This role is for one of Weekday's clients
Salary range: Rs ******* - Rs ******* (ie INR ***** LPA)
Min Experience: 5 years
Location: Bengaluru
JobType: full-time
We are seeking a highly skilled and experienced
Computer Vision Engineer
to join our growing AI team. This role is ideal for someone with strong expertise in deep learning and a solid background in real-time video analytics, model deployment, and computer vision applications. You'll be responsible for developing scalable computer vision pipelines and deploying them across cloud and edge environments, helping build intelligent visual systems that solve real-world problems.
Key Responsibilities:
Model Development & Training:
Design, train, and optimize deep learning models for object detection, segmentation, and tracking using frameworks like
YOLO
,
UNet
,
Mask R-CNN
, and
Deep SORT
.
Computer Vision Applications:
Build robust pipelines for computer vision applications including image classification, real-time object tracking, and video analytics using
OpenCV
,
NumPy
, and
TensorFlow/PyTorch
.
Deployment & Optimization:
Deploy trained models on Linux-based
GPU systems
and
edge devices
(e.g.,
Jetson Nano
,
Google Coral
), ensuring low-latency performance and efficient hardware utilization.
Real-Time Inference:
Implement and optimize real-time inference systems, ensuring minimal delay in video processing pipelines.
Model Management:
Utilize tools like
Docker
,
Git
, and
MLflow
(or similar) for version control, environment management, and model lifecycle tracking.
Collaboration & Documentation:




Work cross-functionally with hardware, backend, and software teams. Document designs, architectures, and research findings to ensure reproducibility and scalability.
Technical Expertise Required:
Languages & Libraries:
Advanced proficiency in
Python
and solid experience with
OpenCV
,
NumPy
, and other image processing libraries.
Deep Learning Frameworks:
Hands-on experience with
TensorFlow
,
PyTorch
, and integration with model training pipelines.
Computer Vision Models:
Object Detection:
YOLO (all versions)
Segmentation:
UNet, Mask R-CNN
Tracking:
Deep SORT or similar
Deployment Skills:
Real-time video analytics implementation and optimization
Experience with
Docker
for containerization
Version control using
Git
Model tracking using
MLflow
or comparable tools
Platform Experience:
Proven experience in deploying models on
Linux-based GPU environments
and
edge devices
(e.g., NVIDIA Jetson family, Coral TPU).
Professional & Educational Requirements:
Education:
B.E./B.Tech/M.Tech in Computer Science, Electrical Engineering, or related discipline.
Experience:
Minimum
5 years
of industry experience in
AI/ML
with a robust focus on
computer vision
and
system-level design
.
Proven portfolio of production-level projects in image/video processing or real-time systems.
Preferred Qualities:
Strong problem-solving and debugging skills
Excellent communication and teamwork capabilities
A passion for building smart, scalable vision systems
A proactive and independent approach to research and implementation

📌 Computer Vision Engineer (Bengaluru)
🏢 Weekday AI
📍 Bengaluru