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: ● Bachelor's, Master's or PhD in Computer Science, Engineering, AI or a related field ● At least 5+ years of experience in machine learning operations ● Extensive experience deploying, managing, and scaling AI/ML workloads for large scale data on AWS services such as EC2, SageMaker, Lambda, and other AWS offerings ● Proficiency in Docker, Kubernetes, and container orchestration, with experience in deploying machine learning models in these environments ● Proven track record in designing and implementing CI/CD pipelines for ML models ● Experience in performance tuning, cost optimization, and managing resources in cloud-based environments. ● Strong understanding of machine learning concepts, including supervised and unsupervised learning and deep learning ● Strong programming skills in Python, and experience with frameworks and libraries such as TensorFlow, PyTorch, scikit-learn and Keras ● Excellent problem-solving and analytical skills ● Strong communication and collaboration skills Nice to have: ● Prior experience working in a fast-paced startup environment 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!

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