Every month, tens of millions of people respond to surveys, fill check-out forms, inquire about products and plan work with Typeform. We want to make this experience seamless, effortless, intuitive and adaptive to each respondent, and Machine Learning (ML) is a crucial pillar to achieve this purpose.

That’s where you come in. We’re looking for a Senior ML Software Engineer to tackle complex problems collaboratively.

You will team up with our ML Specialists and Data Engineers to design scalable state-of-the-art infrastructure to serve the ML models behind some of the key product features, as well as models that power our marketing and customer success campaigns. You will be involved in all steps of the models’ lifecycles, and ensure that we balance end-to-end product delivery and maintenance, perform exploratory investigations for existing model improvements and new model development.

The critical areas of exploration and development include:

• Supervised and unsupervised ML modeling (regression and classification modeling, clustering, etc.).
• NLP models that can help guide our customers to write better questions and increase completion rates for their forms and surveys, as well as better understand the responses they receive.
• Recommendation/Relevance models that help our customers to get more value from Typeform. Our goal is to help our customers discover more features and applications of Typeform in their businesses.
• Models to drive our programmatic marketing efforts (lead scoring, intent to pay, etc.), including buyer and customer segmentation, etc.
• Models to evolve our forms into conversational agents capable of handling bi-directional conversations and responding to goal-oriented requests that do not follow a traditional tree structure associated with forms or traditional chatbots.

The ideal candidate should have experience developing ML libraries and production-ready services. You understand the scalability and performance trade-offs between different frameworks, models architectures, and how to develop and maintain the ML pipeline in distributed and non-distributed environments. You have worked with Software Engineering teams to improve the product architecture and to allow for easy deployment of machine learning models. You will also partner with Product, Marketing and Customer Success teams throughout the whole development cycle of the model, from ideation to production.

What you’ll do:

• Provide expert advice, make architectural considerations, define and promote standards, find solutions, and employ best practices around ML solutions in production, including instrumentation, debugging and networking.
• Develop the required infrastructure to run ML models with demanding requirements.
• Establish and promote best software engineering practices.
• Partner with ML Specialists, Data Scientists and Product Managers across to productize ML models: specification, development, QA, experimentation, and deployment.
• Develop, productize, and maintain models for customer segmentation, LTV and churn prediction, marketing spends optimization and creative optimization.
• Develop, productize and maintain models for product recommendations, sentiment analysis, intent classification, named entity recognition, etc.
• Drive further improvement to our workflow for experimenting, developing, and testing new ML algorithms 

About You

Here's what we are after:

• You have proven experience as an ML Software Engineer, with a track record of building ML solutions.
• You have experience in design, development, and maintenance of ML pipelines, including feature processing and model training.
• You are an “engineer at heart”. You take pride in designing software systems and producing clean, modular, high-quality code, and have experience working with version control and continuous integration tools.
  You have extensive experience with Scala and/or Java.
• You have extensive experience with Python, scikit-learn or similar ML frameworks, as well as Deep Learning (DL) frameworks such as Tensorflow or PyTorch.
• Experience in Spark.
• Experience in AWS and Kubernetes.
• You have experience in service-oriented architectures and microservices.
• Best software engineering practices: SOLID principles, test-driven development (TDD), continuous integration and development (CI/CD), code instrumentation.
• You have experience building large-scale Machine Learning pipelines and data-driven products.
• You are entrepreneurial, self-directed and strongly biased towards action. You thrive in a fast-paced environment.
• You love to learn and continuously invest time to improve your skills.
• You are a great team player.
• You are fluent in English and enjoy working in a multicultural environment.

And for some extra points:

• NLP
• Deep Learning