Your mission

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.

What you need to succeed

• 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

Hiring Process

• Screen call (15 min)
• Take-home challenge
• Technical discussion (1.5h)
• Chat with the Founders (1.5h)
• Meet the team (1h)
• Offer & References 🎉