Senior Backend Engineer: Machine Learning Infrastructure
Constructor1 month ago
Remote, EMEASenior
Base Salary
$80k - $120k/yr
Responsibilities
- Design, build, and operate high-load distributed backend services for the company’s ML infrastructure.
- Own core ML services and related data pipelines from design and implementation through deployment, observability, and continuous improvement.
- Build self-service, configurable infrastructure components that help ML and product teams run workloads at scale.
- Partner with ML and product teams to translate their needs into reliable, reusable platform capabilities.
- Evaluate technical trade-offs, lead system design, and take end-to-end responsibility for outcomes.
Requirements
- 5+ years of professional experience in backend or platform engineering.
- Extensive knowledge of Python, the team’s primary programming language.
- Hands-on experience developing on AWS, GCP, or Azure, or operating self-managed Kubernetes; AWS is the primary platform.
- Experience designing and building distributed, high-load services and APIs.
- Strong knowledge of data structures, algorithms, and their trade-offs.
- Ability to lead with system design while using modern AI coding tools appropriately.
- Ownership, proactivity, collaboration, and willingness to help teammates and others.
- Experience with Rust or C, C++, or Go is preferred.
- Experience with ML platforms or ML infrastructure is preferred.
- Experience operating vector databases such as Qdrant, Milvus, Weaviate, OpenSearch, or pgvector is preferred.
- Experience with model-serving or inference infrastructure, including LLMs, is preferred.
- Experience with Infrastructure as Code such as Terraform is preferred.
Benefits
- Fully remote work arrangement with flexibility to choose where to live.
- Unlimited vacation time, with encouragement to take at least three weeks annually.
- Work-from-home stipend and Apple laptops for new employees.
- Annual training and development budget.
- Maternity and paternity leave for qualified employees.
- Regular team offsites and opportunities to work with experienced teammates.
- Stock options offered in addition to base salary.
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