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 datasets through academic projects, internships, industry roles, or open‑source work, with evidence of hands‑on model development and evaluation. Top Technical and interpersonal skills : Proficiency in Python and familiarity with ML/CV libraries such as scikit‑learn, PyTorch or TensorFlow, and OpenCV; understanding of core ML concepts and basic deep learning; and a collaborative, clear‑communicating working style. What will give you a competitive edge (preferred qualifications): Scientific data and project experience: Exposure to scientific datasets (e.g., high‑content imaging, histopathology, microscopy, behavioral video, assay data) and completed projects, theses, or publications showing applied ML/CV skills with scientific or healthcare relevance. Technical craft and tooling: Familiarity with training deep learning models on GPUs, use of Git and reproducible workflows, and exposure to data platforms or cloud environments such as Databricks, Azure, or AWS. Growth orientation and initiative: Demonstrated ability to learn quickly, iterate on models and analyses, and contribute to reusable code, tools, or documentation that improve team efficiency and quality. Additional Information: Travel: Up to 10% Location: Global Elanco Headquarters - Indianapolis, IN – Hybrid Work Environment Elanco Benefits and Perks: We offer a comprehensive benefits package focusing on financial, physical, and mental well-being while encouraging our employees to pursue our purpose! Some highlights include: Multiple relocation packages Two weeklong shutdowns (mid-summer and year-end) in the US (in addition to PTO) 8-week parental leave 9 Employee Resource Groups Annual bonus offering Flexible work arrangements Up to 6% 401K matching Elanco is an EEO/Affirmative Action Employer and does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status Elanco may use automated tools, including AI, to support parts of our recruitment process, such as reviewing applications against job‑related criteria and/or transferrable skills. These tools help ensure a consistent, structured evaluation, but they do not make hiring decisions. All decisions involve a human reviewer. For more information on how we handle personal data, please see our Elanco Workforce Privacy Notice.