Senior Computer Vision Engineer

Polybee; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A leading tech firm in Singapore seeks an experienced professional to build and productionize deep-learning models for analyzing fruits and vegetables using drone imagery. This role involves optimizing pipelines for cloud and embedded systems, managing the MLOps lifecycle, and mentoring junior engineers. The candidate should have strong programming skills in Python and C++, with extensive experience in robotics and computer vision solutions. This opportunity is pivotal in contributing to innovative algorithms and solutions in agricultural technology.

Qualifications

• 4+ years of experience in robotics, computer vision, or deep learning solutions.
• Strong programming skills in Python and C++, especially in computer vision libraries.
• Hands-on experience maintaining ML pipelines and containerized deployments.

Responsibilities

• Build and productionize deep-learning models using drone imagery.
• Optimize inference pipelines for cloud and edge hardware.
• Design and manage the full MLOps lifecycle from data validation to deployment.

Skills

Deep learning

Computer Vision

Robotics

Python

C++

MLOps

Data model versioning

Tools

TensorRT

ONNX Runtime

Docker

Kubernetes

Grafana

Prometheus

Job description

Responsibilities:

• You will build and productionize deep-learning models that detect, segment, and extract actionable insights from fruits and vegetables using imagery captured by off-the-shelf drones, achieving industry-leading accuracy on key KPIs.
• You will own the end-to-end data and model pipeline from raw image ingestion and data pipelines through training, validation, deployment, and automated retraining ensuring client requests.
• You will optimize inference pipelines for both cloud and embedded edge hardware using runtimes such as TensorRT, ONNX Runtime, or equivalent, meeting latency targets and resource budgets.
• You will implement monitoring, drift detection, and automated feedback loops so that any degradation in model performance is identified and corrected.
• You will establish and enforce a quality-first code culture: unit/integration tests, code reviews, and CI/CD (e. g. GitHub Actions or equivalent), so that 100% of changes roll out with automated validation and zero manual steps.
• You will partner with robotics engineers to refine drone flight patterns, camera settings, and preprocessing workflows, improving input raw data completeness, quality, latency, and cost.
• You will mentor and support junior CV engineers, gradually taking ownership of their technical development and contributing to team growth through hiring and training.
• You will collaborate closely with operations teams and key customers to ensure field-deployed solutions achieve promised results, incorporating direct feedback from initial deployments into roadmap decisions.
• You will design and manage the full MLOps lifecycle, from data validation and model versioning to CI/CD pipelines for models, shadow deployments, and rollback mechanisms.
• You will contribute to the creation of intellectual property and defensible innovation through novel algorithms, research publications, or patents that position Polybee as a category leader.

Requirements:

• 4+ years building and shipping robotics, computer vision, or deep learning solutions in production, with demonstrable impact on business metrics (accuracy, latency, cost).
• Strong programming skills in Python and C++, with experience in computer vision/ML libraries (e. g., OpenCV, scikit-learn, pandas) and deep learning frameworks (e. g., PyTorch, TensorFlow or equivalent).
• Hands-on involvement in designing and maintaining ML pipelines with data/model versioning (e. g., MLflow, DVC, Prefect or equivalent) and containerized deployments (Docker, Kubernetes or equivalent).
• Technical expertise in 3D reconstruction, stereovision, photogrammetry, or structure-from-motion methods.
• Proven ability to define, track, and present KPIs via dashboards (Grafana, Prometheus, or equivalent) and close feedback loops to sustain model performance.
• Excellent communication skills, capable of translating complex technical concepts for non-experts and mentoring junior engineers.
• Ability to work directly with operations and customers to deploy and refine AI-powered systems in real-world field conditions.
• Experience creating, whether in the form of patent filings, conference papers, or proprietary research will be highly valued.