Computer Vision Engineer

BookMyMentor; Sector 10; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Ripik.AI is hiring a Computer Vision Engineer to own end-to-end CV problems—from data strategy through model development, edge deployment, and production monitoring—for industrial applications. You will tackle hard vision challenges, optimize inference on edge hardware, and stay at the forefront of CV research while ensuring robust production readiness.

The role demands 2–5 years of hands-on CV experience, strong Python and PyTorch skills, and experience deploying models to edge or on-prem

Qualifications

• Bachelor's in Computer Science, AI/ML, Electrical Engineering, or a related field.
• 1–3 years of hands-on experience in computer vision with production deployment.
• Proficiency in Python and PyTorch; strong OpenCV knowledge.
• Experience deploying models to edge or on-prem hardware; Docker/Kubernetes experience.
• Familiarity with modern CV tasks and model families; cloud platforms beneficial.

Responsibilities

• Own CV problems end-to-end from data strategy to deployment and monitoring across industrial portfolios.
• Build models for hard vision challenges like rare defects and low-light environments.
• Evaluate new CV models and translate papers into production value.
• Follow standards for vision stack, data/versioning, and CI/CD for models.
• Optimize inference for latency and cost on edge GPUs and cloud instances.
• Debug production issues on live deployments and ship fixes with guardrails.
• Promote data-centric AI with high-quality annotations and active learning.
• Develop robust evaluation frameworks and cross-functional collaboration.

Skills

python

PyTorch

OpenCV

Edge deployment

Industrial CV

Education

Bachelor's in CS/AI/EE or related

Tools

Docker

ONNX Runtime

TensorRT

OpenVINO

CVAT/Label Studio

Job description

Ripik.AI Verified

Computer Vision Engineer

Mid Level (2-5 years)

Posted 7/25/2026

Ripik.AI is an Accel-backed Applied AI company building computer vision and process-optimisation agents for the world's largest industrial enterprises across steel, cement, aluminium, chemicals, pharma, and power. Our Vision AI platform acts as an automated pair of eyes on the shop floor — monitoring materials, equipment, and processes 24/7 with 95%+ accuracy, eliminating human error, and delivering measurable gains in throughput, yield, energy efficiency, and safety.We work with marquee customers including Tata Steel, JSW, ArcelorMittal, Vedanta, Godrej & Boyce, Grasim, Holcim, and Jindal Steel, and are scaling globally across India, the Middle East, Europe, and North America. We are one of the few Indian AI product start-ups to be a partner to GCP, Azure, and AWS, and the AI partner of choice for CII, ICC, and NASSCOM.The RoleWe are looking for a hands-on Computer Vision Engineer to work on the models that power Ripik's industrial AI platform. You will own CV problems end-to-end — from data strategy and annotation to model development, edge deployment, and production monitoring — for some of the most complex vision problems in heavy industry.Key ResponsibilitiesOwn computer vision problems end-to-end — from problem framing and data strategy through model development, edge deployment, and production monitoring — across Ripik's industrial portfolio (steel, cement, pharma, paints, and beyond).Build models for hard vision challenges — novel defect types, extreme class imbalance, multi-camera fusion, low-light / high-noise factory environments, and real-time inference on constrained edge hardware.Stay at the cutting edge of CV research and rapidly evaluate and adopt new models and techniques — YOLO26, SAM 3, Vision Transformers (DINOv2, Swin), Grounding DINO, RF-DETR, zero-shot / open-vocabulary detection (YOLO-World, CLIP) — translating papers into production value.Follow and contribute to engineering standards for the vision stack — model training pipelines, data versioning (DVC), annotation workflows (CVAT, Roboflow, Label Studio), experiment tracking (W&B, MLflow), edge export formats (TensorRT, ONNX, OpenVINO), and CI/CD for model updates.Drive inference optimisation — quantisation (INT8 / FP16, GPTQ), pruning, knowledge distillation, and batching strategies — to meet latency and cost targets across NVIDIA Jetson, industrial PCs, and cloud GPU instances.Debug production issues on live customer deployments — trace performance drops, root-cause failure modes, and ship fixes with the right guardrails.Champion a data-centric AI approach — invest in annotation quality, active learning, synthetic data generation, and feedback loops from production rather than only chasing bigger models.Build robust evaluation frameworks — domain-specific metrics, A/B testing against production baselines, and systematic failure-mode analysis to ensure models deliver real business impact.Partner cross-functionally with product, field engineering, operations, and leadership — translate business problems into well‑scoped modelling projects and communicate results clearly.

Requirements

• Bachelor's in Computer Science, AI/ML, Electrical Engineering, or a related field.
• 1–3 years of hands‑on experience in computer vision — with a strong track record of taking models from research / prototyping through to production deployment.
• Deep proficiency in Python and PyTorch; strong working knowledge of OpenCV, Albumentations, and image / video processing fundamentals.
• Demonstrated expertise across multiple CV tasks — object detection, instance / semantic / panoptic segmentation, anomaly detection, pose estimation, or tracking.
• Hands‑on experience with modern model families — YOLO (v8 / v11 / v26), transformer-based detectors (RT-DETR, DETR, RF-DETR), segmentation models (SAM / SAM 2), and CNN backbones (ResNet, EfficientNet, ConvNeXt, Vision Transformers).
• Production experience deploying models to edge or on‑prem hardware using TensorRT, ONNX Runtime, or OpenVINO; comfort with Docker, Kubernetes, and at least one cloud platform (AWS / Azure / GCP).
• Strong first‑principles problem‑solving — comfortable navigating novel, unstructured problems where no playbook exists.
• Experience in a high‑growth start‑up or similarly fast‑paced environment.
• Excellent communication — able to distil complex technical concepts for non-technical stakeholders, write clear documentation, and present results to leadership and customers.
• Good to Have
• Experience with industrial or manufacturing domains — understanding of factory‑floor constraints, camera setups, lighting variability, and integration with PLCs / SCADA systems.
• Familiarity with zero‑shot and open‑vocabulary detection (Grounding DINO, YOLO-World, CLIP) and foundation models (DINOv2, SAM 3, Florence) for data‑efficient learning.
• Exposure to vision–language models (GPT‑4o vision, Gemini, LLaVA) for combining visual inspection with natural‑language reporting or operator copilots.
• Knowledge of 3D vision, depth estimation, point‑cloud processing, or multi‑camera calibration for volumetric industrial inspection.
• Experience with multi‑object tracking (ByteTrack, BoT‑SORT) and video analytics pipelines for continuous production‑line monitoring.
• Contributions to open‑source CV projects, publications in top‑tier venues (CVPR, ECCV, ICCV, NeurIPS), or strong Kaggle competition results.

Skills Required

python

About the Company

Ripik.AI

Technology

Ripik.ai is a fast‑growing industrial AI SAAS start‑up founded by IIT D alumni and with extensive experiencein McKinsey, IBM, Google and others. It is backed by marquee VC funds like Accel, Venture Highway and 25+ illustrious angels including 14 unicorn founders.Ripik.ai builds patented full stack software for automation of decision making on the factory floor. Today, they are deployed at more than 15 of the largest and most prestigious enterprises in India including the market leaders in steel, aluminium, cement, pharma, paints, consumer goods and others.It is one of India’s very few AI product start‑ups to be a partner to GCP, Azure and AWS. We are also the AI partner of choice for CII, ICC and NASSCOM.The world today is standing on the foundations of automation built over the last century, one of the last laps of which comprised the deployment of hundreds of cameras in order to build visibility into the process, safety, quality, personnel and equipment tracking, amongst others.It is humanly impossible to monitor 24 x 7 the hundreds of continuous video feeds. Hence, visual anomalies and early warnings go undetected. Usually every camera is installed to solve a specific purpose, but that purpose goes unaddressed.Ripik.ai 's vision AI platform continuously monitors the video feeds and provides real‑time alerts so that whatever one needs to detect in any video feed is detected and the right workflow is triggered.We work with industrial enterprises globally to advance their industry 4.0 efforts and harness significant bottom‑line improvement via the deployment of computer vision applications.