Senior Staff AI Research Scientist for Generative AI (REMOTE)

Key Skills

Aartificial intelligence, Effective communication skills, Generative AI, HuggingFace, Large Language Models - LLMs, NeurIPS, Python Programming, PyTorch, TensorFlow

Job Description

Work Flexibility: Remote

Who We Want:

As a valued member of Stryker’s AI innovation unit, you will work alongside trailblazers, industry visionaries, innovators, and inventors who are committed to bringing computer vision, AI/ML and digital innovation to the operating room and other healthcare settings.

You’ll contribute to fast-paced cycles of innovation and develop core technologies that power a wide array of Stryker’s solutions, including: surgical robotics and navigation, image-guided surgery, treatment selection, outcome assessment, and clinical decision intelligence. You will apply your core skills across a range of deployment platforms spanning from mobile applications, cloud services, and SDKs to embedded systems, edge devices, and mixed reality (XR) platforms. You will have an opportunity to work across a wide variety of therapeutic areas ranging from orthopaedics and neurosurgery to emergency care and operating room safety and efficiency – plus many more.

As a Senior Staff AI Research Scientist, you will play a crucial role in driving business impacts and delving deep into the complexities of computer vision and deep learning problem-solving. This high-visibility opportunity is a perfect match for technical leaders who are passionate about making a tangible difference in the AI healthcare landscape.

Don't miss this exceptional chance to leave a lasting mark on healthcare technology. Apply now and harness your expertise to revolutionize AI-driven medical innovation!

What You Will Do:

Technical Responsibilities

• Lead research that enables learning the semantics of multimodal data (images, video, text, audio, speech, and other modalities) as well as apply multimodality learning to medical data (EHR, CT Scans, X-ray, MRI, etc).
• Work towards long-term ambitious research goals, while identifying intermediate milestones
• Explore the new opportunities that generative AI, Large Language Models, and foundation models unlocks in healthcare and identify practical applications of these new technological advances to improve standard of care.
• Develop and implement novel AI algorithms and models, fine-tune and optimize foundation models, develop deployment mechanisms and guardrails for these models.
• Work and collaborate with cross-functional teams, including data scientists, CV engineers, and healthcare professionals, to translate latest advances in AI into scalable solutions.
• Stay abreast of latest developments in AI and machine learning, particularly in generative models, foundation models and LLMs.
• Publish research findings in top-tier journals and conferences and represent Stryker in the AI research community.

What You Will Need:

Basic Qualifications:

• Bachelor's degree in software engineering/ Computer Science or related discipline with 6+ years of work experience OR Master’s in relevant disciplines with 4+ years of experience OR PhD degree in relevant disciplines with 2+ years of work experience.
• Publications in machine learning, AI, computer science, statistics, applied mathematics, data science, or related technical fields.

Preferred Qualifications:

• At least 3 years of experience in AI research, with a focus on generative AI and LLMs.
• Proven work experience in a university or industry lab(s), in a lead role with primary emphasis on AI research
• Strong programming skills in Python and familiarity with AI/ML frameworks such as TensorFlow, PyTorch, Huggingface etc.
• Experience in writing reusable, scalable, test-driven and well documented codebase.
• Excellent written and verbal communication skills, with the ability to effectively communicate complex research findings to both technical and non-technical stakeholders.
• Bonus for:
• Prior experience developing AI applications using LLM
• Academic publication in ML/AI conferences / journals such as CVPR, ICCP, ICCV, NeurIPS, ICML, ICLR etc. is a plus.