Machine Learning Engineer

At Elanco (NYSE: ELAN) – it all starts with animals!

As a global leader in animal health, we are dedicated to innovation and delivering products and services to prevent and treat disease in farm animals and pets. At Elanco, we are driven by our vision of Food and Companionship Enriching Life and our purpose – all to Go Beyond for Animals, Customers, Society and Our People.

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: Machine Learning (ML) Engineer
 

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 machine learning models. You will translate complex business problems into scalable, production-ready AI solutions, applying a strong blend of software engineering discipline and deep ML expertise to design, build, and deploy models that deliver real-world value.
 

Your Responsibilities:
* Model Development & Utilisation: Design, build, and train bespoke ML models, and identify, tune, and deploy third-party ML models (proprietary and open-source).
* Production Deployment & MLOps: Manage the deployment of ML models into production environments, ensuring scalability and reliability, and build/maintain robust MLOps pipelines for CI/CD, 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.
* Cross-Functional Collaboration: Work closely with data scientists, product managers, and software engineers to define requirements, integrate models, and deliver impactful features.
* Code Quality & Performance Tuning: Write clean, maintainable, and well-tested production-grade code, upholding high software engineering standards, and monitor/analyze model performance for optimization.
 

What You Need to Succeed (minimum qualifications):
* Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, or a related quantitative field.
* Proven hands-on experience deploying machine learning models into a production environment.
* Advanced proficiency in Python with deep experience in core ML/data science libraries, coupled with a strong foundation in software engineering principles.
 

What will give you a competitive edge (preferred qualifications):
* Experience with MLOps tools and frameworks and containerisation technologies (Docker, Kubernetes).
* Practical experience with Public Cloud (Microsoft Azure and Google Cloud Platform) and their ML services (e.g., Azure ML, Vertex AI).
* Proven experience with relevant DevSecOps concepts and tooling, including CI/CD, Git SCM, Containerisation, and Infrastructure-as-Code (HashiCorp Terraform).
* Solid understanding of the theoretical foundations of machine learning algorithms, including deep learning, NLP, and classical ML.
* Broad understanding of life science business models, regulatory requirements, and excellent communication skills to articulate complex technical decisions.
 

Additional Information:
* Travel: 0-10%
* Location: Hook, UK - Hybrid Work Environment
 

Don’t meet every single requirement? Studies have shown underrecognized groups are less likely to apply to jobs unless they meet every single qualification. At Elanco we are dedicated to building a diverse and inclusive work environment. If you think you might be a good fit for a role but don't necessarily meet every requirement, we encourage you to apply. You may be the right candidate for this role or other roles!

Elanco is an EEO/Affirmative Action Employer and 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