Lead ML Ops

Job Description :

We are a rapidly expanding AI startup that is transforming digital advertising with groundbreaking AI technology and innovative solutions. We are seeking a dynamic and highly skilled Lead MLOps Engineer to join our team and play a critical role in building the future of advertising.

As a Lead MLOps Engineer, you will be at the forefront of deploying and scaling cutting-edge machine learning models, including custom Transformer-based architectures, to predict consumer behavior. You will take ownership of managing high-performance inference systems, ensuring the seamless delivery of daily predictions for millions of consumers at an unprecedented scale.

The ideal candidate will be a seasoned expert in machine learning operations with deep experience managing large-scale data environments. You should have a proven track record of deploying end-to-end machine learning solutions at scale on cloud platforms (preferably in AWS), with a focus on performance and cost optimization and reliability.

Key Responsibilities :

• Lead MLOps Strategy : Architect and implement machine learning pipelines capable of handling millions of customer predictions
• Build Scalable Infrastructure : Design and build highly scalable and reliable cloud-based infrastructure on AWS to support the training, deployment, and monitoring of machine learning models at scale.
• Cost and Resource Management : Optimize the use of cloud resources, ensuring cost-effective scaling while maintaining high availability and performance standards.
• CI / CD Pipeline Implementation : Develop and optimize CI / CD pipelines specifically for ML models, ensuring smooth transitions from development to production.
• Automation and Optimization : Implement automation tools for model lifecycle management, model retraining, and data pipeline management
• Model Monitoring and Performance : Oversee the development and implementation of robust monitoring solutions to track model performance, identify issues, and ensure that models continue to meet business objectives.
• Collaboration : Work closely with cross-functional teams to ensure alignment between business needs, model performance, and infrastructure capabilities
• Documentation : Document processes, methodologies, and findings comprehensively and ensure that all documentation is kept up-to-date and accurate
• Innovation and Research : Stay up to date with new machine learning techniques, tools, and technologies, and apply this knowledge to improve existing solutions

Qualifications :

Nice to have :

What we offer :

We offer a competitive salary, benefits, and a dynamic work environment. If you are passionate about AI and predicting consumer behaviour, have a strong entrepreneurial spirit, and want to be part of a rapidly growing startup, we encourage you to apply for this exciting opportunity!