• Build production-grade optimization and ML solutions that drive Instacart’s fulfillment decisions end-to-end in a rapidly evolving, high-scale environment. • Design, implement, and deploy algorithms for order batching, real-time shopper assignment, routing, and marketplace positioning using techniques such as MIP/CP-SAT, heuristics/metaheuristics, and learning-to-rank. • Own the full model lifecycle: problem formulation, data pipelines and features, offline evaluation and simulation, A/B testing, staged rollouts, and ongoing monitoring/observability. • Build reliable, low-latency services in Python (and, where performance dictates, C++ or Go) that integrate with solvers (e.g., OR-Tools, Gurobi, CPLEX) and run on cloud infrastructure with Docker/Kubernetes. • Partner with product, operations, and data science to define roadmaps and success metrics; deliver measurable impact to on-time rates, shopper utilization, cost per order, and customer experience. • Leverage experimentation and causal methods along with offline counterfactual replay/simulation to validate changes and de-risk launches. • Contribute to engineering excellence through code reviews, design docs, robust testing, and participation in an on-call rotation for mission-critical fulfillment services; mentor peers and raise the technical bar.

• Develop and improve computer vision models • Build and maintain traditional ML models • Work with LLM APIs for structured outputs • Deploy, package, and serve ML models • Monitor model quality and performance metrics • Collaborate closely with engineering teams

Role Description We are looking for an Emerson Machine Works SME with hands‑on experience using the platform’s core capabilities. The role will support configuration, usage, and enablement of Machine Works across industrial use cases. Key Responsibilities - Act as Emerson Machine Works platform SME for delivery and support - Configure assets, machine models, and standard platform features - Support health indicators, diagnostics, and basic analytics - Assist teams with platform navigation, configuration, and troubleshooting - Support solution demos, PoCs, and early‑stage implementations Qualifications - Hands‑on experience with Emerson Machine Works - Understanding of asset health and machinery reliability concepts - Experience working in OT / industrial environments - Strong communication and documentation skills Requirements - 5-10+ years of experience Nice to Have - Exposure to Emerson Plantweb or APM ecosystem - Mining, oil & gas, manufacturing, or energy domain experience Company Description Kaleidoscope, an Infosys Company, is an equal opportunity employer, and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, spouse of protected veteran, or disability.

• Design and deploy ML models that extract and structure competitive intelligence signals — supply availability, pricing patterns, and market saturation — from large-scale crawled datasets across global competitors • Build and maintain end-to-end ML pipelines spanning feature engineering, offline training, and low-latency online serving, ensuring high data fidelity and resilience to upstream schema drift • Apply entity resolution and matching techniques to accurately map competitor listings and markets to Airbnb's internal supply taxonomy, using methods such as embedding models, gradient boosted trees, and transformer-based architectures • Partner with the crawling infrastructure engineer, data engineers, and product teams to translate competitive intelligence needs into well-defined ML problem formulations and measurable success criteria • Run rigorous offline and online experiments to evaluate model quality, and collaborate with Pricing, Supply Growth, and Strategy stakeholders to turn model outputs into actionable business decisions • Stay current with the latest advances in ML and AI, identifying opportunities to incorporate new techniques into the competitive intelligence platform