Machine Learning Engineer (Full Stack)

Eli Lilly-posted about 1 year ago
$142,500 - $228,800/Yr
Full-time • Mid Level
Indianapolis, IN
10,001+ employees
Chemical Manufacturing
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The Machine Learning Engineer (Full Stack) at Lilly is responsible for leading the development and deployment of machine learning models that enhance predictive analytics and decision-making across various pharmaceutical and marketing processes. This role involves designing, building, and implementing advanced ML/AI models, supporting data strategy and analytics, optimizing model performance, and ensuring compliance with ethical AI practices. The position offers an opportunity to significantly impact patients' lives through innovative solutions in healthcare.

  • Design, build, scale, and implement advanced ML/AI models using diverse data types/sources to enhance products and efficiency.
  • Support the creation of analytics frameworks to mine data, identify trends, and provide actionable insights.
  • Continuously test, refine, and improve model accuracy using robust methodologies, including A/B testing and AI observability metrics.
  • Utilize tools like AWS, Azure, Google Cloud Platform, Docker, Kubernetes, Jenkins, and MLOps frameworks for end-to-end ML solutions.
  • Work with data scientists, business analysts, and stakeholders to integrate ML models into broader strategies.
  • Maintain high standards of integrity and compliance, adhering to ethical AI practices and regulatory requirements.
  • PhD degree in statistics, engineering, computer science, mathematics, or a related field.
  • 1+ years of experience in machine learning engineering or data science roles.
  • 1+ years of experience with AI and machine learning algorithms including supervised and unsupervised learning, deep learning, neural networks, and natural language processing.
  • Experience with AI technologies and tools, such as Natural Language Processing (NLP), Generative AI (GenAI), Foundation models, and Large Language Models.
  • Advanced proficiency in programming languages such as Python, R, C++, or JavaScript, and familiarity with AI libraries and frameworks like PyTorch, Keras, TensorFlow, and Scikit-learn.
  • Strong understanding of software development methodologies including Agile and Scrum, as well as expertise in version control systems like Git.
  • Experience with containerization and orchestration technologies such as Docker and Kubernetes, and familiarity with CI/CD pipeline setup and management.
  • Knowledge of advanced machine learning and deep learning techniques and frameworks, including but not limited to supervised and unsupervised learning models, neural networks, GANs, autoencoders, and transformers.
  • Eligibility to participate in a company-sponsored 401(k); pension; vacation benefits;
  • Eligibility for medical, dental, vision and prescription drug benefits;
  • Flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts);
  • Life insurance and death benefits;
  • Certain time off and leave of absence benefits;
  • Well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).
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