Required Algorithm Developer
The Role:
As an Algorithm Developer, you will be part of the AI team that develops AI-based products and maintains them in production at scale (1700+ hospitals).
As part of the Al team you will:
Design, develop, and implement robust, scalable AI algorithms tailored to real-world challenges in clinical settings.
Prepare, process, and analyze complex medical data to support algorithm development and validation.
Ensure the reliability, performance, and accuracy of algorithms in production, including troubleshooting, testing, monitoring, and continuous improvement.
Collaborate closely with Product Managers and Clinical Specialists to translate clinical and business needs into data-driven solutions.
Research, develop and integrate cutting-edge deep learning techniques and classical computer vision and medical imaging methodologies.
Apply NLP and large language models (LLMs) to extract insights from unstructured medical texts and develop intelligent agents for optimized clinical decision support
Stay up to date with cutting-edge advancements in Deep Learning, Computer Vision, and Large Language Models. Organize and actively participate in seminars, book clubs, and conferences.
Have an opportunity to co-author papers and abstracts for leading medical journals and scientific conferences.
Main technical stack:
Infrastructure: AWS, Docker, Kubernetes
Programming Languages: Python
Data processing: Pandas, Polars, Amazon Athena, Postgress Sql, Opensearch
Deep Learning Frameworks: TensorFlow, Keras, Pytorch
Computer Vision Libraries: OpenCV, MONAI
NLP/LLMs: Hugging Face Transformers, spaCy, Amazon Bedrock
Our Core Values:
Patients First; Time is Brain; Quality Squared; Kindness Wins; I am Accountable.
The Role:
As an Algorithm Developer, you will be part of the AI team that develops AI-based products and maintains them in production at scale (1700+ hospitals).
As part of the Al team you will:
Design, develop, and implement robust, scalable AI algorithms tailored to real-world challenges in clinical settings.
Prepare, process, and analyze complex medical data to support algorithm development and validation.
Ensure the reliability, performance, and accuracy of algorithms in production, including troubleshooting, testing, monitoring, and continuous improvement.
Collaborate closely with Product Managers and Clinical Specialists to translate clinical and business needs into data-driven solutions.
Research, develop and integrate cutting-edge deep learning techniques and classical computer vision and medical imaging methodologies.
Apply NLP and large language models (LLMs) to extract insights from unstructured medical texts and develop intelligent agents for optimized clinical decision support
Stay up to date with cutting-edge advancements in Deep Learning, Computer Vision, and Large Language Models. Organize and actively participate in seminars, book clubs, and conferences.
Have an opportunity to co-author papers and abstracts for leading medical journals and scientific conferences.
Main technical stack:
Infrastructure: AWS, Docker, Kubernetes
Programming Languages: Python
Data processing: Pandas, Polars, Amazon Athena, Postgress Sql, Opensearch
Deep Learning Frameworks: TensorFlow, Keras, Pytorch
Computer Vision Libraries: OpenCV, MONAI
NLP/LLMs: Hugging Face Transformers, spaCy, Amazon Bedrock
Our Core Values:
Patients First; Time is Brain; Quality Squared; Kindness Wins; I am Accountable.
Requirements:
Required Qualifications:
Minimum of 3 years of hands-on experience in algorithm development using Python, with a strong foundation in software engineering principles and clean, efficient coding practices.
Experience in deep learning with a focus on computer vision applications such as image segmentation, object detection, and classification.
Experience in classical computer vision and image processing techniques (i.e. image filtering and enhancement, geometric transformations, image registration, morphological operations)
Hands-on experience with data processing, deep learning and computer vision libraries: PyTorch, TensorFlow, OpenCV, Pandas
Experience in the deployment, delivery, and maintenance of AI algorithms in real-world production environments
Familiarity with NLP and LLMs
Strong interpersonal and communication skills; a team player who can work effectively in a cross-functional environment involving product managers, clinicians, and fellow engineers.
Self-starter with the ability to take ownership of projects and drive them to completion independently.
Preferred Qualifications:
Experience with AWS
Experience with medical imaging technologies and data formats (e.g., DICOM) and familiarity with domain-specific challengesan advantage.
Familiarity with modern MLOps practices and tools for model tracking, deployment, and monitoring (e.g., MLflow, ClearML, Docker, Kubernetes).
M.Sc. or higher in Computer Science, Electrical Engineering, Biomedical Engineering, Applied Mathematics, or a related scientific discipline.
Required Qualifications:
Minimum of 3 years of hands-on experience in algorithm development using Python, with a strong foundation in software engineering principles and clean, efficient coding practices.
Experience in deep learning with a focus on computer vision applications such as image segmentation, object detection, and classification.
Experience in classical computer vision and image processing techniques (i.e. image filtering and enhancement, geometric transformations, image registration, morphological operations)
Hands-on experience with data processing, deep learning and computer vision libraries: PyTorch, TensorFlow, OpenCV, Pandas
Experience in the deployment, delivery, and maintenance of AI algorithms in real-world production environments
Familiarity with NLP and LLMs
Strong interpersonal and communication skills; a team player who can work effectively in a cross-functional environment involving product managers, clinicians, and fellow engineers.
Self-starter with the ability to take ownership of projects and drive them to completion independently.
Preferred Qualifications:
Experience with AWS
Experience with medical imaging technologies and data formats (e.g., DICOM) and familiarity with domain-specific challengesan advantage.
Familiarity with modern MLOps practices and tools for model tracking, deployment, and monitoring (e.g., MLflow, ClearML, Docker, Kubernetes).
M.Sc. or higher in Computer Science, Electrical Engineering, Biomedical Engineering, Applied Mathematics, or a related scientific discipline.
This position is open to all candidates.
