About the job
At Redo, we possess a wealth of e-commerce data points from over 3,000 merchants, and we're excited to explore the vast potential it holds. As our pioneering Machine Learning Engineer, you will play a pivotal role in unlocking this value.
This is an individual contributor (IC) role where you will engage in coding daily, deploying models to production, and making foundational infrastructure decisions. We seek a motivated candidate who thrives in dynamic environments and is passionate about building innovative solutions.
About Redo
Redo is a cutting-edge post-purchase commerce platform that seamlessly integrates returns, order management, marketing, checkout optimization, and customer support into a unified system for e-commerce brands. Our mission is to empower over 3,000 merchants by transforming their post-purchase operations into a significant revenue stream.
As a Series A company with nearly 200 employees, we are profitable and experiencing rapid growth, headquartered in Draper, Utah.
Your Responsibilities
We have early-stage ML models that demonstrate great potential, but we need your expertise to fully realize their capabilities. You will take ownership of model development, from research to deployment, make decisions regarding infrastructure and tooling, and define the technical direction for data science at Redo.
Some exciting challenges you’ll tackle include:
Product Recommendations - Generate upsell suggestions based on millions of transactions, utilizing purchase and return histories, cart data, and browsing behaviors to present optimal offers at crucial moments.
Checkout Intent Prediction - Anticipate mid-session purchase probabilities to initiate tailored promotions before potential drop-offs occur.
Inventory Forecasting - Estimate restock schedules and quantities across a vast array of SKUs, factoring in trends and seasonal variations.
Additionally, you will identify and develop new high-value ML applications across our platform.
You will enhance our ML infrastructure (we currently operate on a basic Metaflow/Sagemaker framework that you can improve or overhaul), collaborate closely with product and data teams to uncover new opportunities, and lead the function as it expands.
Ideal Candidate Profile
We are looking for someone who has successfully deployed models to production, diagnosed performance issues, and managed the complete model lifecycle. We prioritize what you have accomplished over formal qualifications.
Proficient in Python and contemporary ML frameworks (e.g., PyTorch, scikit-learn).
Experience in constructing ML infrastructure (including training pipelines, deployment, and monitoring processes).
Strong data engineering skills: developing pipelines, complex SQL queries, and resolving data quality challenges.
Action-oriented mindset; you prefer to ship and iterate rather than engage in endless planning.
Business-oriented perspective; you focus on revenue implications, not just model performance metrics.
Ability to operate independently as the sole ML professional for the foreseeable future.
This position may not be suitable for those seeking a well-established ML team where they can learn from seasoned engineers.
