Senior Machine Learning Engineer

About Mindvalley

Mindvalley is the leading and most promising ed-tech company to date. We dominate the US market for Personal Growth Education. We are empowering athletes within every major US sports team and promoting successful learning strategies in major companies.

We're currently building the most advanced learning system - a version inspired by Ironman's “J.A.R.V.I.S.” which utilizes AI and augmented reality to provide customized learning. Turning anyone into a superhero.

We innovate tools that induce enlightenment within every aspect of human life. We are seeking the best engineers to build the best and most advanced education platform our species has seen. The goal to mark our success is: powering up to 100 countries, powering every Fortune 500 company, and progressing humanity towards a better future.

About The Role

As a Senior Machine Learning Engineer (MLOps), you will play an active part in bringing Mindvalley to the next level, understanding the educational experience through data, and ensuring a personalized learning experience for our customers/students.

In this role, you will be responsible for preparing data for ML models at scale, building appropriate inference interfaces for ML model consumption, enabling ML Ops for continuous delivery and automation of ML pipelines, and/or building and sustaining AI production platforms.

This job is for you if you are a Machine Learning with at least 5 -10 years of experience, you are a natural team player, leader, a thinker, and have an open mind for constructive but supportive feedback.

Responsibilities

• Assisting data scientists in deploying the ML models into the production environment.
• Developing highly scalable machine learning models, operationalised the ML models
• Oversee machine learning operations, model deployment, model performance tracking and implement optimized machine learning solutions to real-world, large-scale problems that have a direct impact on the business.
• Handle machine learning operations and collaboration with data engineers, DevOps engineers, product managers, and technical partner teams
• Builds trust through automated processes, testing, and validation that creates a repeatable process for managing machine learning in dynamic environments
• Optimization of machine learning products with professional software engineering skills

Requirements

• Experience with RDBMS, SQL and noSQL databases
• Experience with cloud platforms (GCP), Docker and Kubernetes
• Experience in development and implementation of ready-to-use CI/CD pipelines
• Experience building and maintaining data pipelines using Google GCP services
• Experience with monitoring and orchestration of data pipelines using Apache Airflow and GCP Composer
• Experience with data cleaning and transformation using Pandas, Apache Beam and Google GCP DataFlow in Python
• Experience with Data Warehousing solutions preferably Google BigQuery
• Experience with message buses or real-time event processing platforms like Google Pub/Sub
• Proficiency in using query languages such as SQL 
• Solid Experience with Python
• Familiar with Data Science library, such as sklearn, XGBoost and Tensorflow.
• Understand what is MLOps, familiar with MLOps tools such as Kubeflow and feature store.
• Deep skills in machine learning/data science, experience with deep learning
• Good to have knowledge in Recommendation Engine and Natural Language Processing
• You are excellent in communication, teamwork and also independent contributions
• You have a strong attention to detail and flexibility of adapting to fast changes
• You work well under pressure developing key features for high volume business critical systems
• Experience with machine learning is a plus