--- title: 'Machine Learning Engineer III at CommerceIQ' canonical: 'https://feeny.ai/job/machine-learning-engineer-iii-commerceiq-bengaluru-3test7fh8ye4' type: 'job' last_seen: '2026-11-05' --- # Machine Learning Engineer III at CommerceIQ - **Company:** CommerceIQ - **Location:** Bengaluru, India - **Posted:** 2026-11-02 - **Last confirmed live:** 2026-11-05 - **Apply:** https://job-boards.greenhouse.io/commerceiq/jobs/8045855003 ## Job description The Company CommerceIQ is building the AI platform that runs commerce for the world's largest brands. We are not selling AI demos. We are shipping AI agents for content, media, and sales into the workflows of the Fortune 100 every week. 2,200+ Customers 10 of Top 12 CPG Companies 900+ Retailers Connected $200M+ Raised Customers include Coca-Cola, Nestlé, Colgate-Palmolive, Mondelez, Samsung, and Kellogg's. Backed by SoftBank, Insight Partners, and Madrona. Headquartered in Mountain View with teams across the US, India, Canada, and the UK. Pre-IPO. ## About the Role We are looking for a hands-on Machine Learning Engineer III to build and run the ML and AI systems behind our agents for content, media, and sales. You will work closely with Data Science, Engineering, Platform, Product, and Operations teams to take models and LLM-based agents from idea to production, and keep them reliable, fast, and cost-efficient at scale. This is an engineering role first: you will own your systems end to end, including the infrastructure they run on. We look for builders who ship v0s quickly, iterate against evals, and stay adaptable about models and frameworks as the field moves. Key Responsibilities : - AI Agents & Harnesses: Design, build, and ship production agents and the harnesses around them: tool and action design, context window management (retrieval, summarization, compaction), model selection and routing, memory and state, and subagent and parallel tool-call patterns. Iterate until agents reliably complete real customer tasks. - ML Pipelines: Build end-to-end batch and real-time pipelines for classical ML and LLM workloads, from data ingestion to deployment. - Infrastructure: Own the infrastructure your systems run on: containers, Kubernetes, queues, caches, and cloud services on AWS/GCP, managed as code. - Reliability & Quality: Meet latency, throughput, and cost budgets using caching, batching, and parallel execution. Handle rate limits, retries, and failures gracefully. Instrument agents with tracing to profile behavior, find bottlenecks, and catch quality regressions before customers do. - Evals: Build eval sets from production traces, expert examples, and past failures, plus automated checks and LLM judges that measure model and agent quality. Use them to gate every prompt, model, and code change. - Feedback & Experimentation: Turn reviewer and customer feedback into measurable improvements through human-in-the-loop workflows, A/B tests, offline replays, and staged rollouts. - Technical Ownership: Review designs and code, raise the engineering bar, and contribute to the ML and AI roadmap with Data Science and Platform teams. Required Skills : - 5+ years of experience building and running ML or AI systems in production, including at least 1 year on LLM-based applications. Bachelor's or Master's in Computer Science, Maths/Stats, or a related field, or equivalent practical experience. - Strong programming skills in Python, including async and concurrent programming, and solid SQL. - Hands-on experience building production agents and LLM applications: tool and function design, context window management, RAG and embeddings, structured outputs, multi-step and multi-agent orchestration, and model selection across hosted APIs (OpenAI, Anthropic, Gemini, or similar). - Daily use of coding agents such as Claude Code or Cursor, with the judgment to review and verify their output. - Solid ML fundamentals (evaluation metrics, overfitting, leakage, drift) and experience deploying models in both batch and real-time setups, including knowing when classical ML beats an LLM. - Strong infrastructure skills: Docker, Kubernetes, at least one cloud provider (AWS / GCP / Azure), and production observability (OpenTelemetry, Grafana, Prometheus, or equivalent). - Working experience with Terraform and CI/CD, distributed data processing (Spark or Databricks), and workflow orchestration or messaging (Airflow, Temporal, Kafka, or similar). - Strong system design skills. You can reason clearly about cost, latency, failure modes, and scale trade-offs. - Excellent written and verbal communication, and the ability to drive cross-functional requirements with Product and Engineering. Preferred Skills : - Advanced evals: LLM-as-judge calibration against human labels, golden datasets, trace capture and replay, and statistically sound comparisons of variants with confidence intervals. - Agent frameworks & protocols: Hands-on with LangGraph, the OpenAI Agents SDK, MCP, or similar, and knowing when a thin custom harness beats a framework. - Simulation environments: Simulated users and synthetic tasks for testing multi-step agents before they reach customers. - LLM observability & prompt management: Tools like LangSmith, Opik, or Langfuse for tracing, versioning, and debugging prompts in production. - Cost & latency tuning: Prompt caching, batching, model routing, and output-length control for high-volume LLM workloads. - Guardrails: Schema validation, content and safety checks, and fallbacks for when the model gets it wrong. - Vector search: Databricks Vector Search, pgvector, OpenSearch, or similar. Bonus Skills : - Fine-tuning: Adapting models (SFT, LoRA/PEFT, preference tuning, distillation) and serving them efficiently, including on GPUs (vLLM, TGI, or equivalent). - Research: A track record of turning research into production impact. Publications or open-source contributions are a plus. - Experience in ecommerce, retail media, or B2B SaaS. Why you will love to work with us - - Your work ships. Our AI agents run inside the workflows of the world's largest brands every week, and you will see the impact directly. - Work across classical ML, LLMs, agents, and infrastructure, not one narrow slice. - You will own projects end to end, from exploration to production. - Forget endless meetings. Get things done and start making an impact from day 1. 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. ## About CommerceIQ ## Company Overview - **One-liner**: CommerceIQ provides a unified AI platform for retail ecommerce teams to automate and optimize sales, content, and media across thousands of retailers globally. - **Entity Type**: Private (Series D, closed in 2022) - **Headquarters**: Mountain View, California, USA (with additional offices in Bengaluru, India and London, UK) - **Founded**: 2018 - **Founders**: Guru Hariharan (CEO) ## Core Business - **Primary industry**: Retail ecommerce technology / AI-driven commerce automation - **Target customers**: B2B – consumer brands (both SMB and enterprise) selling on Amazon, Walmart, Instacart, and 1,450+ other retail endpoints - **Mission statement**: “We drive profitable ecommerce growth with intelligent automation” [[commerceiq.ai/about-us]](https://www.commerceiq.ai/about-us) ## Products & Services - **AllyAI**: An always-on AI commerce operator that automates pricing adjustments, media spend optimization, and content visibility improvements across retailers. Acts as a “co-pilot” for ecommerce teams. - **Content Agent**: Automates management of thousands of SKUs across hundreds of retailers, ensuring accuracy, compliance, and AEO (Amazon Eligibility Optimization). - **Digital Shelf Analytics**: Tracks digital shelf performance 24/7 across 1,450+ retailers, providing prioritized insights and ready-to-use WBR reports. - **eCommerce Sales Management**: Forecasts sales vs. plan, prioritizes next-best actions, and automates execution to close gaps. - **Retail Media Management**: Optimizes retail media bids and pacing using 50+ shelf-aware signals, driving incremental sales. All products are SaaS-based, delivered via a unified platform. ## Market Standing - **Valuation/Market Cap**: Not disclosed (private company) - **Key Metric**: Total funding raised – Series D in 2022 (amount undisclosed); notable investors include Insight Partners, Madrona Ventures, and Shasta Ventures [[commerceiq.ai/leadership]](https://www.commerceiq.ai/leadership) - **Notable Investors/Partners**: Insight Partners, Madrona Ventures, Shasta Ventures; the platform connects to Amazon, Walmart, Instacart, and 1,450+ other retail endpoints - **Growth Signals**: - 2,200+ brands use the platform - Global network of 900+ retailers - In 2021, CommerceIQ automations drove 250 million actions that contributed to profitable market share gains for customers - Offices in US, India, and UK, with a growing global team ## Competitive Advantages - **Unified platform**: One platform covering content, analytics, sales, and media – eliminating siloed tools and spreadsheets. - **AI-native automation**: AllyAI and other agents continuously monitor and act on pricing, content, and media without manual intervention. - **Shelf-aware signals**: Proprietary intelligence that captures real-time shelf data across 1,450+ retailers, enabling better bid optimization and content decisions. - **Deep retailer integrations**: Direct connections to Amazon, Walmart, Instacart, and many others, built specifically for the algorithmic nature of retail marketplaces. ## Strategic Focus CommerceIQ is doubling down on AI-driven automation to help brands scale profitable growth. The company’s leadership principles emphasize “relentless innovation” and “exception-based automated decision making.” Near-term priorities include expanding platform capabilities (e.g., Director of Engineering – AI, Forward Deployed Engineering) and deepening international reach (85+ countries). The company is investing heavily in product teams (AI, data science) and growth partnerships. ## Why Work Here - **Culture & values**: Emphasis on ownership, hiring and developing the best, and moving quickly. Diversity, equity, and inclusion are core to the company’s identity [[commerceiq.ai/careers]](https://www.commerceiq.ai/careers). - **Work model**: Hybrid and remote options depending on role and location; generous PTO including vacation, holidays, and global recharge days. - **Compensation & perks**: Competitive base pay, equity (stock options for eligible roles), comprehensive health/dental/vision insurance, gym stipends, mental health support, and learning & development opportunities. - **Engineering culture**: Strong focus on internal growth and promotion; many team members expand roles from within. Active engineering hubs in Mountain View, Toronto, Bengaluru, and London. - **Global team**: Cross-regional collaboration across US, UK, and India; inclusive environment that values diverse backgrounds. ## Sources 1. [commerceiq.ai](https://www.commerceiq.ai/) – Main site, product descriptions 2. [commerceiq.ai/careers](https://www.commerceiq.ai/careers) – Culture, perks, DEI, hybrid policy 3. [commerceiq.ai/about-us](https://www.commerceiq.ai/about-us) – Mission, metrics, offices, investors 4. [job-boards.greenhouse.io/commerceiq](https://job-boards.greenhouse.io/commerceiq) – Open roles, locations 5. [commerceiq.ai/leadership](https://www.commerceiq.ai/leadership) – Executive team, board of directors, investors ## Other roles at CommerceIQ - [Software Development Engineer - III](https://feeny.ai/job/software-development-engineer-iii-commerceiq-bengaluru-jb41edp6494g) — Bengaluru, India - [Software Development Engineer - III](https://feeny.ai/job/software-development-engineer-iii-commerceiq-bengaluru-w185b2s5hwnq) — Bengaluru, India - [Senior Account Executive](https://feeny.ai/job/senior-account-executive-commerceiq-united-states-p0qn6gtvj5qa) — United States - [Data Scientist II](https://feeny.ai/job/data-scientist-ii-commerceiq-bengaluru-s2a4rv3ftr2r) — Bengaluru, India - [Senior Technical Program Manager](https://feeny.ai/job/senior-technical-program-manager-commerceiq-bengaluru-f3xcmwpa47k4) — Bengaluru, India - [Security Engineer III](https://feeny.ai/job/security-engineer-iii-commerceiq-bengaluru-amdw0fqkjz4k) — Bengaluru, India - [Financial Analyst](https://feeny.ai/job/financial-analyst-commerceiq-mountain-view-xhfyt5rxn8bv) — Mountain View, CA - [Business Development Representative](https://feeny.ai/job/business-development-representative-commerceiq-united-states-mtvvxn218fmf) — United States - [Customer Success Manager, Display Advertising](https://feeny.ai/job/customer-success-manager-display-advertising-commerceiq-united-states-fzcg55qykbaj) — United States - [Director, Finance](https://feeny.ai/job/director-finance-commerceiq-bengaluru-bvst1v213anf) — Bengaluru, India