MLOps: ML Recall team (Remote)

About Us

Constructor is the next-generation platform for search and discovery in ecommerce, built to explicitly optimize for metrics like revenue, conversion rate, and profit. Our search engine is entirely invented in-house utilizing transformers and generative LLMs, and we use its core and personalization capabilities to power everything from search itself to recommendations to shopping agents. Engineering is by far our largest department, and we've built our proprietary engine to be the best on the market, having never lost an A/B test to a competitive technology. We're passionate about maintaining this and work on the bleeding edge of AI to do so.

Out of necessity, our engine is built for extreme scale and powers over 1 billion queries every day across 150 languages and roughly 100 countries. It is used by some of the biggest ecommerce companies in the world like Sephora, Under Armour, and Petco.

We're a passionate team who love solving problems and want to make our customers' and coworkers' lives better. We value empathy, openness, curiosity, continuous improvement, and are excited by metrics that matter. We believe that empowering everyone in a company to do what they do best can lead to great things.

Constructor is a U.S. based company that has been in the market since 2019. It was founded by Eli Finkelshteyn and Dan McCormick who still lead the company today.

The Team

The ML Recall team consistently delivers measurable KPI improvements for our customers in search, driving better relevance and user satisfaction. We’re focused on building transparent, reproducible, and scalable data-intensive workflows - empowering customers with visibility and trust. We own a set of critical high load services, ensuring high availability, low latency, and robust performance at scale. As a team, we foster a collaborative, curiosity-driven culture where every member has the opportunity to shape the future of search.

Challenges you’ll tackle

• Build, deploy, and maintain our search services, including I/O-bound web services, CPU- and GPU-bound workloads, and data services
• Develop using AWS CloudFormation, AWS CDK, Jenkins, and GitHub Actions
• Optimize system performance - particularly for scaling large ML models efficiently
• Maintain and enhance our observability stack, including tools like Prometheus, Grafana, PagerDuty, and AWS CloudWatch
• Collaborate with both technical and non-technical stakeholders to design and evolve search functionality
• Contribute to broader ML improvements across the platform

• Excellent communicator with a passion for performance optimization
• Excited to build scalable ML platforms and practical search systems
• Strong proficiency in Python
• Proven experience designing, developing, and maintaining high-load, distributed, real-time services
• Demonstrated experience setting up and improving CI/CD pipelines
• Hands-on experience with cloud platforms (AWS preferred) and Infrastructure as Code (e.g., Terraform, CloudFormation)
• Proficiency with big data technologies across the end-to-end ML product lifecycle
• Solid experience in server-side web service development and API design

What can help to stand out

• Experience with Rust or another low-level programming language
• Deep knowledge of data structures, algorithms, and their trade-offs