Senior Staff Data Scientist for Robotics and Vision Systems-Remote within the US
Siemens Healthcare Diagnostics Inc.

Join us in pioneering breakthroughs in healthcare. For everyone. Everywhere. Sustainably.

Our inspiring and caring environment forms a global community that celebrates diversity and individuality. We encourage you to step beyond your comfort zone, offering resources and flexibility to foster your professional and personal growth, all while valuing your unique contributions.

Apply now for the role of Senior Staff Data Scientist at Siemens Healthineers.

The ideal candidate is a computer vision specialist with general ML knowledge covering entire spectrum of the applied ML/AI workflow including object detection, image analysis, big data handling, MLOps, advanced ML concepts and frameworks (including unstructured data and multimodal ML), distributed deep learning training, and ML explainability. The focus of this position is on image analysis, object detection, segmentation, and classification to solve robotic problems.

Your role:

• Developing, training, and testing models for object detection, classification, and segmentation to solve robotic problems.
• Developing AI models and classical computer vision workflows on images of different quality including noisy and low-quality images
• Independently and rapidly develop and test functioning prototypes for feasibility demonstration in a healthcare environment, validate and communicate results to answer business-relevant questions.
• Developing reusable analytic models, configure and deploy algorithms, select optimal tools, and define visualization methods/tools to present results.
• Contributing to developing organizational best practices in computer vision, machine learning, and data engineering.

Your expertise:

• Master's or PHD degree in mathematics, statistics, computer science, physics, electrical engineering, or engineering sciences.
• Strong technical expertise in technologies, algorithms, and methodologies in the areas of object detection and image analysis, deep neural networks architectures for object detection, time-series analysis, feature engineering, dimensionality reduction, etc.
• High level of expertise in applied ML frameworks such as PyTorch, TensorFlow, Scikit-learn, etc.
• Substantial expertise in traditional computer vision and image analysis, for instance, utilizing OpenCV.
• Understanding of vision systems and setups, image formation, intrinsic and extrinsic parameters and calibration, and their distortions and noise factors
• Proficient programming abilities in Python and C++, with hand-on experience with code completion assistants
• Extensive knowledge of using and extending analytical tools and platforms such as Databricks, Spark, and analogous data analytics environments.
• Proficiency in the current landscape of large vision-language models: understanding of state-of-the-art vision-language models like GPT4-V, CLIP, DALL-E, and Llava-1.6, including their architectures (autoregressive and stable diffusion), strengths, and limitations.
• Expertise in collecting, curating, and preprocessing diverse datasets that combine visual and textual information, ensuring high-quality and balanced data for training.
• Skills in training large-scale vision-language models from scratch and fine-tuning pre-trained models to adapt them for specific applications, including hyperparameter tuning and model optimization.
• Skills in leveraging few-shot learning techniques and context learning strategies to enable models to generalize from a small number of examples and understand contextually relevant information, improving performance on tasks with limited data.
• Experience with NVIDIA Omniverse environment is preferred but not required.
• Expertise in robotic applications and ROS is preferred.
• Expertise in big data analytics and analytics with structured and unstructured data.
• Ability to apply analytical rigor and statistical methods to optimize our products.
• Understanding of concepts in medical statistics
• Comfortable with creation and analysis of complex models to support effective decision making.
• Understanding of ML model explainability and ML risk assessment concepts
• Broad understanding of ML life cycle management/MLOps.
• Practical skills in distributed GPU ML training and inference.
• Strong presentation and communication skills to present technical and business-relevant insights at different levels of the organization.
• Medical applications experience is preferred but not required.

Who we are:
We are a team of more than 71,000 highly dedicated Healthineers in more than 70 countries. As a leader in medical technology, we constantly push the boundaries to create better outcomes and experiences for patients, no matter where they live or what health issues they are facing. Our portfolio is crucial for clinical decision-making and treatment pathways.

How we work:
When you join Siemens Healthineers, you become one in a global team of scientists, clinicians, developers, researchers, professionals, and skilled specialists, who believe in each individual's potential to contribute with diverse ideas. We are from different backgrounds, cultures, religions, political and/or sexual orientations, and work together, to fight the world's most threatening diseases and enable access to care, united by one purpose: to pioneer breakthroughs in healthcare. For everyone. Everywhere. Sustainably. Check our Careers Site at Careers - Siemens Healthineers USA (siemens-healthineers.com)

The pay range for this position is $172,000 - $230,000 U.S. dollars annually; however, base pay offered may vary depending on job-related knowledge, skills, and experience, as well as where the work will be performed. The annual incentive target is (15%) of base pay. Siemens Healthineers offers a variety of health and wellness benefits including paid time off and holiday pay. Details regarding our benefits can be found here: https://benefitsatshs.com/index.html

This information is provided per the required state Equal Pay Act. Base pay information is based on market location. Applicants should apply via Siemens Healthineers external or internal careers site.

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