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Machine Learning Engineer III

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What you’ll work on

Full posting
  • Build end-to-end ML pipelines that deploy and scale models in production

  • Build an internal ML platform covering the full model lifecycle

  • Deploy LLMs and other algorithms on GPUs with distributed computing

  • Build tools for data ingestion, feature engineering and data management

  • Contribute to model management and model performance monitoring tools

From the employer’s posting
Contribute to development of multiple AI driven end to end pipelines
Build an end-to-end machine learning platform, covering all lifecycle stages of a model
Deploy cutting edge algorithms like LLMs etc. on GPUs along with distributed computing for scalability
Build tools and capabilities that help with data ingestion to feature engineering, data management and organisation
Contribute to tools and capabilities for model management and model performance monitoring
Education & alternatives
What we are looking for - - Bachelor’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 - Prior experience with deploying large scale machine learning models to production, both in batch and real-time setups
Apply at CommerceIQ

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Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 3, 20261 day ago
Recorded sightings
2
Last seen by us
Nov 4, 2026

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CommerceIQ is hiring

2 open jobs

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See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • Azure
  • Databricks
  • GCP
  • Spark
  • Terraform
  • Keras
  • NumPy
  • pandas
  • PyTorch
  • scikit-learn
  • TensorFlow
Where the posting names them
- Experience architecting and building an AI pipelines that supports productionization of ML models - Strong programming skills in a scientific computing language such as Python, SQL - Experience using frameworks for machine learning and data science like scikit-learn, pandas, NumPy
- Experience with distributed computing frameworks like Spark / Map-Reduce etc. - Cloud experience with any one provider ( AWS / GCP / Azure ) - Experience with Infra-as-code tools like Terraform
- Opportunity to work on cutting edge technologies in text and images data like LLMs, OCR, transformer based embeddings models. - Deploy code using the most advanced tech stack like AWS, GCP etc. - You will own projects end to end i.e., from exploration to final production
- Experience using frameworks for machine learning and data science like scikit-learn, pandas, NumPy - Experience with Databricks is a plus - Experience working with ML tools such as Tensorflow, Keras, and Pytorch
- Prior experience with deploying large scale machine learning models to production, both in batch and real-time setups - Experience with distributed computing frameworks like Spark / Map-Reduce etc. - Cloud experience with any one provider ( AWS / GCP / Azure )
- Cloud experience with any one provider ( AWS / GCP / Azure ) - Experience with Infra-as-code tools like Terraform - Experience and understanding of the entire machine learning pipeline from data ingestion to production
- Experience with Databricks is a plus - Experience working with ML tools such as Tensorflow, Keras, and Pytorch - Ability to take successful, complex research ideas from experimentation to production
- Strong programming skills in a scientific computing language such as Python, SQL - Experience using frameworks for machine learning and data science like scikit-learn, pandas, NumPy - Experience with Databricks is a plus

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

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.

Company Overview

At 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.

We are in hyper growth mode, having recently raised our Series D funding at unicorn valuation
(>$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.

What You’ll Be Doing

As 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. 

The 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. 

  • Contribute to development of multiple AI driven end to end pipelines that allows for deployment and scalability of machine learning models
  • Build an end-to-end machine learning platform, covering all lifecycle stages of a model, to ease model development and deployment
  • Build tools and capabilities that help with data ingestion to feature engineering, data management and organisation
  • Deploy cutting edge algorithms like LLMs etc. on GPUs along with distributed computing for scalability
  • Contribute to tools and capabilities for model management and model performance monitoring
  • Implement the best engineering practices for scaling ML-powered features, with a goal to enable the fast iteration of and efficient experimentation with novel features
  • Champion and own the ML infrastructure roadmap, in collaboration with Data Science and other platform teams

What we are looking for -

  • Bachelor’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 
  • Prior experience with deploying large scale machine learning models to production, both in batch and real-time setups
  • Experience with distributed computing frameworks like Spark / Map-Reduce etc.
  • Cloud experience with any one provider ( AWS / GCP / Azure )
  • Experience with Infra-as-code tools like Terraform
  • Experience and understanding of the entire machine learning pipeline from data ingestion to production
  • Experience with machine learning operations, software engineering, and architecture
  • Experience architecting and building an AI pipelines that supports productionization of ML models
  • Strong programming skills in a scientific computing language such as Python, SQL
  • Experience using frameworks for machine learning and data science like scikit-learn, pandas, NumPy
  • Experience with Databricks is a plus
  • Experience working with ML tools such as Tensorflow, Keras, and Pytorch
  • Ability to take successful, complex research ideas from experimentation to production
  • Excellent written and oral communication skills and the capability to drive cross-functional requirements with product and engineering teams
  • Good depth and breadth in machine learning (theory and practice), optimization methods, data mining, statistics and linear algebra

Why you will love to work with us -

We 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.

  • Opportunity to work on cutting edge technologies in text and images data like LLMs, OCR, transformer based embeddings models.
  • Deploy code using the most advanced tech stack like AWS, GCP etc.
  • You will own projects end to end i.e., from exploration to final production
  • You will be empowered to make decisions. It implies more responsibilities but high learning
  • Immense opportunities to learn and develop ML based SaaS products for brands and get company-wide recognition
  • Forget endless meetings. Get things done and start making an impact from day 1 
  • Work hard, have amazing fun, create history, build the future of eCommerce 
  • Start-up environment with a strong culture and values to accelerate your career 

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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Bengaluru, Karnataka, India

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