Software Engineer 3

TL;DR

Software Engineer 3 (Backend/Infrastructure): Building core systems and services that power model inference at scale for hirify.global Atlas with an accent on real-time, low-latency, and high-scale inference. Focus on improving performance, autoscaling, GPU utilization, and resource efficiency in a cloud-native environment.

Location: Based in Palo Alto, CA or Seattle, WA with an in-office or hybrid work model.

Salary: $109,000—$215,000 USD

Company

hirify.global is built for change, empowering our customers and our people to innovate at the speed of the market.

What you will do

• Design and build components of a multi-tenant inference platform integrated directly with hirify.global 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.

Requirements

• 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.
• Comfortable working across functional teams, including ML researchers, backend engineers, and platform teams.
• Motivated to work on systems integrated into hirify.global 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.

Culture & Benefits

• Committed to developing a supportive and enriching culture for everyone.
• Employee affinity groups.
• Generous parental leave policy.
• Flexible paid time off.
• Mental health counseling.