Intern - Advanced Intelligence and Research

About the Role

Day-to-day, the intern will engage in data exploration, model prototyping, and evaluation, ensuring robust experimental results and well-documented data preprocessing pipelines. This involves handling imbalanced, noisy, and high-dimensional datasets, which require meticulous attention to detail and a deep understanding of computer vision principles. The role also encompasses building and optimizing models for real-time inference and batch processing, including benchmarking latency/throughput and accuracy trade-offs, which is crucial for applications in medical imaging and manufacturing.

Eli Lilly and Company values its employees and fosters an environment that encourages growth, learning, and contribution. As an intern in this role, one can expect to work in a dynamic and supportive setting where collaboration and open communication are key. The company's commitment to healthcare innovation and its global reach provide a platform for interns to make a meaningful impact.

What You Will Do

• Apply traditional and advanced computer vision algorithms to solve complex challenges through data exploration, model prototyping, and evaluation.
• Handle imbalanced, noisy, and high-dimensional datasets to ensure robust experimental results and well-documented data preprocessing pipelines.
• Partner with cross-functional teams to understand requirements and translate them into CV experiments in medical imaging and/or manufacturing vision-based inspection.
• Support the configuration and integration of imaging systems (cameras/sensors) in collaboration with engineers, as applicable to the project.
• Build and optimize models for scenarios such as real-time inference and batch processing, including benchmarking latency/throughput and accuracy trade-offs.
• Contribute to the model lifecycle by packaging experiments, writing clean inference scripts/APIs, and supporting deployment handoff under guidance from the team.
• Leverage machine learning, optimization, and deep learning techniques to improve detection/segmentation performance and reduce manual review effort for selected use cases.
• Utilize version control (e.g., Git) and Docker to ensure reproducible experiments, with exposure to CI/CD workflows being a plus.
• Leverage image annotation tools and image registration methods, especially for medical imaging workflows, for domain-specific challenges.
• Collaborate with the team and communicate results through clear experiment reports, demos, and documentation.

What We Are Looking For

• A strong foundation in computer science, machine learning, or a related field, with a keen interest in computer vision and its applications.
• Experience with programming languages such as Python, and familiarity with deep learning frameworks like TensorFlow or PyTorch.
• Understanding of computer vision concepts, including object detection, segmentation, and image processing.
• Experience with handling and preprocessing large datasets, including imbalanced and noisy data.
• Ability to work collaboratively in a cross-functional team environment and communicate complex ideas effectively.
• Familiarity with version control systems like Git and containerization tools such as Docker.
• Basic understanding of medical imaging or manufacturing processes, and how computer vision can be applied to these fields.
• Strong analytical and problem-solving skills, with the ability to approach complex challenges from multiple angles.
• Ability to learn quickly and adapt to new technologies and workflows.

Nice to Have

• Experience with CI/CD workflows and Agile development methodologies.
• Familiarity with cloud platforms such as AWS or Google Cloud, and their services related to machine learning and computer vision.
• Knowledge of image annotation tools and image registration methods, particularly in the context of medical imaging.
• Participation in Kaggle competitions or similar projects that demonstrate expertise in machine learning and computer vision.
• Experience with working in a remote environment and using collaboration tools for distributed teams.

Benefits and Perks

• Generous Paid Time Off to ensure a healthy work-life balance.
• 401k Matching Retirement Plan to support long-term financial goals.
• Visa Sponsorship for international candidates, reflecting the company's global outlook and commitment to diversity.
• Four Day Work Week, allowing for an improved quality of life and increased productivity.
• Generous Parental Leave, supporting employees during significant life events.
• Tuition Reimbursement, encouraging ongoing education and professional development.
• Relocation Assistance, for those who need to move for the role, ensuring a smooth transition.
• Opportunity to work with a global healthcare leader, contributing to meaningful projects that impact lives worldwide.
• Collaborative and dynamic work environment that fosters growth and innovation.

• Tailor Your Resume: Ensure your resume highlights relevant projects or experiences in computer vision, machine learning, and data preprocessing, as these are key to the role.
• Prepare to Discuss Projects: Be ready to talk about your past projects, especially those involving computer vision and deep learning, and how you overcame challenges during these projects.
• Showcase Your Skills: Demonstrate your proficiency in programming languages like Python, and your experience with deep learning frameworks and tools like TensorFlow or PyTorch.
• Emphasize Collaboration: Highlight any experience working in cross-functional teams and your ability to communicate complex ideas to both technical and non-technical stakeholders.
• Be Open to Learning: Show enthusiasm for learning new technologies and methodologies, as the field of computer vision and AI is rapidly evolving.
• Ask About Culture: During the interview, ask questions about the company culture, team dynamics, and opportunities for growth and professional development to ensure you're a good fit.
• Discuss Your Challenges: Be prepared to discuss challenges you've faced in your previous roles or projects, and how you approached solving them, as this shows problem-solving skills and resilience.