OverviewMedallia is the pioneer and market leader in Experience Management. Our award-winning SaaS platform, Medallia Experience Cloud, leads the market in the understanding and management of experience for candidates, customers, employees, patients, citizens and residents.
We are more than a software company. We want to be known as a company that does the right thing, no matter the challenge or controversy. We are committed to creating a culture that values every person and every experience. Individual life experiences shape the way we interact with the world, which is why we encourage people to bring their whole selves to work each day. The strength of our global workforce is the most significant contributor to our success.
We believe: Every Experience Matters. Talent is Everywhere. All Belong Here.
At Medallia, we hire the whole person.
We are looking for a motivated Senior Machine Learning Engineer to join our Medallia Athena Platform team.
The Role
As a Senior ML Engineer in our Athena Platform team, you will be responsible for architecting and developing the building blocks of the next generation of products at Medallia. You will work with product to build world class products providing some of the largest companies with actionable insights.
Responsibilities- Collaborate with product and design teams to build innovative new features and products for the Customer Experience space.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.
- Create and maintain optimal data pipeline architecture.
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer feedback applying sentiment analytics, NLP, clustering methodologies and generative AI.
- Keep our data separated and secure across national boundaries through multiple data centers.
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our product.
- Architect and implement scalable solutions for dealing with large data prepared by the data science team, and making it available to clients with high performance
- Design and implement APIs to power front-end applications
QualificationsMinimum Qualifications
- BA/BS degree in Computer Science or a related technical discipline, or equivalent practical experience.
- Strong experience in a technical role working on distributed systems and web services.
- 5+ years performing software development in a production environment using a mainstream object-oriented programming language (Python, Java or Scala)
- Engineering experience including distributed systems like Spark, Hadoop, Kafka etc.
- Relational SQL including Postgres
- Experience with services deployment and customization using K8s
- Strong experience with code quality best practices and implementing testing architectures and modularization on large codebases.
Preferred Qualifications
- Experience with data pipeline and workflow management tools such Airflow or Kubeflow.
- Experience with big data tools: Hive, Presto/Trino, Redash.
- Familiarity with model serving platforms: TensorFlow, TensorRT, Triton, KServe
- Micro services development using Django or Spring framework
- Relational SQL and NoSQL databases experience, including Postgres and ElasticSearch
At Medallia, we celebrate diversity and recognize the value it brings to our customers and employees. Medallia is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, genetic information, disability, veteran status, or any other applicable status protected by state or local law. Individuals with a disability who need an accommodation to apply please contact us at ApplicantAccessibility@medallia.com. For information regarding how Medallia collects and uses personal information, please review our Privacy Policies. Applications will be accepted for 30 days from the date this role was posted or until the role has been filled.
