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As a Machine Learning Architect, you'll be the driving force behind the next generation of our autonomous fulfillment solutions, leading the definition and design of cutting-edge machine learning versions for our core algorithms. You will be instrumental in evolving our product suite, ensuring our systems are more intelligent, adaptive, and efficient than ever before.

Key Responsibilities:

Own the architectural vision for all ML applications within our product suite, translating business needs into robust and scalable ML system designs.
Define the architecture and design patterns, and build POCs for ML algorithms.
Work with the engineering team on design and implementation of ML model pipelines, including data ingestion, training, validation, deployment, and monitoring.
Collaborate closely with software, robotics, product, and operations teams to align system goals with real-world fulfillment challenges.
Stay at the forefront of ML research and technology, identifying opportunities to apply new techniques to our products.

Required Qualifications:

Education: M.S/Ph.D in Computer Science, AI/ML, or a related field.
Experience: 10+ years of total experience in academia or industry.
Technical Expertise
Deep expertise in machine learning, deep learning
Hands-on experience in building and deploying production grade ML models
Experience with the full ML pipeline (data collection, model training, MLOps, deployment)
Experience with Generative-AI and LLMs
Experience with cloud platforms and their ML services (e.g. Vertex AI)
Ability to identify high-impact AI use cases and translate business problems into technical requirements
Experience building and implementing an AI strategy and roadmap for a team/organization
Strong understanding of data architecture and big data technologies (e.g., data lakes, streaming pipelines)
Experience with ML Ops principles and tools for continuous model delivery
(Nice to Have) - Contributions to open-source projects, research publications, or patents in ML/AI