Computer Vision Engineer

Sakar Robotics

Pune District

On-site

INR 900,000 - 1,500,000

Full time

14 days+

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Benefits offered by this job

Competitive compensation including ESOP
Professional development opportunities
Collaborative work environment

Job summary

A leading robotics firm in Pune is looking for a Computer Vision Engineer to develop and deploy advanced vision systems for automated quality control and inspection across various industries. Candidates should have 3-7 years of experience in computer vision development and be proficient in OpenCV and Python. This full-time position offers the chance to work on cutting-edge technology and includes opportunities for professional development and collaborative work in a dynamic environment.

Qualifications

  • 3-7 years of hands-on experience in computer vision development.
  • Proven track record of deploying computer vision systems in production.
  • Experience with visual inspection and defect detection.

Responsibilities

  • Design and implement computer vision pipelines for inspection.
  • Develop algorithms for defect detection and quality assessment.
  • Integrate vision systems with robotic motion planning.

Skills

OpenCV
Deep learning with PyTorch
C++
Image processing techniques
Robot Operating System (ROS)

Education

Bachelor’s or Master’s degree in Computer Science, Electronics Engineering, Robotics

Tools

NVIDIA Jetson
Intel NUC

Job description

JD – Computer Vision Engineer

Location: Pune

Experience: 2-5 years

Employment Type: Full-time

About the Company

We founded Sakar Robotics to collapse fragmented point solutions into a single extensible mobile manipulation platform. Traditional automation requires bespoke integration per workflow—slow to deploy, rigid to evolve. We built a composable stack where perception, autonomy, manipulation and orchestration cooperate natively. Guided by field feedback across regulated, high‑mix and throughput‑critical domains, we iterate on production reality—not lab abstractions—building durable leverage for customers. Our mission is to deliver a unified robotics platform that can be rapidly configured to execute diverse workflows—reducing time‑to‑value, elevating safety, and embedding continuous improvement loops into daily operations.

Role Summary

We’re seeking an experienced Computer Vision Engineer to design, develop, and deploy robust vision systems for automated visual inspection integrated with our mobile manipulator robots. This role is critical to delivering quality inspection solutions across manufacturing, warehousing, and industrial environments.

Build production‑grade computer vision stack for visual inspection applications that seamlessly integrates with our robotic platforms to enable automated quality control, defect detection, dimensional verification, and compliance inspection across diverse industrial use cases.

Key Responsibilities
  • Vision System Architecture & Development
    • Design and implement end‑to‑end computer vision pipelines for industrial inspection applications
    • Develop robust algorithms for defect detection, classification, measurement, and quality assessment
    • Build vision systems for various inspection scenarios: surface defects, dimensional accuracy, assembly verification, component identification, OCR/text recognition, anomaly detection
    • Optimize vision algorithms for real‑time performance on edge devices and embedded platforms
    • Integrate vision systems with robotic motion planning and control for coordinated inspection workflows
    • Develop calibration procedures for cameras and vision sensors in robotic systems
    • Build data pipelines for image acquisition, preprocessing, augmentation, and annotation
  • Deep Learning & Model Development
    • Design, train, and deploy deep learning models for classification, object detection, segmentation, and anomaly detection
    • Implement classical computer vision techniques where appropriate (edge detection, feature extraction, template matching, morphological operations)
    • Develop custom models tailored to specific industrial inspection requirements
    • Create synthetic data generation pipelines to augment training datasets
    • Perform model optimization, quantization, and compression for deployment on edge devices
    • Implement active learning and continuous improvement frameworks
    • Benchmark and evaluate model performance across accuracy, speed, and robustness metrics
  • System Integration & Deployment
    • Integrate vision systems with ROS‑based robotic platforms
    • Work with hardware team to specify and select appropriate cameras, lighting, and sensors
    • Develop APIs and interfaces for vision system integration with broader automation stack
    • Deploy models on edge computing platforms (NVIDIA Jetson, Intel NUC, or custom hardware)
    • Implement robust error handling, fault tolerance, and system monitoring
    • Create configuration management systems for different inspection scenarios
    • Ensure vision systems meet industrial reliability and uptime requirements
  • Testing, Validation & Documentation
    • Develop comprehensive testing frameworks for vision system validation
    • Conduct field testing and performance validation at customer sites
    • Create technical documentation including system architecture, API documentation, and user guides
    • Collaborate with quality assurance team to establish inspection accuracy benchmarks
    • Support customer pilots and proof‑of‑concept deployments
    • Provide technical training to field engineers and customers
Must‑Have Skills
  • Computer Vision & Image Processing
    • Strong proficiency in OpenCV, PIL/Pillow, scikit‑image
    • Expertise in classical CV techniques: feature extraction, image segmentation, object detection, geometric transformations
    • Experience with 3D vision, stereo vision, or depth sensing (structured light, time‑of‑flight)
    • Knowledge of camera calibration, lens distortion correction, and geometric vision
  • Deep Learning & ML
    • Hands‑on experience with PyTorch or TensorFlow
    • Proficiency in CNNs, object detection (YOLO, R‑CNN family, SSD), semantic segmentation (U‑Net, DeepLab)
    • Experience with vision transformers (ViT, DINO, SAM) is a plus
    • Knowledge of anomaly detection and one‑shot/few‑shot learning techniques
    • Familiarity with MLOps tools and model versioning
  • Programming & Development
    • Expert‑level Python programming
    • Strong understanding of C++ for performance‑critical components
    • Experience with ROS (Robot Operating System) or ROS2
    • Proficiency with Git, Docker, and CI/CD pipelines
    • Knowledge of multi‑threading, parallel processing, and optimization techniques
  • Deployment & Edge Computing
    • Experience deploying models on NVIDIA Jetson, Intel RealSense, or similar edge platforms
    • Knowledge of model optimization frameworks (TensorRT, ONNX, OpenVINO)
    • Understanding of embedded Linux systems
    • Experience with GPU programming (CUDA) is a plus
Good‑to‑Have Skills
  • Experience with industrial cameras (Basler, FLIR, Allied Vision) and machine vision standards (GigE Vision, GenICam)
  • Knowledge of industrial lighting techniques and illumination design
  • Familiarity with 3D reconstruction and point cloud processing (PCL, Open3D)
  • Experience with synthetic data generation tools (Unity, Unreal Engine, Blender)
  • Understanding of industrial communication protocols (Modbus, OPC‑UA, MQTT)
Soft Skills
  • Technical Problem Solving
    • Strong analytical and debugging skills for complex vision system issues
    • Ability to balance theoretical knowledge with practical engineering constraints
    • Creative problem‑solving for challenging inspection scenarios
    • Systematic approach to performance optimization
  • System Thinking
    • Understanding of full‑stack development from sensor to application layer
    • Ability to design scalable and maintainable vision architectures
    • Awareness of hardware‑software trade‑offs in vision system design
  • Collaboration & Communication
    • Excellent collaboration skills to work with robotics, mechanical, and software teams
    • Ability to translate customer requirements into technical specifications
    • Clear documentation and knowledge sharing practices
    • Comfortable presenting technical concepts to non‑technical stakeholders
  • Adaptability & Learning
    • Quick learner who can adapt to new domains and inspection requirements
    • Stay updated with latest research and industry trends in computer vision
    • Willingness to work across the full stack from research to deployment
    • Comfortable with startup pace and evolving requirements
Required Qualifications
  • Education
    • Bachelor’s or Master’s degree in Computer Science, Electronics Engineering, Robotics, or related field
    • Strong academic background in computer vision, image processing, or machine learning
  • Experience
    • 3‑7 years of hands‑on experience in computer vision development with at least 2 years focused on industrial or manufacturing applications
    • Proven track record of deploying computer vision systems in production environments
    • Experience with visual inspection, quality control, or defect detection systems
    • Background in robotics integration or working with robotic systems is highly desirable
    • Experience with edge deployment and embedded vision systems
What We Offer
  • Opportunity to build cutting‑edge vision systems for real‑world industrial applications
  • Work on diverse and challenging computer vision problems across multiple industries
  • Collaborate with experienced robotics and automation engineers
  • Access to state‑of‑the‑art hardware and computing resources
  • Competitive compensation package including ESOP
  • Professional development opportunities including conferences and training
  • Collaborative work environment with focus on outcomes
  • Direct impact on product development and customer success
Work Environment
  • Office‑based role in Pune
  • Hands‑on work with robotics hardware and vision systems
  • Occasional travel (20‑25%) for customer site deployments and field testing
  • Collaborative team environment with regular technical discussions and knowledge sharing
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