🚀Hiring: AI/ML Engineer – Computer Vision | Ignatiuz | Indore | 2–6 Years |

Ignatiuz is hiring an AI/ML Engineer – Computer Vision in Indore! If you have hands-on experience in Computer Vision, Python, PyTorch, YOLO, real-time video analytics and GPU/edge deployment, this opportunity could be a strong next step for your AI engineering career. 🤖📹

📍 Location: Indore, India – On-site
💼 Experience: 2–6 Years
🎯 Role: AI/ML Engineer – Computer Vision
🏢 Company: Ignatiuz

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🏢 About Ignatiuz

Ignatiuz is a technology and digital transformation company working across areas including AI, cloud engineering, product engineering, digital journeys and emerging technologies. Its current AI initiatives include IGNA, a governed AI operations platform designed to help organizations deploy AI agents, connect enterprise systems and operationalize AI securely.

The company works with industries including life sciences, financial services, manufacturing, retail, insurance and public-sector organizations, giving engineers opportunities to work on technology addressing real business and operational challenges.

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💼 Why Is This Role Great for Your Experience?

This isn’t a conventional model-development position where your work ends after achieving a good accuracy score. The JD focuses on taking Computer Vision models into real-time, production environments.

You could gain practical experience in:

🔹 Real-time object detection and tracking
🔹 CCTV, RTSP and IP-camera video analytics
🔹 YOLO / RT-DETR-based production solutions
🔹 GPU optimization and inference acceleration
🔹 TensorRT and edge deployment
🔹 Dockerized AI applications
🔹 REST API integration
🔹 AWS cloud environments
🔹 Linux-based deployment and troubleshooting

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🧠 Skills Required

Candidates should focus on the following technical areas:

Core AI/ML: Python, Machine Learning, Deep Learning, neural networks, model evaluation and optimization.

Computer Vision: OpenCV, image/video processing, object detection, object tracking, bounding boxes, confidence thresholds and real-time inference.

Frameworks: PyTorch, Ultralytics and YOLO. Experience with RT-DETR would be particularly relevant for this position.

Deployment: TensorRT, Docker, Linux, GPU optimization and edge computing.

Video Analytics: RTSP streams, IP cameras, CCTV pipelines, frame processing, FPS optimization and handling multiple video streams.

Cloud/API: AWS fundamentals and REST API integration.

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🎯 Preparation Tips

Don’t prepare only theoretical Machine Learning questions. Build your preparation around a real-time video analytics pipeline.

For example, be ready to explain:

IP Camera → RTSP Stream → OpenCV → YOLO/RT-DETR → Object Tracking → Event Detection → REST API → Docker/AWS

Expect questions such as:

🔸 How does YOLO perform object detection?
🔸 What is the difference between detection and tracking?
🔸 How would you improve FPS in a real-time video pipeline?
🔸 CPU vs GPU inference — when would you choose each?
🔸 What does TensorRT optimize?
🔸 How would you process multiple RTSP streams simultaneously?
🔸 How would you reduce latency without significantly reducing accuracy?
🔸 How would you deploy your model using Docker?
🔸 How would you handle a camera disconnecting from an RTSP stream?
🔸 What metrics would you monitor in production?

Also revise precision, recall, F1-score, IoU, mAP, NMS, model quantization, batching and inference latency.

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📝 Resume Tips

Avoid writing only:

“Worked on YOLO and Python.”

Instead, quantify your engineering contribution.

For example:

✅ “Developed a real-time YOLO-based object detection pipeline for CCTV streams using Python, OpenCV and PyTorch.”

✅ “Optimized GPU inference using TensorRT, improving video-processing throughput and reducing inference latency.”

✅ “Containerized Computer Vision inference services using Docker and exposed prediction results through REST APIs.”

If you have worked with RTSP, CCTV, NVIDIA GPUs, TensorRT, AWS, Docker or edge devices, place those keywords prominently in your Skills and Project Experience sections.

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💰 Expected Salary Range

Ignatiuz does not appear to publicly specify a salary range for this particular AI/ML Engineer opening. Available salary data for Ignatiuz shows varying compensation across software roles, so it should not be treated as a direct benchmark for this position.

For an AI/ML Engineer with 2–6 years of experience in Indore, a reasonable market-oriented expectation could be around ₹5–12 LPA, with stronger Computer Vision, GPU optimization and production-AI experience potentially supporting a higher package.

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🎤 Expected Interview Rounds at Ignatiuz

There isn’t a current official interview-round structure published specifically for this Computer Vision position. However, historical candidate reports for Ignatiuz indicate processes involving HR, technical and hiring-manager/team discussions, with some candidates reporting three rounds including a technical round and a combined behavioural/technical discussion.

For this role, candidates should therefore be prepared for:

Round 1 – HR/Recruiter: Experience, availability, location and career discussion.

Round 2 – Technical: Python, Computer Vision, PyTorch, YOLO, OpenCV, ML fundamentals and your projects.

Round 3 – Manager/Team: Architecture, production deployment, problem-solving, real-time video scenarios and project ownership.

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📩 How to Apply

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📩 Apply: careers@ignatiuz.com

👉 Application Link: Click Here

Interested candidates can share their profile at careers@ignatiuz.com. You can also monitor the company’s official careers page for relevant openings. Ignatiuz states that its recruitment process does not require candidates to pay fees, so be cautious of anyone requesting money for a job offer.

Subject: Application – AI/ML Engineer – Computer Vision – Indore

🚀 If you have Python + PyTorch + YOLO + OpenCV + real-time video analytics experience and want to work on production-grade AI systems, this is an opportunity worth exploring.

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