Staff Engineer - Machine Learning

<p><strong>The Impact You Will Create</strong></p><p>As a Staff Machine Learning Engineer, you will serve as the critical architectural bridge between cutting-edge Data Science research and massive-scale, product-ready implementation. You will move beyond standard feature delivery to define the technical vision and infrastructure that brings sophisticated algorithms to life. Your work will directly result in:</p><ul><li><p><strong>Massive Scale &amp; Reliability:</strong> Architecting and deploying robust ML APIs and pipelines capable of serving millions of requests with ultra-low latency and unwavering reliability.</p></li><li><p><strong>Engineering Excellence:</strong> Setting the gold standard for ML Engineering practices, MLOps, and system design across the organization.</p></li><li><p><strong>Accelerated AI Innovation:</strong> Transforming theoretical models into high-performance, production-grade systems, directly shrinking the time-to-market for complex ML business solutions.</p></li><li><p><strong>Cross-Organizational Multiplier:</strong> Acting as a strategic technical anchor, influencing cross-product architects, leading POCs, and mentoring teams to ensure tight technical alignment across all engineering groups.</p></li></ul><p><strong>Roles &amp; Responsibilities</strong></p><ul><li><p><strong>End-to-End Pipeline Architecture:</strong> Architect, build, and manage comprehensive, highly scalable ML pipelines covering data pre-processing, model generation, automated deployment, cross-validation, and active feedback loops.</p></li><li><p><strong>ML Algorithm Implementation:</strong> Partner deeply with Data Scientists to translate complex, theoretical ML models and algorithms into high-performance, production-grade code.</p></li><li><p><strong>High-Performance Service Delivery:</strong> Design, develop, and deploy highly extensible ML API services rigorously optimized for low latency and massive scalability.</p></li><li><p><strong>Operational Intelligence &amp; Observability:</strong> Devise and build advanced monitoring capabilities to track both engineering system health and ML model performance metrics (drift, accuracy, etc.) over the long term.</p></li><li><p><strong>Strategic Innovation &amp; Architecture:</strong> Architect solutions from scratch, leading Proof of Concept (POC) initiatives across various tech stacks to validate optimal solutions for complex business challenges.</p></li><li><p><strong>Technical Leadership &amp; Execution:</strong> Own the full lifecycle of feature delivery autonomously—from requirement gathering with product stakeholders to final deployment—while collaborating with cross-product architects to drive platform adoption.</p></li></ul> <p><strong>Qualifications</strong></p><ul><li><p><strong>Experience:</strong> 9+ years of progressive, highly relevant experience in software engineering and machine learning development.</p></li><li><p><strong>Production Excellence:</strong> A proven, demonstrable track record of successfully architecting, building, and productionizing complex Machine Learning solutions at an enterprise scale.</p></li><li><p><strong>MLOps Mastery:</strong> Deep, practical experience with modern MLOps practices, ensuring seamless, automated, and secure model transitions from development and training into production environments.</p></li><li><p><strong>Education:</strong> A Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Mathematics, or a related quantitative field.</p></li></ul><p><strong>Skills</strong></p><ul><li><p><strong>Core Programming:</strong> Expert-level Object-Oriented Programming (OOP) expertise in Python and Java.</p></li><li><p><strong>ML &amp; Deep Learning Frameworks:</strong> Mastery of industry-standard ML libraries and Deep Learning frameworks, including PyTorch, Keras, TensorFlow, and TFServing.</p></li><li><p><strong>Foundational Engineering:</strong> Deep, advanced understanding of Data Structures, Algorithms (DSA), an ... (truncated, view full listing at source)