Sr. AI Engineer

Danaher•Washington DC, DC

1d•$135,000 - $180,000•Remote

About The Position

The Sr. AI Engineer, Device Intelligence will be a key member of the AI Product and Imaging Innovation team, reporting to its Sr Director. This new role is instrumental in the implementation of cutting-edge AI systems that leverage data created by Danaher devices to extract meaningful insights and dramatically improve user experience, with the goal of upleveling Danaher's devices across Life Sciences, Diagnostics and Biotechnology sectors. This position is remote in Eastern US. In this role, you will have the opportunity to: Collaborate with the VP and the broader team to develop Enterprise grade capabilities and platforms enable the creation of intelligent instruments and autonomous labs. Design and implement advanced AI systems, including next-generation multi-level and multi-domain agentic systems, to enhance instrument intelligence and lab automation, upleveling user capabilities. Work closely with cross-functional and cross company teams to translate product concepts into concrete AI architectures, ensuring alignment with product success criteria and measurable KPIs. Lead the technical implementation of AI projects of notable complexity, involving multiple functions and typically spanning multi-quarter timelines. Drive innovation in the AI software stack, focusing on maximizing value extraction from instruments for customers through AI systems. Collaborate with business stakeholders, technical experts, and subject matter experts to build comprehensive AI roadmaps for imaging products across various verticals.

Requirements

Bachelor's degree in computer science, electrical engineering, robotics, automation, life sciences or a related field.
Long standing experience in the Life Science, Diagnostics, Biotechnology or Tech Industry, including multiple years of experience with Agentic Systems, LLMs, Automation, Robotics, and/or Multimodal AI.
Demonstrable expertise with at least 3 of the following: convolutional neural networks, foundation models, vector databases, AI evaluation methods, RAG approaches, agentic frameworks, robotics.
Proven track record of successful end-to-end implementation of AI projects in imaging applications, particularly in life sciences or healthcare domains.
Strong programming skills in languages such as Python or C++.
Extensive experience with deep learning frameworks (e.g., TensorFlow, PyTorch, OpenCV) and containerization technologies (e.g., Docker, Kubernetes).
Including the use of genAI and agentic systems for coding.
Experience with cloud platforms (e.g., AWS, Google Cloud, Azure).
Familiarity with hardware acceleration technologies (e.g. TPUs, GPUs, ARM-CPUs).
Demonstrated ability to work effectively with cross-functional teams.
Communicate complex technical concepts to both technical and non-technical stakeholders.
Align AI development with product goals and roadmaps.

Nice To Haves

An advanced degree (MS or PhD) in a relevant area (i.e. Neural Networks, Foundation Model, Agentic Workflows, Machine Learning, Computer Vision, Robotics) is preferred.
Experience with regulatory processes, especially for medical devices and AI/ML-based software as a medical device (SaMD).
Familiarity with quality management systems and standards relevant to the life sciences and diagnostics industries.
Knowledge of instrument control mechanisms and how they integrate with AI systems for enhanced automation.

Responsibilities

Collaborate with the VP and the broader team to develop Enterprise grade capabilities and platforms enable the creation of intelligent instruments and autonomous labs.
Design and implement advanced AI systems, including next-generation multi-level and multi-domain agentic systems, to enhance instrument intelligence and lab automation, upleveling user capabilities.
Work closely with cross-functional and cross company teams to translate product concepts into concrete AI architectures, ensuring alignment with product success criteria and measurable KPIs.
Lead the technical implementation of AI projects of notable complexity, involving multiple functions and typically spanning multi-quarter timelines.
Drive innovation in the AI software stack, focusing on maximizing value extraction from instruments for customers through AI systems.
Collaborate with business stakeholders, technical experts, and subject matter experts to build comprehensive AI roadmaps for imaging products across various verticals.