Senior Machine Learning Engineer - Team Lead

Key Skills

Azure, Clustering, Continuous Integration & Continuous Delivery - CI/CD, Databricks, DevOps, Effective communication skills, Kubeflow, Machine learning techniques, MLflow, PySpark, REST API, Scala Programming, SPARK Programming, SQL, Teamwork

Job Description

At Kaizen, our aim is to make data driven decisions in order to automate our services while also focusing on offering tailored customer experiences to our customers. Our machine learning team is dedicated towards this mission by building a variety of models, from binary classification tasks up to recommendation systems. We focus on transforming business needs into production applications, and we cover a wide range of business sectors utilizing different data types and handling a broad project diversity. 

Our teams comprise of three different roles, data scientists, machine learning engineers and data engineers so that they include the full skillset to deliver projects to production.

The Role

We are looking for an experienced machine learning engineer to lead our platform team. The team is responsible for the feature store, a central application that computes hundreds of features on a 24 hour basis in real time. It is used to support all ML applications which run predictions on the aforementioned features. The role should combine software engineering skills with strong knowledge of MLOps and machine learning algorithmic understanding.

Responsibilities:

• Develop production ready pipelines;
• Implement model diagnostics such as evaluation, monitoring flows etc.;
• Automate model deployment, enable REST API model endpoints;
• Develop scalable model serving flows;
• Work on cluster optimisation and scalability;
• Develop and maintain internal tools and libraries;
• Lead the technical decisions and mentor the rest of the team;
• Architecture scalable solutions in a distributed environment;
• Previous experience in managing a team;
• Write CI/CD pipelines.

Requirements

Must have:

• A background in Computer Science, Statistics, Math or related field;
• Deep understanding of the ML project lifecycle;
• Hands-on experience with MLOps;
• 5+ years of hands-on experience in Python;
• Solid software background in OOP;
• Knowledge of version control tools and application development processes;
• Understanding of machine learning algorithms; 
• Experience with Spark (PySpark or scala);
• Strong skills in teamwork, communication and analytical thinking;
• Fluency in English, both oral and written.

Nice to have:

• Understanding of Structured Streaming;
• Experience with Azure / Databricks, Azure DevOps;
• Knowledge of SQL;
• Knowledge of MLflow and/or Kuberflow.