ML Platform & Infrastructure Engineer

agi-inc; Santa Fe (NM); On-site; USD 110,000 - 170,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Relocation assistance

Immigration support

Job summary

AGI, Inc. is seeking a software engineer to build end‑to‑end ML infrastructure and tooling for trustworthy consumer‑grade agents. You will design CI/CD pipelines for ML, create evaluation harnesses, and develop SDKs, CLIs, and lightweight UIs for researchers.

You will also implement observability dashboards and performance metrics, ensuring scalable, reliable experimentation and fast feedback for model iteration.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• 3+ years in Software Engineering, MLOps, or ML Infrastructure.
• Strong Python proficiency.
• Experience building internal developer tools, CLIs, or dashboards.
• Experience with cloud infrastructure (AWS or GCP) and containerization (Docker, Kubernetes).

Responsibilities

• Training Automation: Design and implement robust CI/CD pipelines for machine learning workflows.
• Evaluation Infrastructure: Build scalable evaluation harnesses to benchmark models on every merge.
• Research Tooling: Develop internal SDKs, CLIs, and lightweight UIs to empower researchers.
• Observability & Performance: Implement tracking for latency, throughput, errors, GPU usage, and costs.

Skills

Software Engineering

Python

MLOps

Internal tools

Cloud proficiency

Education

Bachelor’s degree in CS/Engineering or equivalent

Tools

Docker

Kubernetes

AWS

GCP

Job description

Think Different. Build the Future.

Our Mission

Build everyday AGI. Trustworthy, consumer-grade agents that redefine human–AI collaboration for millions. Software shouldn’t wait for commands; it should partner with you, amplifying what you can do every single day.

Why AGI, Inc.

We’re a stealth team of elite founders and AI researchers, with backgrounds spanning Stanford, OpenAI, and DeepMind. We’re industry leaders in mobile and computer-use agents, bringing these capabilities to consumer scale.

Grounded in years of agent research, our AI is designed with trustworthiness and reliability as core pillars, not afterthoughts.

We are supported by tier-1 investors who funded the first generation of AI giants; now they’re backing us to build the next: everyday AGI. (Watch the demo)

If you see possibility where others see limits, read on.

What You’ll Do

Training Automation: Design and implement robust CI/CD pipelines for machine learning workflows. Automate nightly and on-demand training runs, including data ingestion, job orchestration, checkpointing, and artifact management, with reliability as a first-class requirement.

Evaluation Infrastructure: Build scalable evaluation harnesses that automatically benchmark models on every merge. Optimize latency and resource usage so experimentation stays fast, and performance regressions are caught immediately.

Research Tooling: Develop internal SDKs, CLIs, and lightweight UIs (e.g., Streamlit, Retool) that empower researchers to:

• Inspect trajectories and traces
• Visualize model failures
• Curate and manage datasets
• Iterate without friction

You’ll make experimentation ergonomic.

Observability & Performance: Implement comprehensive tracking for:

• Model latency, throughput, and error rates
• GPU utilization and cluster health
• Inference cost and unit economics

Build dashboards and alerting systems that give real-time visibility into system performance and reliability.

Minimum Qualifications

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience
• 3+ years in Software Engineering, MLOps, or ML Infrastructure
• Strong Python proficiency
• Experience building internal developer tools, CLIs, or dashboards
• Experience with cloud infrastructure (AWS or GCP) and containerization (Docker, Kubernetes)

Preferred Qualifications

• Experience designing CI/CD pipelines specifically for ML workflows
• Familiarity with LLM serving stacks such as vLLM or TGI
• Experience managing GPU clusters and optimizing distributed workloads

Why This Role Matters

Great research without great infrastructure slows to a crawl. Great infrastructure multiplies the impact of every researcher.

You will define how experiments scale, how reliability is measured, and how quickly we can ship improvements to real users. The systems you build will directly shape the speed and quality of our progress toward everyday AGI.

Our Culture

All in, in person — work moves faster face-to-face

Ship by default — novel and polished can coexist, speed is the feature

One band, one sound — radical candor, zero politics, help each other win

Perks

Competitive company-sponsored medical, dental, and vision insurance

Top-tier relocation and immigration support