Machine Learning Engineer 2

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.

Roles and responsibilities :
– Part of Data Science team to develop high impact, scalable and sustainable ML solutions
– Collaborate with Senior Data Scientists and product managers to understand customer
needs and co-own the deployment and maintenance of key ML models
– Work closely with Data Scientists on text and image data using the leading ML techniques
in GenAI / OCR / Image processing
– Develop end to end pipeline and further enhancement of solutions for scale and stability
– Build quality checks, unit tests and diagnostic reports for code and output quality
monitoring using python, SQL and yaml
– Conduct modeling experiments and report automation
– Scheduling, automating and stabilizing the current AWS pipeline using jenkins, Step
Function, Lambda, Runtime, Sagemaker
– Develop in-house capability to deploy custom models on Sagemaker endpoints taking
care of platform and library compatibility
– Explore GCP capabilities to deploy projects – Code Versioning, end points, GCS, Bigquery
and automation / scheduling
 

Preferred Qualifications :
– Curiosity to learn Advanced ML, Data Science + ML Ops ; looking to build a career and
expertise in Data Science
– 1-2 years working experience as a Data Engineer / ML Engineer / Data Analyst
– Hands-on experience with Python and SQL is must
– Understanding of data modeling, data access, data storage, and optimization techniques
– Experience working with cloud-based technologies and development processes
– An ideal candidate would be expected to have basic familiarity of GCP and AWS
Infrastructure. Advanced knowledge of ML Ops related tools like Sagemaker, ECR, Step
Functions, Vertex AI is preferred
– Ability to quickly understand the tech pipeline / project infrastructure; engage deeply with
Team members; Delivery quickly on new development or optimization related action items
– Quick action oriented approach preferred over brainstorming on very long term ideas