Machine Learning Engineer

Location: Indianapolis

** At Elanco (NYSE: ELAN) – it all starts with animals!
**** 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:
** As a Machine Learning (ML) Engineer at Elanco, you will be a key member of our engineering team, specializing in the end-to-end lifecycle of custom and third-party (including open source) machine learning models. You will translate complex business problems into scalable, production-ready AI solutions. This role is focused on the practical application of machine learning, requiring a strong blend of software engineering discipline and deep ML expertise to design, build, and deploy models that deliver real-world value.

This includes four strategic priorities:
* ** Pipeline Acceleration:
** Optimize the search and approval of high impact medicines with a focus on speed, cost and precision.
* ** Manufacturing Excellence:
** Improve the efficiency, quality and consistency of core manufacturing processes, specifically execution and equipment effectiveness.
* ** Sales Effectiveness:
** Simplify the process to find, trust and consume relevant customer insights that drive sales growth and improved engagement.
* ** Productivity:
** Expand operating margin through efficiency by systematically reducing our operating expenses across the company, improving profitability.
** Your Role:**
* ** Custom Model Development:
** Design, build, and train bespoke ML models tailored to specific business needs, from initial prototype to full implementation.
* ** Third-Party Model Utilization:
** Identify, tune and deploy third-party ML models, covering proprietary and open-source models.
* ** Production Deployment:
** Manage the deployment of ML models into our production environments, ensuring they are scalable, reliable, and performant.
* ** MLOps and Automation:
** Build and maintain robust MLOps pipelines for Continuous Integration/Continuous Delivery (CI/CD), model monitoring, and automated retraining.
* ** Data Pipeline Construction:
** Collaborate with data engineers/stewards to build and optimize data pipelines that feed ML models, ensuring data quality and efficient processing for both training and inference.
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* Cross-Functional Collaboration:

** Work closely with data scientists, product managers, and software engineers to define requirements, integrate models into applications, and deliver impactful features.
* ** Code and System Quality:
** Write clean, maintainable, and well-tested production-grade code. Uphold high software engineering standards across all projects.
* ** Performance Tuning:
** Monitor and analyze model performance in production, identifying opportunities for optimization and iteration.
** What You Need to Succeed (Minimum Qualifications):**
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* Education:

** A Bachelor’s or Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, or a related quantitative field.
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* Required Experience:

** 3+ years experience in Machine Learning/Engineer or relevant work.
* ** Programming Excellence:
** Advanced proficiency in Python and deep experience with core ML/data science libraries (e.g., PyTorch, Tensor Flow, scikit-learn, pandas, Num Py).
* ** Software Engineering Fundamentals:
** Strong foundation in software engineering principles, including data structures, algorithms, testing, and version control (Git).
* ** ML Model Deployment:
** Proven, hands-on experience deploying machine learning models into a production environment.
* ** MLOps Tooling:
** Experience with MLOps tools and frameworks and containerization technologies (Docker, Kubernetes).
* ** Cloud Platform Proficiency:
** Practical experience with Public Cloud, specifically Microsoft Azure and Google Cloud Platform (GCP) and their ML services (e.g., Azure ML, Vertex AI).
** What Will Give You the Competitive…