Lead Machine Learning Engineer

Required

• You have experience with distributed systems and scalable architectures to handle large-scale ML applications.
• You have experience with building, deploying and maintaining ML systems using relevant ML techniques and platforms, i.e.: Scikit-learn, Tensorflow, MLFlow, Kubeflow, Pytorch.
• You have experience with building, deploying and maintaining ML systems and experience with application of MLOps principles and CI/CD to ML.
• You have experience in machine learning engineering and data science, are familiar with key ML concepts, algorithms and frameworks, and understand ML model lifecycles.
• You have experience with designing and operating the infrastructure required to run different types of ML training and serving workloads, i.e.: on-premise vs. cloud infrastructure, infrastructure as code, monitoring, etc.
• You have hands-on experience with on-premise and cloud services for building and deploying ML pipelines, i.e.: Azure, AWS, GCP and/or Databricks and associated ML managed services.
• You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way.
• You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives.
• You don’t shy away from risks or conflicts, instead you take them on and skillfully manage them.
• You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work.
• You enjoy influencing others and always advocate for technical excellence while being open to change when needed.
• You are a proven leader with a track record of encouraging teammates in their professional development and relationships.