Director of Engineering

• Strategic Leadership: Develop and execute a cohesive strategy that equally emphasizes advancements in ML/MLOps and core software engineering practices, ensuring they collectively support and enhance our product's vision and capabilities.
• Engineering Excellence: Oversee the development, scaling, and optimization of our ML platform while ensuring the software engineering foundations are solid, scalable, and maintainable. This includes leading efforts in system architecture, API design, data processing, and infrastructure that supports both machine learning and application development.
• ML/MLOps Innovation: Guide the team in adopting and innovating in the areas of machine learning model development, deployment, monitoring, and management. Ensure the ML lifecycle is fully integrated with our CI/CD pipelines, Kubernetes, emphasizing automation, reproducibility, and scalability.
• Software Development Leadership: Champion best practices in software development, including design patterns, code quality, security, and performance. Ensure that our core software engineering practices enable and enhance our ML capabilities, fostering a culture of excellence.
• Team Building and Mentorship: Lead, mentor, and lead a diverse distributed engineering team of software developers, ML engineers, and data engineers. Create an environment that encourages innovation, collaboration, and continuous learning across both software engineering and ML/ML Ops domains.
• Cross-functional Collaboration: Serve as a bridge between the ML/MLOps and software engineering teams, ensuring tight integration and collaboration. Work closely with product management, UX/UI designers, and other stakeholders to deliver a seamless, high-quality product.

• Experience: At least 5 years of technology experience, with experience in leadership roles managing teams that specialize in both ML/MLOps and core software engineering. Experience with ML metrics observability, workflow orchestration, service release automation, notebook development, and LLM deployment is a plus.
• Technical Expertise: A deep understanding of Enterprise Software architecture, design patterns, and modern programming languages coupled with a strong foundation in machine learning algorithms, data modeling, and MLOps practices across the major cloud providers (AWS, Azure, GCP).
• Leadership and Vision: Proven ability to lead, inspire, and grow multidisciplinary engineering teams. A Strategic thinker with the capacity to balance short-term goals with long-term vision.
• Collaborative Skills: Excellent communication and collaboration skills, capable of fostering positive relationships across engineering teams and with other business units.
• Education: Advanced degree in Computer Science, Engineering, or a related field, with a strong background in both AI/machine learning and software engineering.

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