AI Model Developer - Computer Vision

JobItUs; Rajkot; On-site; INR 700,000 - 1,200,000; Full time

Benefits offered by this job

20 GB GPU server access for experimentation and training

Lead your own annotation team

Exposure to multimodal, real-world AI problems

Room for innovation and career growth

Job summary

JobItUs is seeking an AI Model Developer to create and optimize computer vision models for real-time analytics. This role involves hands-on development, model training, and managing annotations.

Ensure quality in model deployment and lead a small annotation team while experimenting with cutting-edge AI techniques to solve complex vision problems.

Exciting opportunities for career growth and innovation await in a fast-paced environment.

Qualifications

• Strong experience with PyTorch or TensorFlow for model development.
• Hands-on experience in computer vision tasks such as detection, segmentation, or classification.
• Proficiency in hyperparameter tuning and training large-scale models.

Responsibilities

• Develop deep learning models for camera images and optimize for generalization.
• Conduct hyperparameter tuning to balance accuracy, robustness, and speed.
• Train and evaluate models on curated datasets and analyze performance.

Skills

Strong experience with PyTorch or TensorFlow

Hands-on experience in computer vision tasks

Proficiency in hyperparameter tuning

Excellent teamwork and communication skills

Education

Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field

Tools

Roboflow

CVAT

MLflow

DVC

Kubeflow

Job description

This role blends hands-on data labelling, model experimentation, and performance tuning to ensure the platform delivers robust and real-time vision analytics.

We are looking for an AI Model Developer who will build generalized computer vision models for camera imagery. You will play a key role in developing, fine-tuning, and optimizing models that can generalize across diverse camera feeds and environments. The role requires strong ownership of the full AI lifecycle — from data annotation planning to model deployment — and a passion for experimenting with different strategies to push model performance boundaries.

Key Responsiblities

• Model Development: Develop and optimize deep learning models for camera images, focusing on generalization across varied domains.
• Hyperparameter Tuning: Conduct systematic experiments with model architectures and hyperparameters to achieve the best trade-off between accuracy, robustness, and speed.
• Annotation Management:
  • Plan weekly annotation activities and strategies for the annotation team.
  • Review and approve annotations to ensure quality and consistency.
  • Design new labeling strategies to improve model understanding of complex scenarios.
• Model Training & Evaluation:
  • Train and evaluate models on curated datasets.
  • Compare new model performance against previous baselines to identify improvement trends.
  • Analyze model failure cases and design corrective actions.
• Automation & MLOps:
  • Develop and maintain data/model pipelines to automate repetitive or manual workflows.
  • Implement experiment tracking, versioning, and automated training/evaluation loops.
• Experimentation & Research:
  • Explore new architectures, augmentation techniques, and annotation strategies.
  • Stay updated on recent trends in multimodal AI and apply them to complex surveillance use cases.

Requirements :

• Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field.
• Strong experience with PyTorch or TensorFlow for model development.
• Hands-on experience in computer vision tasks such as detection, segmentation, or classification.
• Proficiency in hyperparameter tuning and training large-scale models.
• Familiarity with data annotation tools like Roboflow or CVAT and managing annotation quality.
• Experience in building ML pipelines and MLOps workflows (e.g., MLflow, DVC, Kubeflow).
• Analytical mindset for model evaluation and performance benchmarking.
• Excellent teamwork and communication skills.

Good-to-Haves

• Experience with multi-camera or multimodal data (e.g., image + metadata).
• Familiarity with Edge AI or real-time video inference.
• Knowledge of data versioning, model drift detection, or continuous learning.
• Prior experience managing or coordinating a small annotation team.

What we Offer

• 20 GB GPU server access for experimentation and training.
• Lead and coordinate your own annotation team.
• Work directly with the Co-founder and Senior Developer on high-impact projects.
• Exposure to multimodal, real-world AI problems that go beyond typical datasets.
• Fast-paced environment with room for innovation, autonomy, and career growth.