AI Evaluation Engineer, Device Intelligence

Danaher Corporation•Washington, DC

104d•Remote

About The Position

Bring more to life. At Danaher, our work saves lives. And each of us plays a part. Fueled by our culture of continuous improvement, we turn ideas into impact – innovating at the speed of life. Our 63,000+ associates work across the globe at more than 15 unique businesses within life sciences, diagnostics, and biotechnology. Are you ready to accelerate your potential and make a real difference? At Danaher, you can build an incredible career at a leading science and technology company, where we’re committed to hiring and developing from within. You’ll thrive in a culture of belonging where you and your unique viewpoint matter. Learn about the Danaher Business System which makes everything possible. The AI Evaluation 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 Europe or Eastern US. In this role, you will have the opportunity to: Define, own and run the AI evaluation strategy for AI products in life sciences, diagnostics, and biotechnology. Design and implement robust evaluation frameworks for agentic workflows, LLMs / NLP, computer vision and multimodal models. Develop and execute evaluation plans to measure performance, reliability, and safety across multimodal datasets. Collaborate with the Sr. Director for the Initiative, Sr. AI Engineers and product teams to align evaluation criteria with product KPIs and regulatory needs. Analyze evaluation results, identify weaknesses, and recommend improvements to AI models and workflows. Build automated pipelines for continuous evaluation and monitoring of AI systems in production. Within Danaher Corporate - Digital Product Development, we believe in designing a better, more sustainable workforce. We recognize the benefits of flexible, remote working arrangements for eligible roles and are committed to providing enriching careers, no matter the work arrangement. This position is eligible for a remote work arrangement in which you can work remotely from your home. Additional information about this remote work arrangement will be provided by your interview team. Explore the flexibility and challenge that working within Danaher can provide.

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, or related field; MS/PhD preferred.
Proven experience designing and implementing evaluation methodologies for AI systems, including LLMs and computer vision.
Strong knowledge of metrics for AI performance, robustness, and fairness, especially in regulated domains.
Expertise in at least 3 of the following: benchmarking frameworks, statistical validation, synthetic data generation, adversarial testing, explainability techniques.
Proficiency in Python and ML libraries (e.g., PyTorch, TensorFlow) and familiarity with evaluation tools (e.g., OpenAI Evals, Dynabench, Promptfoo).
Ability to communicate complex evaluation results to technical and non-technical stakeholders and influence model improvements.

Nice To Haves

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

Define, own and run the AI evaluation strategy for AI products in life sciences, diagnostics, and biotechnology.
Design and implement robust evaluation frameworks for agentic workflows, LLMs / NLP, computer vision and multimodal models.
Develop and execute evaluation plans to measure performance, reliability, and safety across multimodal datasets.
Collaborate with the Sr. Director for the Initiative, Sr. AI Engineers and product teams to align evaluation criteria with product KPIs and regulatory needs.
Analyze evaluation results, identify weaknesses, and recommend improvements to AI models and workflows.
Build automated pipelines for continuous evaluation and monitoring of AI systems in production.