Senior Staff Data Scientist for Robotics and Vision Systems-Remote within the US

Joinus in pioneering breakthroughs in healthcare. For everyone. Everywhere.Sustainably.

Our inspiring and caring environment forms a globalcommunity that celebrates diversity and individuality. We encourage you to stepbeyond your comfort zone, offering resources and flexibility to foster yourprofessional and personal growth, all while valuing your unique contributions.

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

The ideal candidate is a computer visionspecialist with general ML knowledge covering entire spectrum of the appliedML/AI workflow including object detection, image analysis, big data handling,MLOps, advanced ML concepts and frameworks (including unstructured data andmultimodal ML), distributed deep learning training, and ML explainability. Thefocus 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 tosolve robotic problems.
• DevelopingAI models and classical computer vision workflows on images of differentquality including noisy and low-quality images
• Independentlyand rapidly develop and test functioning prototypes for feasibilitydemonstration in a healthcare environment, validate and communicate results toanswer business-relevant questions.
• Developingreusable analytic models, configure and deploy algorithms, select optimaltools, and define visualization methods/tools to present results.
• Contributingto developing organizational best practices in computer vision, machinelearning, and data engineering.

Your expertise:

• Master's or PHD degree in mathematics, statistics, computerscience, physics, electrical engineering, or engineering sciences.
• Strongtechnical expertise in technologies, algorithms, and methodologies in the areasof object detection and image analysis, deep neural networks architectures forobject detection, time-series analysis, feature engineering, dimensionalityreduction, etc.
• High levelof expertise in applied ML frameworks such as PyTorch, TensorFlow,Scikit-learn, etc.
• Substantialexpertise in traditional computer vision and image analysis, for instance,utilizing OpenCV.
• Understandingof vision systems and setups, image formation, intrinsic and extrinsicparameters and calibration, and their distortions and noise factors
• Proficientprogramming abilities in Python and C++, with hand-on experience with codecompletion assistants
• Extensiveknowledge of using and extending analytical tools and platforms such asDatabricks, Spark, and analogous data analytics environments.
• Proficiency in the current landscape of largevision-language models: understanding of state-of-the-artvision-language models like GPT4-V, CLIP, DALL-E, and Llava-1.6, includingtheir architectures (autoregressive and stable diffusion), strengths, andlimitations.
• Expertise in collecting, curating, and preprocessingdiverse datasets that combine visual and textual information, ensuringhigh-quality and balanced data for training.
• Skills in training large-scale vision-languagemodels from scratch and fine-tuning pre-trained models to adapt them forspecific applications, including hyperparameter tuning and model optimization.
• Skills in leveraging few-shot learning techniques andcontext learning strategies to enable models to generalize from a small numberof examples and understand contextually relevant information, improvingperformance on tasks with limited data.
• Experiencewith NVIDIA Omniverse environment is preferred but not required.
• Expertise inrobotic applications and ROS is preferred.
• Expertise inbig data analytics and analytics with structured and unstructured data.
• Ability toapply analytical rigor and statistical methods to optimize our products.
• Understanding of concepts in medical statistics
• Comfortablewith creation and analysis of complex models to support effective decisionmaking.
• Understandingof ML model explainability and ML risk assessment concepts
• Broadunderstanding of ML life cycle management/MLOps.
• Practicalskills in distributed GPU ML training and inference.
• Strongpresentation and communication skills to present technical andbusiness-relevant insights at different levels of the organization.
• Medicalapplications experience is preferred but not required.

Who we are:

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

How we work:

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

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

This informationis provided per the required state Equal Pay Act. Base pay information is basedon market location. Applicants should apply via Siemens Healthineers externalor internal careers site.

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