8bit.ai
Website:
8bit.ai
Job details:
About The Opportunity
A fast-scaling AI-driven enterprise technology firm, 8bit.ai 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.
Skills: python,algorithms,system design,agentic ai
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