Resonate is seeking a Head of Data Science and Machine Learning Engineering to own the entire AI/ML lifecycle, from research to production deployment, to drive innovation and enhance their AI-powered consumer data platform.
Requirements
- Deep expertise in modern machine learning techniques, including gradient boosting, Bayesian latent class models, causal inference, deep learning, embeddings, and GNNs.
- Deep, hands-on experience with MLOps principles and tools to support repeatable research and deployment (e.g., CI/CD for ML, model registries, feature stores, model monitoring).
- Strong software engineering fundamentals and architectural skills.
- Hands-on experience with AWS AI/ML services, particularly Bedrock and SageMaker.
- Proficiency in Python and common data science libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Agentic workflow experience is desirable
Responsibilities
- Lead, manage, and mentor our integrated Data Science and Machine Learning Engineering teams ensuring full accountability for both methodology and delivery.
- Drive the strategic vision for data science and AI, ensuring alignment with our product roadmap and business goals.
- Take full ownership of the end-to-end machine learning lifecycle, from model ideation and development to deployment, monitoring, and maintenance in a production environment.
- Propose, lead, and communicate an R&D agenda to advance our product lines, with a focus on methodologies, modeling techniques, and agentic systems.
- Drive the architectural vision for our MLOps infrastructure, working with the MLE team to install and champion best practices for scalable, automated, and robust model deployment.
- Provide hands-on leadership in the development and deployment of advanced machine learning models, including deep learning techniques, embeddings, neural networks, and GNNs.
- Leverage your expertise in AWS Bedrock, SageMaker, TensorFlow, and PyTorch to build and scale our AI/ML capabilities.
Other
- Exceptional communication and presentation skills, with the ability to articulate a clear and compelling vision.
- A "player-coach" mentality, capable of guiding a lean, senior team while also contributing technically.
- Comfortability communicating with clients, reporters, and industry analysts
- A collaborative and cross-functional mindset, with the ability to work effectively with engineering, product, and go-to-market teams.
- A continuous learning mindset and a passion for staying at the forefront of the AI/ML field.
