Senior Backend Engineer: Machine Learning Infrastructure

About Us

Launched in 2019, Constructor is an AI-first e-commerce search and discovery platform that helps shoppers find the right products at the right time and enables leading global e-commerce brands to drive meaningful revenue and conversion gains.

About The Role

The ML Infrastructure team builds and operates the shared backend services and platform capabilities that Constructor's ML and product teams rely on to develop, deploy, and run machine learning at scale - from model serving (including LLMs) to the specialized storages and data pipelines behind it.

We are a service team by nature: our roadmap is shaped by the needs of product teams, and we succeed when they can move faster with less friction. We're looking for a Senior Backend Engineer who is comfortable with, and motivated by this dynamic, and who will take end-to-end ownership of core services.

In the near and mid-term, our focus areas include:

• Making ML workloads easy to run, scale, and operate for every team
• Providing self-service, configurable infrastructure components to ML and product teams
• Owning and evolving core ML services and related pipelines with a high bar for reliability and performance

Challenges you will tackle

• Design, build, and operate high-load distributed backend services that power the company's ML infrastructure
• Take end-to-end ownership of core ML services and related data pipelines: from design and implementation to deployment, observability, and continuous improvement
• Partner with ML and product teams to understand their needs and turn them into reliable, reusable platform capabilities
• Make and defend technical decisions: evaluate trade-offs, design first, and own the outcome
• Be responsible for what you and your team do

Requirements

• 5+ years of professional experience in backend or platform engineering
• Extensive Python knowledge (our primary language)
• Hands-on experience developing on a public cloud (AWS, GCP, or Azure) or with self-managed Kubernetes - AWS is our primary platform, but we're not limited to it
• Experience designing and building distributed, high-load services and APIs
• Strong knowledge of data structures, algorithms, and their trade-offs
• Design-driven engineering mindset: we're a coding-assistant-friendly environment and expect you to use modern AI tools - but you lead with system design and a strong understanding of their applicability and trade-offs
• Ownership and proactivity: you can't close your eyes to problems, but are ready to solve them and take responsibility for outcomes
• You are friendly and willing to help your teammates & others

Nice to have:

• Experience with Rust (or C/C++/Go) - a strong plus
• Experience developing or contributing to ML platforms or ML infrastructure - a strong plus
• Experience setting up and operating any vector database (Qdrant, Milvus, Weaviate, OpenSearch, pgvector, etc.) - a strong plus
• Experience with model serving / inference infrastructure, including LLMs
• Experience with Infrastructure as Code (Terraform or similar)

Benefits

• 🏝️ Unlimited vacation time - we strongly encourage all of our employees take at least 3 weeks per year
• 🌎 Fully remote team - choose where you live
• 🛋️ Work from home stipend! We want you to have the resources you need to set up your home office
• 💻 Apple laptops provided for new employees
• 🧑‍🎓 Training and development budget for every employee, refreshed each year
• 👪 Maternity & Paternity leave for qualified employees
• 🧠 Work with smart people who will help you grow and make a meaningful impact
• 💵 Base salary: $80k–$120k USD, depending on knowledge, skills, experience, and interview results
• 📈 Stock options - offered in addition to the base salary
• 🎉 Regular team offsites to connect and collaborate