, matplotlib, tensorflow, pytorch etc.
- Strong data manipulation, exploration and visualisation skills.
- Experience working with real-world datasets.
- Ability to understand cutting-edge research papers.
- Knowledge or willingness to learn techniques from reinforcement learning to complement your skills.

Extra credit
- Experience with bayesian and frequentist approaches for time series modelling: GPs, RNNs, Bayesian NNs, etc.
- Experience deploying commercial machine learning models.
- Comfortable in a distributed linux-based environment.
- Extracurricular activities: contributing to the open-source community, side projects, coding competitions, etc.

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What We're Building

Since the Green Revolution sixty years ago, the combination of new lab-made fertilisers and pesticides has been saving our rapidly growing population from starvation - significantly increasing the efficiency of agriculture at the expense of food quality. At Optimal, we are growing safer, healthier food by deploying large-scale AI-controlled indoor farms outside every city on earth - enabling a longer-living population, not just a larger one.

We are a team of AI scientists and engineers from the University of Oxford, Google DeepMind and MIT - including a chair of ICML, a DeepMind research scientist who reduced the cooling bill of a Google data centre by 40%, and a grower who started as a vegetable picker and now runs one of the most advanced indoor farming operations in the world.

We are backed by world-leading deep technology funds, including Founders Fund, who have backed companies such as SpaceX and Palantir.

We are in stealth mode. There is limited information about us online.

Other Jobs at Optimal

Optimal Team

David Hunter
Founder/CEO Optimal Labs [Applied Reinforcement Learning]. Deep Reinforcement Learning research, University of Oxford. Algorithmic trading, Deutsche Bank.
João Abrantes
CTO @Optimal. Machine Learning and Robotics research at @EPFL .

Optimal Investors

Nathan Benaich
Investing in intelligent systems.
Edward Grefenstette
Staff Research Scientist at DeepMind. Former Research Fellow at Oxford. DPhil CS Oxford. Works on the intersection of logic, language, and machine learning.