AI Model Developer - Computer Vision

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 Responsibilities

• 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.