At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.

Organization Overview:

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our 39,000 employees work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the globe.

Role Summary:

We are looking for a skilled and innovative AI Developer to design, develop, and deploy AI-powered applications and services. The ideal candidate will have hands-on experience with machine learning, deep learning, and natural language processing, and will be responsible for building intelligent systems that solve real-world problems. This role requires strong programming skills, a solid understanding of AI/ML algorithms, and the ability to work collaboratively in a fast-paced environment.

Responsibilities:

Develop and implement machine learning models and algorithms for classification, regression, clustering, recommendation, and more.Build and maintain data pipelines for training and inference workflows.Collaborate with data scientists, product managers, and software engineers to integrate AI models into production systems.Optimize model performance and scalability for real-time and batch processing.Conduct experiments, evaluate model performance, and iterate based on results.Stay up to date with the latest research and advancements in AI/ML and apply them to practical use cases.Document code, processes, and model behavior for reproducibility and compliance.Basic Requirements:

1. Programming Languages

Python: Core language for AI/ML development. Proficiency in libraries like:NumPy, Pandas for data manipulationMatplotlib, Seaborn, Plotly for data visualizationScikit-learn for classical ML algorithmsFamiliarity with R, Java, or C++ is a plus, especially for performance-critical applications.

2. Machine Learning & Deep Learning Frameworks

Experience building models using the following:

TensorFlow and Keras for deep learningPyTorch for research-grade and production-ready modelsXGBoost, LightGBM, or CatBoost for gradient boostingUnderstanding of model training, validation, hyperparameter tuning, and evaluation metrics (e.g., ROC-AUC, F1-score, precision/recall).

3. Natural Language Processing (NLP)

Familiarity with:

Text preprocessing (tokenization, stemming, lemmatization)Vectorization techniques (TF-IDF, Word2Vec, GloVe)Transformer-based models (BERT, GPT, T5) using Hugging Face TransformersExperience with text classification, named entity recognition (NER), question answering, or chatbot development.

4. Computer Vision (CV)

Experience with:

Image classification, object detection, segmentationLibraries like OpenCV, Pillow, and AlbumentationsPretrained models (e.g., ResNet, YOLO, EfficientNet) and transfer learning

5. Data Engineering & Pipelines

Ability to build and manage data ingestion and preprocessing pipelines.Tools: Apache Airflow, Luigi, Pandas, DaskExperience with structured (CSV, SQL) and unstructured (text, images, audio) data.

6. Model Deployment & MLOps

Experience deploying models as:

REST APIs using Flask, FastAPI, or DjangoBatch jobs or real-time inference servicesFamiliarity with:Docker for containerizationKubernetes for orchestrationMLflow, Kubeflow, or SageMaker for model tracking and lifecycle management

7. Cloud Platforms

Hands-on experience with at least one cloud provider:AWS (S3, EC2, SageMaker, Lambda)Google Cloud (Vertex AI, BigQuery, Cloud Functions)Azure (Machine Learning Studio, Blob Storage)Understanding of cloud storage, compute services, and cost optimization.

8. Databases & Data Access

Proficiency in:

SQL for querying relational databases (e.g., PostgreSQL, MySQL)NoSQL databases (e.g., MongoDB, Cassandra)Big data tools like Apache Spark, Hadoop, or Databricks is a plus

9. Version Control & Collaboration

Experience with Git and platforms like GitHub, GitLab, or Bitbucket.Familiarity with Agile/Scrum methodologies and tools like JIRA, Trello, or Asana.

10. Testing & Debugging

Writing unit tests and integration tests for ML code.Using tools like pytest, unittest, and debuggers to ensure code reliability.

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly 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.

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