Staff Engineer - Computer Vision and Machine Learning

Who we want

• Detail-oriented process improvers. Critical thinkers who naturally see opportunities to develop and optimize work processes – finding ways to simplify, standardize and automate. 

• Strategic thinkers. People who enjoy analyzing data or trends for the purposes of planning, forecasting, advising, budgeting, reporting, or sales opportunities. 

• Collaborative partners. People who build and leverage cross-functional relationships to bring together ideas, data and insights to drive continuous improvement in functions.

• Analytical problem solvers. People who go beyond just fixing to identify root causes, evaluate optimal solutions, and recommend comprehensive upgrades to prevent future issues. 

• Dedicated achievers. People who thrive in a fast-paced environment and will stop at nothing to ensure a project is complete and meets regulations and expectations. 

What you will do:
Key Responsibilities:

• Develop advance computer vision, medical image processing solutions.

• Work on design and implementation of ML/DL solutions for image segmentation, pattern recognition, object identification.

• Wright high-quality, scalable and maintainable code in C++, C# and Python for state-of-the-art products.

• Work closely with cross-functional teams including data scientists, radiologists, hardware engineers, and other stakeholders to integrate advance features into clinical workflows and products.

• Create and Maintain detailed and clear technical documentation of the developed software components and algorithms, ensuring regulatory compliance and reproducibility.

What You Need:

Minimum Qualifications (Required):

• BTech/MTech in Computer Science, Electronics Engineering or related field with focus on Image Processing, Computer Vision, ML/DL.

• 7-9 years of experience in developing high quality codes using C++, C# and Python. Candidates with experience in api/library development will be preferred.

• At least 5 years of experience developing Computer Vision and ML/DL solutions in image segmentation, object detection, pattern recognition etc.

Preferred Qualifications (Strongly desired):

• Solid coding skill in C++. Experience in OOP, STL, template programming, multithreading, basic design patterns is preferred. Candidate should have excellent debugging and optimization skill.

• Excellent understanding of data structures and algorithms.

• In-depth understanding of the Python software development stacks, ecosystems, frameworks and tools such as Numpy, Scipy, Pandas, sci-kit-learn, Pillow and TensorFlow/PyTorch.

• Candidate should have excellent proficiency in OpenCv.

• In-depth understanding of color-space, histogram, contrast enhancement, spatial and frequency domain filtering, Morphology, connected components analysis, image segmentation, object detection, camera calibration, pattern finding, feature detectors, geometry analysis, multiple view geometry, 3D reconstruction algorithms.

• Excellent understanding of ML algorithms like SVM, Random Forest, regression analysis, Cluster analysis, PCA.

• Experience with DL models like VGG, YOLO, U-Net, ResNet etc.

• Knowledge of medical imaging modalities such as CT, MRI, or ultrasound and familiarity with medical data handling.

• Understanding of medical device regulatory requirements and standards (e.g., FDA, CE marking).

• Strong problem-solving skills and ability to work in collaborative, cross-functional teams.

• Basic understanding of C# will be an added advantage.

• Experience with VTK, ITK and MITK will be an added advantage.

We are looking for highly skilled Staff Engineer with a solid background in Image Processing/Computer Vision and Machine Learning in healthcare domain. This position is suitable for professionals with 7-9 years of experience in the field mentioned above. The ideal candidate will be proficient in C++, Python, OpenCv, TensorFlow/PyTorch. The candidate should have hands-on experience in developing, debugging, optimizing and documenting Computer Vision solutions for healthcare applications.