ML Cloud Infrastructure Engineer
HavocAI · Remote · Remote ·
COMPENSATION
$150k – $175k
Listed on the employer's job board (Ashby)
- Fully remote (US)
- Python + Go/C++
- AWS + Kubernetes
- US Citizenship required
- Equity package
Join Havoc to engineer the cloud infrastructure that powers all-domain collaborative autonomy. You will build scalable pipelines and platforms that connect data lakes, simulation environments, and cloud compute, enabling teams to move from raw data to production deployment efficiently.
This position requires a strong background in software or infrastructure engineering with hands-on ML experience. You will solve ambiguous technical problems while ensuring systems remain secure, observable, and reliable in a fast-paced environment.
What you'll do
- Build pipelines transforming multi-modal raw data into curated, versioned training datasets
- Develop reproducible training and evaluation workflows scaling across cloud GPU resources
- Maintain model deployment infrastructure for packaging, serving, inference, and rollback
- Design and operate scalable AWS infrastructure using Infrastructure as Code
- Manage Kubernetes/EKS workloads for training, batch processing, and model serving
- Implement monitoring, logging, and observability across training jobs and deployed models
- Partner with cross-functional teams to integrate edge data capture with cloud training
What you'll need
- 3+ years in software, infrastructure, data engineering, or ML infrastructure
- Strong programming skills in Python, with preference for Go or C++
- Experience building production services, APIs, data pipelines, or developer platforms
- Hands-on experience with ML workflows including dataset preparation and model training
- Proficiency with cloud infrastructure, preferably AWS, and Infrastructure as Code
- Experience with Kubernetes and containerized environments
- U.S. Citizenship and ability to obtain a U.S. Government security clearance
Nice to have
- Experience with MLOps platforms like MLflow, Weights & Biases, or Kubeflow
- Knowledge of GPU scheduling, distributed training, or large-scale ML workloads
- Background working with multi-modal datasets such as imagery, video, or sensor data
- Experience supporting autonomy, robotics, simulation, or real-time systems
- Familiarity with AWS GovCloud or compliance-driven environments like FedRAMP
Stack
- Python
- Go
- C++
- AWS
- Kubernetes
- EKS
- MLflow
- Kubeflow
How you'll work
- Headquartered in Providence, Rhode Island
- Requires U.S. Citizenship for security clearance
- Fast-paced environment with high ownership expectations
What you get
- 100% employer-paid health insurance
- Dental and vision coverage for employees and families
- Employer-paid life insurance
- 401k program with matching contributions
- Unlimited PTO with enforced two-week minimum
- Equity package included
- Work from home office stipend
- Global Entry reimbursement
- 16 weeks paid parental leave
- Monthly health and wellness stipend