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Machine Learning Engineer, Athena (Remote, US)

  • Location: Remote, United States
  • Team: Data Science
  • Role Type: Full-Time Employee (Individual)
Medallia’s mission is to help companies win through customer experience. The world’s best-loved brands trust Medallia’s Experience Cloud™, which embeds the pulse of the customer in an organization and empowers employees with the real-time customer data, insights, and tools they need to make every experience great. Named a leader in the most recent Forrester Wave and ranked in the 2018 Forbes Cloud 100 list, Medallia is growing quickly, with a global footprint that spans Silicon Valley, Austin, New York, Washington DC, London, Paris, Sydney, Buenos Aires, Tel Aviv, and Prague. Here, we value people for each of the aspects that make them whole. We believe that people should not be defined only by a job title—nobody is "just an engineer" or "just a salesperson." We are each partners, parents, children, siblings, friends, and former classmates. We have different backgrounds and we celebrate different cultures. And, just like our product, we honor each of the experiences that build our people.

At Medallia we hire the whole person, not just a part of them.

The Role:

 Machine Learning Engineer at Medallia / Athena applies artificial intelligence to uncover hidden meanings in vast amounts of customer experience information and determine the right action for each touchpoint and journey. You will help further the capabilities of the Athena platform by building features to get deeper insights on the data using state-of-the-art machine learning and AI algorithms. Own the End 2 End life cycle of the Model development. It includes requirement gathering, data acquisition, model creation, deployment & support in production.

The Work:
Design, implement and support ongoing essential data pipelines for collection, quality transformation, and generation of insights as a prerequisite for ML/AI model training. Build and deploy portable, Scalable ML Workflows enabling easy orchestration and experimentation. Write the end-to-end ML Pipelines for acquiring data for the creation and re-training of models. Debug and solve complex problems that may span the E2E lifecycle of the Model. Proactively monitor and manage the availability of the Model infrastructure and applications and provide on-call support (if required). Work closely with product engineering teams to align the product expectation with the ML engineering expectations.
In the past year, the team has tackled projects as diverse as:
·       Optimizing Representation Learning for Text Analysis
·       Suggestion Mining classification and clustering
·       Customer Journey Analysis and Prediction
·       Infrastructure for Statistics Toolkit for Non-Expert Users
·       Toxicity Detection and Masking in Feedback
·       Automated insight generation from time-series data

Our Engineering Culture:

  • We don’t expect to be perfect, but we are always proactively seeking out ways to help ourselves and our teams to minimize pain points within our infrastructure and code base.  
  • We love technology -- and follow the latest technologies and sharing what we learn.
  • We are not afraid of failing when we are experimenting with different technologies, development methodologies, and toolings.
  • We build strong relationships with team members around the globe.

Minimum Qualifications:

  • 2+ years experience creating and maintaining ML models in production.
  • Experience building and designing ML-related ETL/ELT pipelines using Spark, Hadoop, Kafka, Apache Airflow, etc.
  • Have performed software development in a production environment using Java/Python/Scala. 
  • BA/BS degree in Computer Science or a related technical discipline, or equivalent practical experience.

Preferred Qualifications:

  • Experience with Tensorflow or PyTorch
  • Experience with object-oriented/object function scripting languages: Python, Java & Scala.
  • Experience with big data tools: Hadoop, Spark, Kafka, or similar.
  • Experience with data pipeline and workflow management tools such as Airflow.

At Medallia, we don’t just accept difference—we celebrate it 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. Equal opportunity and consideration are afforded to all qualified applicants and employees. We won't unlawfully discriminate on the basis of gender identity or expression, race, ethnicity, religion, national origin, age, sex, marital status, physical or mental disability, Veteran status, sexual orientation, and any other category protected by law. We also consider all qualified applicants regardless of criminal histories, consistent with legal requirements. Medallia is committed to working with and providing reasonable accommodation to applicants with disabilities in accordance with the American Disabilities Act and local disability laws. For information regarding how Medallia collects and uses personal information, please review our Privacy Policies.