# Software Engineer 3

**Company:** [MongoDB](https://hotfix.jobs/companies/mongodb)
**Location:** Palo Alto, CA, Seattle, WA
**Role:** Fullstack Engineering
**Salary:** $109k – $215k/yr
**Experience:** 2+ years
**Skills:** Go, Rust, Python, C++, Kubernetes, vLLM, Mongodb Atlas, Distributed Systems, Cloud-Native Architectures, Faiss
**Posted:** 2026-02-11

> Build scalable inference platform for embedding models integrated with MongoDB Atlas, focusing on real-time, low-latency systems for semantic search. Requires 2+ years backend experience with Go, Rust, Python, or C++ and distributed systems knowledge.

## Job Description

## What You’ll Do
- Design and build components of a multi-tenant inference platform integrated directly with MongoDB Atlas, supporting semantic search and hybrid retrieval
- Collaborate with AI engineers and researchers to productionize inference for embedding models and rerankers — enabling both batch and real-time use cases. Contribute to platform capabilities such as latency-aware routing, model versioning, health monitoring, and observability
- Improve performance, autoscaling, GPU utilization, and resource efficiency in a cloud-native environment
- Work across product, infrastructure, and ML teams to ensure the inference platform meets the scale, reliability, and latency demands of Atlas users
- Gain hands-on experience with tools like vLLM and container orchestration with Kubernetes

## Who You Are
- 2+ years of experience building backend or infrastructure systems at scale
- Strong software engineering skills in languages such as **Go**, **Rust**, **Python**, or **C++**, with an emphasis on performance and reliability
- Experienced in cloud-native architectures, distributed systems, and multi-tenant service design
- Familiar with concepts in ML model serving and inference runtimes, even if not directly deploying models
- Knowledge of vector search systems (e.g., **Faiss**, **HNSW**, **ScaNN**) is a plus
- Comfortable working across functional teams, including ML researchers, backend engineers, and platform teams
- Motivated to work on systems integrated into MongoDB Atlas and used by thousands of developers

## Nice to Have
- Experience integrating infrastructure with production ML workloads
- Understanding of hybrid retrieval, prompt-driven systems, or retrieval-augmented generation (RAG)
- Contributions to open-source infrastructure for ML serving or search

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