Machine Learning / Computer Vision Engineer (Contractor)

Note:

This is a full-time contractor role, and we require that they do not take up any other employment while working with us.

Role Overview We are seeking a highly skilled and motivated

Machine Learning/Computer Vision Engineer

to join our AI team. The core focus of this role will be the end-to-end development and deployment of deep learning models for advanced visual understanding. This includes a strong emphasis on Computer Vision tasks such as

Object Detection, Semantic Segmentation, and Instance Segmentation . You will be responsible for translating cutting-edge research into robust, scalable, production-grade systems in a Python-centric environment.

Key Responsibilities ●

Model Design and Development:

Research, design, implement, and optimize state-of-the-art deep learning models specifically for computer vision segmentation and object detection algorithms. ●

ML Lifecycle Management:

Own the full machine learning lifecycle, from data collection and annotation to training, evaluation, validation, and production deployment. ●

Coding & Integration:

Write clean, efficient, and well-documented production code in

Python , utilizing key ML/CV libraries and frameworks. ●

System Integration:

Collaborate with software and platform engineers to seamlessly integrate computer vision capabilities into our core products and infrastructure. ●

Performance Optimization:

Evaluate model performance, benchmark speed and accuracy, and optimize models for inference latency and memory consumption on target hardware (cloud or edge). ●

Research & Innovation:

Stay abreast of the latest academic and industry advancements in deep learning and computer vision to propose and implement innovative solutions. ●

Collaboration:

Work closely with data scientists, software developers, and product managers to define requirements and deliver high-impact features.

Required Qualifications ●

Experience:

A minimum of

3+ years

of professional experience in a Machine Learning Engineer, Computer Vision Engineer, or similar role. ●

Programming:

Strong proficiency in

Python

and its scientific computing stack (e.g., NumPy, Pandas). ●

Computer Vision:

Proven practical experience with computer vision algorithms and deep learning techniques for

Object Detection

(e.g., YOLO, Faster R-CNN) and

Segmentation

(Semantic or Instance). ●

Deep Learning Frameworks:

Expertise in at least one major deep learning framework ( PyTorch

or

TensorFlow/Keras ). ●

Tooling:

Hands-on experience with computer vision libraries such as

OpenCV . ●

Foundational Knowledge:

Solid understanding of machine learning principles, neural network architectures (especially CNNs), and image processing fundamentals. ●

Education:

Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related technical/quantitative field. ● Proficiency in modern code management tools, especially Git.

Preferred Qualifications (Nice-to-Haves) ● Experience with

MLOps

practices and tools (e.g., Docker, Kubernetes, experiment tracking, model serving). ● Familiarity with cloud computing services (AWS, Google Cloud Platform, or Azure) for model training and deployment. ● Experience in optimizing models for performance and size (e.g., quantization, pruning, use of TensorRT/ONNX).