Senior Lead- Machine Learning Engineer job opportunity at CommerceIQ.

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CommerceIQ Senior Lead- Machine Learning Engineer
Experience: 10-years
Pattern: full-time
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Engineering

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loacation Bengaluru, Karnataka,, India
loacation Bengaluru, Kar..........India

Company Overview CommerceIQ’s AI-powered digital commerce platform is revolutionizing the way brands sell online. Our unified ecommerce management solutions empower brands to make smarter, faster decisions through insights that optimize the digital shelf, increase retail media ROI and fuel incremental sales across the world’s largest marketplaces. With a global network of more than 900 retailers, our end-to-end platform helps 2,200+ of the world’s leading brands streamline marketing, supply chain, and sales operations to profitably grow market share in more than 50 countries. 10 out of the top 12 CPG brands work with us, including Coca-Cola, Nestle, Colgate-Palmolive, and Mondelez. We’ve raised over $200M from some of the top investors including SoftBank, Insight Partners, and Madrona. Learn more at commerceiq.ai. We are seeking a highly skilled senior technical lead to join our Agentic AI & Semantic Search team. This is a hands-on technical leadership role responsible for designing scalable AI systems that integrate agentic reasoning with semantic search to deliver real-time, context-rich, and commerce-aware decisions. You will define the technical vision, lead architectural strategy, and build retrieval, reasoning, and evaluation platforms that directly impact how the world’s top brands manage billions of dollars in eCommerce revenue. Key Responsibilities Architecture & Leadership: Define and drive the architecture for agentic AI systems that combine LLM reasoning, semantic search, and contextual grounding. AI Agent Development: Design frameworks that allow agents to autonomously analyze data, retrieve context, and execute workflows across e-commerce platforms. Semantic Search Excellence: Build scalable retrieval systems leveraging vector databases, embeddings pipelines, hybrid search (dense + sparse), and re-ranking models. Agent-Oriented Design: Enable agents to access structured and unstructured commerce data (retailer catalogs, customer demand, supply chain signals) with contextual reasoning and memory. AI Flywheel & Continuous Improvement: Design and operationalize evaluation datasets and benchmarking frameworks for agents and semantic search. Integrate annotation and labeling workflows to generate high-quality training and evaluation datasets. Build feedback loops where customer signals and agent outcomes drive system improvements. Metrics & Instrumentation: Define robust metrics for search relevance, grounding accuracy, reasoning quality, and business impact. Scalable Infrastructure: Architect distributed, low-latency, production-grade AI systems that serve mission-critical to CommerceIQ use cases. Cross-team Collaboration: Partner with Agentic AI engineers, and product managers to turn AI innovations into scalable solutions. Mentorship & Influence: Provide technical guidance, mentor engineers, and champion best practices in system design and AI engineering. Qualifications Must-Have 8-10+ years of software engineering experience, including 3+ years in Senior IC roles. In-depth knowledge of LLMs, agent frameworks, orchestration (LangChain, LlamaIndex, CrewAI, etc.), and retrieval-based methods. Experience in semantic search, retrieval systems, and distributed system design. Strong expertise in vector DBs (FAISS, Pinecone, Weaviate, Milvus), hybrid search, embeddings, and re-ranking models. Proven track record with RAG pipelines and integrating retrieval into LLM reasoning. Familiarity with evaluation dataset design, annotation tools (Labelbox, Scale AI, Prodigy, or in-house), and developing continuous evaluation pipelines. Proficient in Python and at least one systems language (Go, Java, or C++). Strong background in system design with the ability to lead end-to-end technical initiatives. Nice-to-Have Experience with LLM fine-tuning, alignment, or reinforcement learning with human feedback (RLHF). Background in NLP/IR research, query understanding, or contextual search optimization. Experience with eCommerce / retail datasets and domain-specific semantic search challenges. What We Value Commerce-First AI: Passion for applying AI to solve real-world commerce problems. Builder Mindset: Thrives in ambiguity and can translate vision into scalable systems. Pragmatic Innovation: Balances cutting-edge research with enterprise-grade reliability. Leadership Without Authority: Influences across teams through technical depth and clarity. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or any other category prohibited by applicable law. 

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