We are seeking a motivated
Machine Learning Engineer
with
1–2 years of professional experience
in image processing and convolutional neural networks (CNNs). This role is ideal for someone who is passionate about computer vision and excited to build and deploy models that solve challenging real-world problems. You will work closely with a cross-functional team of engineers and researchers to design, train, and operationalize state-of-the-art deep learning solutions.What You’ll DoAs part of our machine learning team, you will contribute to the full lifecycle of computer vision model development:
- Model Development – Design, build, and train convolutional neural network (CNN) models for image-related tasks such as classification, segmentation, and object detection.
- Data Handling – Work with large and complex image datasets, ensuring proper preprocessing, annotation handling, and applying data augmentation techniques to maximize model performance.
- Transfer Learning & Optimization – Leverage pre-trained models and fine-tune them for domain-specific tasks, experimenting with different architectures and hyperparameters to optimize accuracy and efficiency.
- Evaluation & Validation – Define and implement metrics to assess model performance, perform error analysis, and iterate to improve generalization and robustness.
- Deployment & Integration – Collaborate with software engineers to package models and integrate them into production systems. This includes optimizing inference performance, testing scalability, and ensuring reliability in real-world applications.
- Research & Innovation – Stay up to date with the latest trends in computer vision and deep learning, particularly advancements in CNNs, transfer learning, and emerging architectures such as vision transformers.
- Cloud ML Services – Experience deploying models on platforms such as AWS SageMaker, Google Cloud AI, or Azure ML.
What You Bring
Skills
We are looking for someone with a balance of technical skills, problem-solving ability, and eagerness to learn. The ideal candidate has:
- 1–2 years of hands-on experience developing machine learning models in Python using PyTorch or TensorFlow.
- A strong understanding of CNNs, image preprocessing, data augmentation, and model evaluation techniques.
- Experience working with large-scale image datasets and familiarity with common challenges such as class imbalance and noisy data.
- A practical mindset, with the ability to move from research and prototyping to building models ready for deployment.
- Exposure to containerization tools (Docker) and version control (Git), with the ability to collaborate effectively in a team environment.
Bonus Points
While not required, experience in the following areas will make you stand out:
- Medical Imaging – Familiarity with DICOM formats, image registration, and working with healthcare datasets.
- Cloud ML Services – Experience deploying models on platforms such as AWS SageMaker, Google Cloud AI, or Azure ML.
- Advanced Architectures – Exposure to vision transformers (ViTs) or hybrid CNN-transformer approaches for next-generation vision applications.
- Get the requirements and devlop the functionality and deliver robust and clean code.
Why Join Us?This is an exciting opportunity to apply your skills in machine learning and computer vision to create impactful solutions. You’ll work in an environment that values
innovation, collaboration, and continuous learning
, with the chance to grow alongside a team of experienced engineers and data scientists.If you are driven by solving real-world challenges with AI and eager to sharpen your expertise in deep learning, we’d love to hear from you.Skills: computer vision,machine learning,datasets,python
