Senior Machine Learning Engineer - Self Study (all genders)

Babbel is the top-selling language learning platform globally. We are driven by our purpose of creating mutual understanding through language. Through the Babbel app, Babbel Live classes, Babbel podcasts, and Babbel for Business products, we provide learners with the most effective solutions, enabling them to communicate in real-life scenarios with real people.

The Babbel team is as diverse as our content. With headquarters in Berlin, Germany and our US office in New York, we're a team of 1,000+ people from over 80 different nationalities.

For more information about Babbel and our language learning solutions, please visit www.babbel.com or download our app from the App Store or Play Store. 

We are looking for a Senior Machine Learning Engineer for one of our Product Teams.

You will join a team of engineers, computational linguists, NLP and machine learning specialists building new speech features driven by NLP and machine learning.

You will:

• Design, build and deploy models that power our NLP solutions.
• Accelerate our journey into machine learning, impacting millions of language learners across the globe.
• Evaluate & improve existing machine learning (ML) processes, training and deploying NLP production ready machine learning models and setting up MLOps pipelines
• Own your work and drive what matters
• Work in a multidisciplinary AI team
• Explore innovative methods to advance on language learning contexts
• Collaborate cross-functionally on feature design, architectural decisions, and assessing technical debt
• Help shape our coding guidelines and quality standards
• Provide recommendations to improve our services and shape our culture of testing, learning, and innovation
• Participate in and potentially lead knowledge-sharing sessions  - we are a learning company inside and out
• Focus on continuous learning and improvement, and drive the evolution of our engineering practices
• Collaborate with computational linguists and fullstack engineers to bridge the gap between research and production, and transform concepts into deployable features
• Swiftly react and troubleshoot operational events

You are:

• Quick Learner: A quick learner who is comfortable with uncertainty and shines like a star when the path is clear and certain.
• An ambassador for continuous improvement:  The culture of being better today than yesterday. You are comfortable to provide and receive feedback.
• Experiment Enthusiast: Comfortable working on experiments and have a can-do attitude to build MVPs and iterate on them in short cycles, but at the same time do not compromise on having high quality standards and clean code. You know how to find a balance between addressing technical debt and ensuring delivery speed.
• Tech Explorer: You enjoy navigating NodeJS and Python backends, AWS infrastructure, and tools, and have a solid understanding of platforms like AWS lambda, AWS DynamoDB, AWS Kinesis etc.

Your profile:

• Experience in fast Build-Measure-Learn cycles
• Computer science, Mathematics or related engineering degree.
• 4+ years of professional experience as Python engineer, with industry experience in modern Python, ML and Deep Learning frameworks (e.g. PyTorch, ONNX) 
• Transforming NLP prototypes into production-ready solutions with commitment to engineering best practices;
• Designing and building end-to-end MLOps pipelines on the cloud from data gathering and transformation to model training, validation, benchmarking, and monitoring. Ability to select hardware to run an ML model with the required latency
• 2+ years of experience with AWS services, operations and architecture (e.g. Sage Maker,AWS Lambda, API Gateway, S3)
• Knowledge of Statistics and algorithms.
• Automated testing experience on different levels.
• Strong interest in contributing to product development as demonstrated by your positive approach to gathering requirements, building and iterating on features, and continuously reviewing and innovating.
• Troubleshooting and problem-solving skills to identify and resolve issues efficiently

Nice to haves:

• DevOps experience using terraform.
• Exposure to big data solutions such as Snowflake
• Experience with AWS SageMaker.
• Experience in Natural Language Processing.

Some perks of becoming a Babbelonian:

• Enjoy 30 vacation days and the chance to take a 3-month Sabbatical. Plus family and life situation counseling.
• Decide how, when and from where you want to work with our flexible working hours and remote friendly options as Jobbatical (up to 3 months inside the EU) or work from our fully equipped office with nap, faith and family rooms. 
• Learn and grow with the internal learning opportunities, and use a yearly learning & development budget for external training. Learn languages with Babbel for free with your full access to Babbel & Babbel Live classes.
• Take advantage of your mobility benefits options and a discounted Urban Sports Club membership. 
• Be part of our employee communities (such as Femgineers, DE&I Ambassadors and LGBTQIA groups), attend cultural and regular social events. 

Diversity at Babbel

As part of our ongoing journey towards building a diverse, equitable and inclusive company, we welcome everyone to apply, especially those individuals who are underrepresented in tech. We are a learning company, inside and out, and we encourage you to apply even if you do not fit all the technical requirements - all candidates are assessed based on skills, qualifications and on our business needs. Please state your pronouns in your application, and let us know if you’d like to be addressed by a name other than the one appearing on your official documents. If you have a disability or special need, feel welcome to inform us, so that we can provide you with the proper assistance in the application process.

Sounds good? We are already looking forward to hearing from you! Check out also our jobs page, our blog and our techblog to get an impression about #lifeatbabbel!