ML Infrastructure Engineer

AI AGENTS LLC
San Mateo, CA, United States
3 days ago
Apply on startup.jobs
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Data Analysis Distributed Systems Large Language Models AI Platforms Machine Learning Operations Hardware Infrastructure

Job description

You’ll own our inference and model-serving infrastructure end to end. This isn’t a research role. It’s a build role: you’re setting up and scaling the systems that let our agents actually run in production, fast and reliably, at increasing concurrency.

You report to Sofus and work closely with our ML and infra teams.

What You’ll Own

  • Set up and scale inference/Ray Serve for ML and LLM model serving, integrated with our data analysis and agent workflows
  • Scale agent GPU infrastructure for concurrency and efficiency across multiple agent workloads
  • Optimize and improve the engine builder and model server that power scalable agent orchestration, * Familiarity with AIBrix Why Join

  • A rare chance to shape both company and product direction as an early team engineer
  • Work alongside engineers and researchers from LinkedIn, Visa, Meta, and Branch
  • Onsite culture in San Mateo, built for deep collaboration and high-velocity building
  • Full benefits (medical, dental, vision, 401k)
  • We sponsor H-1B visas and assist with immigration We value builders over rĂŠsumĂŠs. If this role excites you but you don’t check every box, we still want to hear from you. zaimler is an equal opportunity employer.

Requirements

  • Proven ability to build scalable ML/AI platforms from scratch, end-to-end, for production use cases. You’ve owned a zero-to-one build before, or can show you’re capable of it
  • Deep understanding of the inference stack: vLLM, KV cache, and the optimization layers underneath model serving
  • Experience building distributed systems for AI/ML workloads at scale, connecting them to real product or vertical integrations
  • 3+ years of relevant experience. We care about capability, not tenure

About the company

About zaimler AI agents can’t reason over data they don’t understand. Enterprise data today is fragmented across dozens of systems with no shared context, meaning, or structure, and that’s why most enterprise AI is failing. The shift from copilots to autonomous agents is creating an entirely new infrastructure layer, and we’re building it. zaimler is the context infrastructure for the agentic era: a platform that automatically discovers domain knowledge, maps relationships, and gives AI agents the semantic understanding to operate with precision at scale. Imagine knowledge graphs that support real-time inference, built for systems that need to reason, not just retrieve. zaimler was founded by Biswajit Das (ex-VP Engineering, Truera), a Data Infra veteran and former Chief Architect at Visa, and Sofus Macskassy (ex-Director of Engineering, LinkedIn), who built one of the largest knowledge graphs in production in the industry at LinkedIn. We’re growing and deploying with major enterprises across insurance, travel, and technology. If you want to build infrastructure that the next decade of enterprise AI runs on, we’d love to talk.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on startup.jobs
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

2:36 min

Choosing between managed AI platforms and custom governance

PÊter Farkas PÊter Farkas ¡ Europe 2026 Virtual

1:48 min

Automating exploratory data analysis within training pipelines

Dora Petrella ¡ World Congress 2023

1:29 min

Overcoming challenges in AI-assisted distributed system development

Przemysław Ładyński Przemysław Ładyński · World Congress 2026 Europe

2:08 min

Essential engineering roles in the generative AI space

Mary Grygleski Mary Grygleski ¡ LIVE

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou ¡ Coffee With Developers

6:26 min

Bringing accurate time synchronization to global distributed systems

Werner Vogels Werner Vogels ¡ World Congress 2026 Europe

Videos

See all

Related articles

See all