DevOps Team Lead

Key Skills

Unix Operating system, Teamwork, Leadership, Python Programming, DevOps, Git, Azure, AWS, Machine learning techniques, Data science techniques, Keras software library, PyTorch, TensorFlow, Docker, Kubernetes-K8s, Continuous Integration & Continuous Delivery - CI/CD, Google Cloud Platform (GCP), Linux Operating system, MLOps tools, Effective communication skills

Job Description

As ML Ops Engineer - Team Lead you will be working at the intersection of machine learning and engineering (i.e., ML Ops), leading teams to deliver innovative and high-quality services. You will be a strong advocate for both engineering standard methodologies (e.g. code reviews, unit testing) and also the adoption of new technologies.

Responsibilities

• Work end-to-end on the ML lifecycle, from data exploration to model operationalization, and Partner with different teams and domains on crafting, explaining, and implementing ML models.
• Collaborate with data engineers, data scientists, product, etc in a multi-functional team for the delivery and maintenance of these solutions and business integration
• Working closely with the other department to understand their needs and recommend appropriate solutions, and support the customer on an on-going basis.
• Led sprint planning sessions, retrospectives, and code reviews
• Staying up-to-date with a fast-moving industry, embracing new tools and frameworks
• Working as part of the team, sharing and reviewing ideas, mentoring and guiding team members through technology architecture and implementation details.
• Leading by example: demonstrating what good looks like through doing
• Helping to grow the team by taking part in hiring and interviewing.

Requirements

• Bachelor’s Degree in a Science or Engineering related discipline.
• A passion for coding, data science, and open-source technologies.
• 4+ years of experience in a senior engineering role.
• Ability to lead and mentor a small team of developers.
• Excellent communication skills; both in customer-facing and internal team communication.
• Experience in team management Experience delivering software using an agile development methodology.
• Fluency in Python programming and willingness to learn new languages and technologies as needed. Knowledge of Go is a plus.
• Experience with cloud computing, for example, AWS, Google Cloud, or Azure, along with modern DevOps tools and techniques.
• Fluent in our core software tooling: Git, Unix/Linux, Docker, CI/CD. Has a strong opinion on their IDE/editor of choice
• Familiarity with modern machine learning tools, for instance TensorFlow, Keras, PyTorch or SKLearn. Commercial experience with these is not essential.
• Knowledge of MLOps is not essential, but some awareness of this emerging space is good to have.
• Experience with Kubernetes is a strong plus
• Fluency in English