About the Opportunity
A fast-scaling AI-driven enterprise technology firm, https://jobeax.com/link/Z11ervWk39OSiwes builds mission-critical deployed AI solutions for global defense, logistics, and industrial automation clients. We embed engineers directly with customer teams to design, deploy, and maintain real-time edge-AI systems—bridging the gap between cutting-edge ML research and operational environments. Our Forward Deployed Engineers are the technical linchpins who translate prototype models into rugged, field-tested systems that perform under pressure. Role & Responsibilities

Deploy, debug, and optimize machine learning models in constrained edge environments—on-prem, air-gapped, or offline-capable systems.
Partner directly with client engineering teams to integrate AI pipelines into existing IT/OT infrastructures using Docker, Kubernetes, and embedded Linux.
Develop and maintain robust SDKs, monitoring tools, and health-check scripts to ensure ML model reliability under real-world conditions.
Translate ML research outputs (TensorFlow/PyTorch models) into production-grade C++/Python inference services with low-latency, high-throughput performance.
Conduct on-site system audits, performance benchmarking, and root-cause analysis for model drift or hardware bottlenecks.
Document deployment playbooks, configuration standards, and client handoff materials to enable sustainable client ownership.

Skills & Qualifications
Must-Have

Python
TensorFlow
PyTorch
Docker
Kubernetes
Linux
SDK Development
Edge AI

Preferred

C++
ONNX Runtime
MLOps Tools (MLflow, Kubeflow)

Benefits & Culture Highlights

Work on high-impact, classified and unclassified national infrastructure projects with real-world consequences.
Fast-track technical ownership—lead deployments from day one and present directly to client CTOs.
Hybrid travel model: 60% on-site client locations across India, 40% Bangalore HQ with flexible scheduling.

Forward Deployed Engineer

Start with your email