ML Cloud Platform Engineer

HavocAI; Rhode Island; Remote; USD 140,000 - 200,000; Full time

Benefits offered by this job

Health insurance

401k matching

Unlimited PTO

Equity package

WFH stipend

Parental leave

Job summary

HavocAI is seeking a Machine Learning Cloud Infrastructure Engineer to build and operate the infrastructure used to train, evaluate, deploy, and monitor ML models safely and reliably. You will connect data lakes, telemetry stores, simulation environments, and cloud compute to production deployments.

This role suits engineers with hands-on ML experience who enjoy building production systems at the intersection of data, models, compute, and autonomy, and who thrive in fast-paced, scalable

Qualifications

• 3+ years of experience in software engineering, infrastructure engineering, data engineering, ML infrastructure, or a related field.
• Strong programming experience in Python, with experience in Go, C++, or another systems-oriented language preferred.
• Experience building and operating production services, APIs, data pipelines, developer platforms, 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.

Responsibilities

• Build pipelines transforming multi-modal data into curated, versioned training datasets.
• Develop scalable training and evaluation workflows across cloud compute and GPUs.
• Build and maintain model deployment infrastructure for packaging, serving, inference, versioning, and rollback.
• Implement experiment tracking, dataset lineage, model versioning for reproducible ML development.
• Own data schema versioning and migration across pipelines, data lakes, and services.
• Design, build, and operate scalable AWS infrastructure using Infrastructure as Code.
• Build and maintain Kubernetes workloads for training, batch processing, evaluation, and model serving.
• Develop self-service tooling for compute scheduling, storage, data access, training, and deployment.
• Improve utilization, scalability, and cost efficiency across cloud and accelerator infrastructure.
• Build infrastructure enabling engineering teams to launch workloads safely with minimal overhead.
• Build evaluation frameworks and regression testing for model quality and data integrity.
• Establish quality and reliability signals to determine production readiness of models.
• Develop monitoring, logging, tracing, and observability across training, pipelines, and deployed models.

Skills

Python programming

Go or C++

Production services

ML workflows

Cloud infrastructure

Kubernetes

Observability & reliability

Security & data management

Cross-functional collaboration

Education

Bachelor's degree in CS/Engineering or equivalent

Tools

AWS

Kubernetes/EKS

Terraform

Docker

Job description

HavocAI is seeking a Machine Learning Cloud Infrastructure Engineer to build and operate the infrastructure used to train, evaluate, deploy, and monitor ML models safely and reliably. You will connect data lakes, telemetry stores, simulation environments, and cloud compute to production deployments.

This role suits engineers with hands-on ML experience who enjoy building production systems at the intersection of data, models, compute, and autonomy, and who thrive in fast-paced, scalable