Machine Learning & Computer Vision Scientist – R&D (Junior/Associate)

At Elanco (NYSE: ELAN) – it all starts with animals!

As a global leader in animal health, we are dedicated to innovation and delivering products and services to prevent and treat disease in farm animals and pets.

At Elanco, we are driven by our vision of Food and Companionship Enriching Life and our purpose – all to Go Beyond for Animals, Customers, Society and Our People.

At Elanco, we pride ourselves on fostering a diverse and inclusive work environment.

We believe that diversity is the driving force behind innovation, creativity, and overall business success.

Here, you’ll be part of a company that values and champions new ways of thinking, work with dynamic individuals, and acquire new skills and experiences that will propel your career to new heights.

Making animals’ lives better makes life better – join our team today!

Your Role: Machine Learning & Computer Vision Scientist – R&D (Junior/Associate)

As the Machine Learning & Computer Vision Scientist (Junior/Associate), you will help drive Elanco’s R&D innovation by implementing and refining ML and computer‑vision models that support faster, better‑informed decisions.

You will work closely with senior scientists and R&D stakeholders to turn proprietary molecular, in vitro, imaging, and digital endpoint data into predictive and classification models for target identification, molecular optimization, ADMET, and digital biomarkers in animal health.

Your Responsibilities:


* Implement and refine ML/CV models under guidance, developing, training, and tuning models on R&D datasets (molecular, in vitro, imaging, behavioral) in collaboration with senior scientists to align with scientific objectives.


* Prepare and manage datasets for modeling by cleaning, transforming, and merging data from multiple scientific sources, running exploratory analyses, and contributing to feature engineering and clear dataset documentation.


* Support data collection, annotation, and synthetic data work by helping improve capture and labeling workflows for images, video, and assay data, assisting with annotation guidelines, and evaluating synthetic data and augmentation to improve sparse datasets and model robustness.


* Assist with model evaluation and reporting by contributing to train/validation/test design, applying appropriate metrics and error analyses, and documenting methods, assumptions, limitations, and results for review and reuse.


* Collaborate and grow ML/CV expertise by joining cross‑functional project meetings, sharing learnings through short demos or presentations, and actively building knowledge in drug discovery, development, and ML/CV techniques.

What You Need to Succeed (minimum qualifications):


* Education: Master’s degree in a quantitative field (e.g., Data Science, Engineering, Mathematics, Physics, Statistics, Bioinformatics)


* Required Experience: Early applied ML/CV experience: 0–3 years applying ML and/or computer vision to real ...