{"id":3611775,"url":"https://alion.io/job/commerceiq-machine-learning-engineer-iii","title":"Machine Learning Engineer III","company":{"id":2208,"name":"CommerceIQ","domain":"commerceiq.ai","url":"https://alion.io/company/commerceiq","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":81,"open_postings":4,"ghost_share":0,"stale_share":0.75,"repost_share":0,"time_to_fill_p50_days":54,"computed_at":"2026-11-04T06:34:25Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"GCP","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Embeddings","optional":true},{"name":"Keras","optional":true},{"name":"OCR","optional":true},{"name":"PyTorch","optional":true},{"name":"TensorFlow","optional":true}],"status":"live","first_seen_at":"2026-11-02T12:12:56Z","employer_posted_date":"2026-11-02","last_verified_at":"2026-11-04T18:38:18Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"The Company\nCommerceIQ 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.\n\n2,200+\n\nCustomers\n\n10 of Top 12\n\nCPG Companies\n\n900+\n\nRetailers Connected\n\n$200M+\n\nRaised\n\nCustomers 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.\nCompany Overview\nAt CommerceIQ, we help consumer brands accelerate their retail ecommerce market share growth and profitability through machine learning algorithms. We are building the world’s most complete and sophisticated Retail Ecommerce Management Platform, which connects and intelligently automates the management of retail ecommerce channels like Amazon, Walmart, and Instacart, across the entire ecommerce operational chain of retail media management, sales operations, supply chain, and digital self analytics.\nWe are in hyper growth mode, having recently raised our Series D funding at unicorn valuation\n(>$1B) and ended our third year of triple-digit revenue growth. Continued acceleration of our growth is fueled by landing new customers, expanding our platform through new products, managing new retail ecommerce platforms, and delivering exceptional customer service to unlock high net retention rates.\nWhat You’ll Be Doing\nAs an ML Engineer in the team, you will work closely with Data Science, Engineering, Platform, Product and Operations teams to build state-of- the-art ML based solutions for B2B SaaS products. This will entail applying advanced ML algorithms at scale for core products and developing robust end to end production pipelines which includes Human-in-the-Loop component to boost the quality. \nThe ideal candidate will have a strong background in machine learning model development, deploying large scale, high throughput machine learning pipelines to production, experience with developing and managing frameworks for machine learning platforms, which they can utilise to manage and improve our company’s AI/ML initiatives. \nContribute to development of multiple AI driven end to end pipelines that allows for deployment and scalability of machine learning models\nBuild an end-to-end machine learning platform, covering all lifecycle stages of a model, to ease model development and deployment\nBuild tools and capabilities that help with data ingestion to feature engineering, data management and organisation\nDeploy cutting edge algorithms like LLMs etc. on GPUs along with distributed computing for scalability\nContribute to tools and capabilities for model management and model performance monitoring\nImplement the best engineering practices for scaling ML-powered features, with a goal to enable the fast iteration of and efficient experimentation with novel features\nChampion and own the ML infrastructure roadmap, in collaboration with Data Science and other platform teams\nWhat we are looking for -\nBachelor’s or Masters in Computer Science or Maths/Stats from a reputed college with 7+ years of experience in solving of experience in machine learning engineering problems \nPrior experience with deploying large scale machine learning models to production, both in batch and real-time setups\nExperience with distributed computing frameworks like Spark / Map-Reduce etc.\nCloud experience with any one provider ( AWS / GCP / Azure )\nExperience with Infra-as-code tools like Terraform\nExperience and understanding of the entire machine learning pipeline from data ingestion to production\nExperience with machine learning operations, software engineering, and architecture\nExperience architecting and building an AI pipelines that supports productionization of ML models\nStrong programming skills in a scientific computing language such as Python, SQL\nExperience using frameworks for machine learning and data science like scikit-learn, pandas, NumPy\nExperience with Databricks is a plus\nExperience working with ML tools such as Tensorflow, Keras, and Pytorch\nAbility to take successful, complex research ideas from experimentation to production\nExcellent written and oral communication skills and the capability to drive cross-functional requirements with product and engineering teams\nGood depth and breadth in machine learning (theory and practice), optimization methods, data mining, statistics and linear algebra\nWhy you will love to work with us -\nWe have multiple brands, which are among the biggest brands operating on Amazon, as our customers. You will be responsible for working with their data and developing models and algorithms to drive lift in tune of hundreds of thousands of dollars.\nOpportunity to work on cutting edge technologies in text and images data like LLMs, OCR, transformer based embeddings models.\nDeploy code using the most advanced tech stack like AWS, GCP etc.\nYou will own projects end to end i.e., from exploration to final production\nYou will be empowered to make decisions. It implies more responsibilities but high learning\nImmense opportunities to learn and develop ML based SaaS products for brands and get company-wide recognition\nForget endless meetings. Get things done and start making an impact from day 1 \nWork hard, have amazing fun, create history, build the future of eCommerce \nStart-up environment with a strong culture and values to accelerate your career \nWe are an equal opportunity employer and value diversity at our company. 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