Senior Computer Vision / ML Engineer

## About Artikate Studio We're a deep-tech engineering firm that has been building software since 2016. We engineer AI-powered systems for defence institutions, government bodies, national-scale enterprises, and D2C brands — from a single AI module to entire mission-critical platforms. We're AWS and GCP Certified Partners, Razorpay Technology Partners, and Red Hat Partners. Our engineers are dedicated, senior-led teams that embed with our clients, ship working software every two weeks, and work to a defence-grade security baseline as standard. ## About the role We're hiring a Senior Computer Vision / ML Engineer to build the AI that powers our systems — real-time detection and inspection across multi feeds, models that run on the edge and in air-gapped environments, and pipelines that keep them accurate in production. This is a hands-on builder role: you'll own models end to end, from data and training through optimization and deployment, working alongside our Solution Architect and platform engineers. If you've shipped computer-vision models that ran reliably in the real world — not just in a notebook — and you care about latency, robustness, and what happens after the model is "done," this is for you. ## What you'll build - Train, fine-tune and evaluate **detection, classification and segmentation models** (YOLO-family and similar) for production accuracy and robustness. - Own **data pipelines** — collection, annotation workflows and QA, augmentation, and dataset versioning — because model quality starts with data quality. - **Optimize models for edge and on-prem inference** — quantization, ONNX / TensorRT, and latency/throughput tuning on GPU and edge devices. - Build **real-time, multi-camera / multi-feed inference** systems that hold accuracy at scale. - Deploy into **air-gapped and on-premise** environments, and stand up **retraining / continuous-learning loops** so models improve over time. - Write clean, tested, maintainable code and collaborate closely on architecture and integration. ## Must-have experience - 3–7 years building production ML / computer-vision systems — models that actually shipped and ran in the field. - Strong Python and **PyTorch** (TensorFlow a plus). - Deep computer vision: object detection, segmentation, and classification (YOLO-family, Detectron, or equivalent), plus OpenCV. - Model optimization and deployment: ONNX, TensorRT, quantization, and edge/GPU inference. - Hands-on with data and annotation pipelines — labelling workflows, QA, dataset versioning. - Solid software-engineering fundamentals: Git, testing, clean code, Docker. - Comfortable owning a model end to end, from raw data to a deployed, monitored system. ## Nice to have - Edge AI hardware (NVIDIA Jetson) and GPU-cluster experience. - MLOps tooling — model registry, monitoring, retraining pipelines. - Air-gapped / on-prem deployment and handling of sensitive or classified data. - LLM / RAG exposure (Llama-class, LangChain, Hugging Face) and ASR (Whisper). - Industrial / manufacturing machine vision and harsh-environment deployment; awareness of PLC/CNC integration. - Cloud (AWS / GCP). ## How we work - **Senior-led delivery** — no hand-off to juniors after the pitch. - **2-week sprint velocity** — working software every fortnight. - **Defence-grade security baseline** — air-gapped and zero-egress are everyday work. - **Embedded partnership** — dedicated teams that treat the client's product as their own. - **IST-aligned** — no timezone friction. ## Engagement details - **Location:** Gurugram, with occasional travel to client sites. - **Type:** Full-time, senior individual contributor. - **Start:** Immediate.