AI / ML Engineer

Mostedge; Ahmedabad District, Vadodara; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Mostedge is seeking an AI/ML Engineer specialized in Computer Vision for building video analytics solutions for smart surveillance. You will train and deploy models for face detection, object tracking, and activity analysis, with real-time inference on edge devices like Jetson and Coral.

The role emphasizes model optimization, API deployment with FastAPI or Flask, containerization with Docker, and scalable orchestration with Kubernetes, along with MLOps practices.

Qualifications

• Bachelor's or master's in CS/AI/Data Science or related field.
• 3–6 years of AI/ML experience with a focus on computer vision.
• Strong portfolio demonstrating CV projects and real-time inference.

Responsibilities

• Develop and optimize AI/ML models for video analytics.
• Implement face detection/recognition, object tracking, and activity analysis.
• Integrate models with CCTV/RTSP streams for real-time analytics.
• Deploy and monitor models on cloud and edge devices with CI/CD pipelines.

Skills

AI/ML development

Computer vision

Edge deployment

Python programming

Team collaboration

Education

Bachelor's or Master's in CS/AI/Data Science

Tools

PyTorch

TensorFlow

OpenCV

YOLOv8

DeepSORT

RetinaNet

FastAPI

Flask

TorchServe

Docker

Kubernetes

ONNX

TensorRT

OpenVINO

MLflow

DVC

Job description

AI/ML Engineer (2-3 positions)

Job Summary:
We are seeking a highly skilled and motivated AI/ML Engineer with a specialization in Computer Vision & Un-Supervised Learning to join our growing team. You will be responsible for building, optimizing, and deploying advanced video analytics solutions for smart surveillance applications, including real-time detection, facial recognition, and activity analysis.
This role combines the core competencies of AI/ML modelling with the practical skills required to deploy and scale models in real-world production environments, both in the cloud and on edge devices.

Key Responsibilities:

• AI/ML Development & Computer Vision
  • Design, train, and evaluate models for:
  • Face detection and recognition
  • Object/person detection and tracking
  • Intrusion and anomaly detection
  • Human activity or pose recognition/estimation
• Work with models such as YOLOv8, DeepSORT, RetinaNet, Faster-RCNN, and InsightFace.
• Perform data preprocessing, augmentation, and annotation using tools like LabelImg, CVAT, or custom pipelines.
• Surveillance System Integration
  • Integrate computer vision models with live CCTV/RTSP streams for real-time analytics.
  • Develop components for motion detection, zone-based event alerts, person re-identification, and multi-camera coordination.
  • Optimize solutions for low-latency inference on edge devices (Jetson Nano, Xavier, Intel Movidius, Coral TPU).
• Model Optimization & Deployment
  • Convert and optimize trained models using ONNX, TensorRT, or OpenVINO for real-time inference.
  • Build and deploy APIs using FastAPI, Flask, or TorchServe.
  • Package applications using Docker and orchestrate deployments with Kubernetes.
  • Automate model deployment workflows using CI/CD pipelines (GitHub Actions, Jenkins).
  • Monitor model performance in production using Prometheus, Grafana, and log management tools.
  • Manage model versioning, rollback strategies, and experiment tracking using MLflow or DVC.
• As an AI/ML Engineer, you should be well-versed of AI agent development and finetuning experience.
• Collaboration & Documentation
  • Work closely with backend developers, hardware engineers, and DevOps teams.
  • Maintain clear documentation of ML pipelines, training results, and deployment practices.
  • Stay current with emerging research and innovations in AI vision and MLOps.

Required Qualifications:

• Bachelors or masters degree in computer science, Artificial Intelligence, Data Science, or a related field.
• 3-6 years of experience in AI/ML, with a strong portfolio in computer vision, Machine Learning.

Hands-on experience with:

• Deep learning frameworks: PyTorch, TensorFlow
• Image/video processing: OpenCV, NumPy
• Detection and tracking frameworks: YOLOv8, DeepSORT, RetinaNet.
• Solid understanding of deep learning architectures (CNNs, Transformers, Siamese Networks).
• Proven experience with real-time model deployment on cloud or edge environments.
• Strong Python programming skills and familiarity with Git, REST APIs, and DevOps tools.

Preferred Qualifications:

• Experience with multi-camera synchronization and NVR/DVR systems.
• Familiarity with ONVIF protocols and camera SDKs.
• Experience deploying AI models on Jetson Nano/Xavier, Intel NCS2, or Coral Edge TPU.
• Background in face recognition systems (e.g., InsightFace, FaceNet, Dlib).
• Understanding of security protocols and compliance in surveillance systems.

Tools & Technologies:

• Category Tools & Frameworks
• Languages & AI: Python, PyTorch, TensorFlow, OpenCV, NumPy, Scikit-learn
• Model Serving: FastAPI, Flask, TorchServe, TensorFlow Serving, REST/gRPC APIs
• Model Optimization: ONNX, TensorRT, OpenVINO, Pruning, Quantization
• Deployment: Docker, Kubernetes, Gunicorn, MLflow, DVC
• CI/CD & DevOps: GitHub Actions, Jenkins, GitLab CI
• Cloud & Edge: AWS SageMaker, Azure ML, GCP AI Platform, Jetson, Movidius, Coral TPU
• Monitoring: Prometheus, Grafana, ELK Stack, Sentry
• Annotation Tools: LabelImg, CVAT, Supervisely