About Lilly
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.
About the Role: Generative AI - Machine Language Engineer
This position is for an expert in machine learning to help us extract value from our data. You will lead all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production. The key responsibilities will be to prepare modern Natural Language Technology (NLT) platforms to gain insights from key business data. The employee will be responsible for designing, implementing, and managing data preparation and advanced analytics tools in addition to demonstrating insights from the varied sources of data to business users. Responsibilities also include developing and designing language understanding/generation systems and effectively using text representation techniques.
Objectives Of The Role
- Work in tandem with our engineering partners to identify and implement the most optimal cloud-based ML solutions for the company.
- Research, design, and adopt cutting-edge NLG algorithms to address real-world challenges such as summarization.
- Define and document best practices and strategies regarding deployment and infrastructure maintenance.
- Ensure ML Model performance, uptime, and scale, maintaining high standards of code quality and thoughtful design.
- Maintain a platform that automates creating, training, deploying, and updating machine learning models.
- Managing BI Platforms in accordance with company security guidelines.
- Build effective relationships with business areas, strategic vendors, and key delivery partners such as the Advanced Analytics and Data Sciences (AADS) group to share expertise and seek opportunities to reuse internal processes and services, so we can streamline implementation and support of key systems.
Required Experience
Proven experience with the following:
- Designing, developing, and researching Machine Learning systems, models, and schemes through data science and data analytics prototypes.
- Understanding of Natural Language Processing (NLP), Natural Language Understanding (NLU), and Natural Language Generation (NLG).
- Develop and implement technical efforts to design, build, and deploy AWS ML models at the direction of lead architects, including large-scale data processing, computationally intensive statistical modeling, and advanced analytics.
- Familiarity with deep learning, machine learning, and NLP/NLG frameworks (like Keras, TensorFlow or PyTorch etc.), HuggingFace Transformers and libraries (like scikit-learn, spacy, gensim, CoreNLP etc.).
- Should have experience in AWS services such as SageMaker, Elasticsearch, and general knowledge of AWS architecture & other services.
- Ability to write robust code in Python, Java, and R.
- Experience optimizing model hyperparameter tuning for speed and cost.
- Experience in building MLOps pipeline using MLOps frameworks like Kubeflow, MLFlow, and DataRobot.
- Experience with Docker and Kubernetes.
- Familiarity with Eventbridge and AWS step function for workload orchestration.
- Experience with Agile Development.
Desirable Skills
- 3-10 years of production model deployment experience for ML solutions.
- Highly motivated/self-starter with a sense of ownership, willingness to learn, and desire to succeed.
- Strong teamwork, problem-solving, and analytical skills.
- Deep knowledge of math, probability, statistics and algorithms.
- Strong understanding of Pharma Quality Standards and Practices.
- Excellent leadership and interpersonal skills (both verbal and written).