ML Cloud Infra Engineer: Scale AI Pipelines

HavocAI; Providence (RI); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Health insurance

401k (Matching)

Equity package

Unlimited PTO with 2 weeks minimum

Work/Home Office Stipend

Parental leave

Job summary

HavocAI, based in Providence, RI, seeks a Machine Learning Cloud Infrastructure Engineer to build and operate the data, training, and deployment infrastructure powering its autonomous ML workloads.

You will connect data lakes, telemetry stores, simulations, and cloud compute to enable scalable, reproducible ML from data capture to production deployment. Hybrid of software and ML infrastructure work, with strong emphasis on reliability and security.

Qualifications

• 3+ years of software/infra/data/ML infrastructure experience.
• Strong Python experience; Go or C++ preferred.
• Experience building and operating production services, APIs, data pipelines, or infrastructure.
• Hands-on experience with ML workflows such as dataset preparation, model training, evaluation, or deployment.
• Experience with cloud infrastructure, preferably AWS, and Infrastructure as Code.
• Hands-on experience with Kubernetes and containerized environments.
• Knowledge of reliability, observability, testing, automation, and maintainability.

Responsibilities

• Build pipelines transforming multi-modal data into curated, versioned training datasets.
• Develop reproducible training/evaluation workflows across cloud compute and GPUs.
• Build and maintain model deployment infrastructure for packaging, serving, and versioning.
• Implement experiment tracking, dataset lineage, model versioning, and other reproducible ML capabilities.
• Own data schema versioning and migration across pipelines and services.

Skills

Python

Go

C++

Production services

Cloud infra

Kubernetes

CI/CD

Data pipelines

Tools

MLflow

Weights & Biases

Kubeflow

Ray

Airflow

Dagster

AWS GovCloud

Job description

HavocAI, based in Providence, RI, seeks a Machine Learning Cloud Infrastructure Engineer to build and operate the data, training, and deployment infrastructure powering its autonomous ML workloads.

You will connect data lakes, telemetry stores, simulations, and cloud compute to enable scalable, reproducible ML from data capture to production deployment. Hybrid of software and ML infrastructure work, with strong emphasis on reliability and security.