- Engineering Excellence: Oversee the development, scaling, and optimization of our ML platform and other products while ensuring the software engineering foundations are solid, scalable, and maintainable. This includes being very hands-on in leading efforts in system architecture, API design, data processing, and infrastructure supporting machine learning and application development.
- ML/MLOps Innovation: Guide the team in adopting and innovating in 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 8+ years of technology experience, with experience 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, 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. 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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Lead Product Engineer - Toronto, Canada - Fusemachines
Description
About Fusemachines
Fusemachines is a leading AI strategy, talent, and education services and products provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, United States, Canada, and Dominican Republic and more than 400 full-time employees). Fusemachines seeks to bring its global expertise in AI to transform companies around the world.
We seek a Lead Product Engineer with strong core software engineering experience and some experience with Machine Learning (ML)/ML Operations (MLOps) to spearhead our engineering initiatives for a new product line.
Bonus Points if you've worked on an ML Ops platform.
Responsibilities:
Qualifications:
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