Machine Learning Engineer

About Tenyks

Tenyks is a University of Cambridge spin-out inventing the way humanity interacts with AI to protect and delight. To protect the world from the misuse of AI, but also to ensure that AI is developed with passion, excitement, and joy!

We are building an MLOps monitoring and validation platform that helps AI developers working with computer vision data to build more reliable software faster. Specifically, our platform helps ML developers understand what's wrong with their software and fix it. Imagine all the tools you use to develop software that need to be reimagined and created for the AI world.

At Tenyks we set our goals ridiculously high and stick together to go further than anything previously imaginable. We start small, work hard, and deliver fast, embracing the inevitable obstacles with open hearts because challenges fuel our burning desire for learning. Tenyksians make no distinction between work and play. We simply pursue our vision of excellence, leaving others to decide whether we are working or playing.

We are a remote-first team, consisting of 3 PhDs and 1 MPhil in Explainable AI that has now raised substantial seed funding from leading UK, EU, and BG investors.

The Position

As an ML Engineer, you will wear multiple hats across our ML pipeline, including: solution architecting of AI/ML based solutions, CI/CD practices, DevOps, MLOps principles, data pipelines and data cleansing. The role will revolve around developing & productionising ML prototypes developed at Tenyks, and integrating them into the Tenyks product.

This will involve working directly with the product manager, software engineers, and ML Research Engineers in order to understand why a given feature is required and how best to implement & integrate it into the Tenyks Product.

We are a small but dedicated team and expect everyone to be self-driven, comfortable working in our dynamic and fast-paced environment, and embrace the challenges we face.

Requirements

• 4+ years of relevant working experience in developing production-grade ML systems, with a Bachelor’s / Master’s Degree in Computer Science or related fields (e.g., Physics, Mathematics, Engineering)
• Proficiency with Python and basic machine learning libraries (scikit-learn, numpy, scipy, pandas, etc)
• Proficiency with at least 1 deep learning framework (Tensorflow, Keras, PyTorch, etc)
• Experience in operationalization of ML, such as using open source frameworks (e.g., MLflow, Seldon.io), or managed services / cloud provider offerings (e.g. AWS Sagemaker, Google AI Platform, Azure Machine Learning, Databricks, DataRobot, …), or specific on-prem solutions (e.g., Kubeflow)
• Experience in building RESTful APIs on top of Python-based servers (e.g. Flask, Tornado), and running these over scalable Databases (e.g. Mongo, SQL, Postgres)
• Experience with core DevOps principles, such as CI/CD, Testing (e.g. unit, integration, regression), Containerisation, & Security
• Familiarity with Linux and bash commands
• Passion for learning and applying new research.
• Excellent communication, relationship skills, and a great teammate
• Experience working as part of an agile product development team
• Preferably based in UK or Europe

Our Hiring Process

1. Screen call (15 min)
2. Take-home challenge
3. Technical discussion (1.5h)
4. Chat with the Founders (1.5h)
5. Meet the team (1h)
6. Offer & References 🎉

Benefits

£70K - £85K GBP / 0.30% - 0.68%