Job Description

As a Senior Machine Learning Engineer at Synapse Analytics, you'll be a machine learning leader, driving the development of complex and critical model-driven product areas. You'll take ownership of major features and initiatives, contributing significantly to the product strategy and ensuring the high quality, scalability, and market fit of our applications. You'll also play a crucial role in mentoring and guiding less experienced engineers, fostering a culture of excellence and continuous improvement.

Responsibilities

Lead the product discovery, definition, and delivery of major machine learning initiatives and complex features. Design and advocate for significant model architecture decisions, ensuring alignment with the overall business strategy and user needs. Set and enforce high standards for machine learning practices, best practices, and principles across the team, leading by example. Mentor and coach Machine Learning Engineer I and II colleagues, providing deep technical guidance, fostering their growth, and leading strategic discussions. Solve highly complex, ambiguous, and strategic modeling challenges that have a broad impact on the product or the organization. Collaborate extensively with senior leadership, engineering, design, and other stakeholders to define requirements, evaluate feasibility, and deliver robust, integrated solutions. Identify and address critical market opportunities, user pain points, and competitive threats through machine learning. Proactively identify, prioritize, and lead efforts to address model debt and process inefficiencies. Research, evaluate, and propose new ML strategies and technologies to improve the product offering and development processes. Act as a primary point of contact for complex model-related issues, leading diagnosis and resolution. BS/BA, MS, or PhD equivalent in Computer Science, Engineering, or a related field. 4+ years of experience in a machine learning or applied science role. Deep expertise in Python and extensive experience with ML frameworks like PyTorch, Tensorflow, and scikit-learn. Expert knowledge and experience in defining model vision, strategy, and roadmaps. Excellent experience in designing, building, and managing large-scale, production-grade machine learning systems. Expert understanding of computer vision, NLP, or another core ML domain relevant to our products. Excellent troubleshooting skills, including solving complex user problems and navigating business ambiguities. Expert understanding of the end-to-end product development lifecycle. Deep knowledge of MLOps, system architecture, and the technical aspects of software development. Strong experience in mentoring and developing junior team members. * Excellent communication skills and experience in stakeholder management and influencing without authority.