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Senior ML Engineer - NLP (m/f/d)

🎤 Why voize? Because we’re more than just a job!

At voize, we’re revolutionizing the healthcare industry with AI: Nurses simply speak their documentation into their smartphones, and our AI automatically generates the correct entries. This saves each nurse an average of 39 minutes per day, improves the quality of documentation, and makes their daily work much more rewarding.

voize is YCombinator-funded, already in use at over 600 senior care homes, and has grown by 100% in the last 90 days. Our customers save over 3.5 million hours annually – time spent on people instead of paperwork.

But this is just the beginning. With our self-developed voize AI, we’re transforming not only the healthcare industry, but also have the potential to create value in many other sectors – from healthcare to inspections.

💡 Your Mission:

If you're a Senior Machine Learning Engineer experienced with NLP and are excited to work at the cutting edge of product design, applied ML research, and MLOps, then go ahead and apply! With us, you'll build products with direct user feedback, train AI models with real data, and ship new features to production every day.

🤝 Your Skillset – What you bring to the table

  • Several years experience shipping models (LLMs) into production

  • Significant experience with deep learning frameworks (preferably PyTorch)

  • Proven capability training new models from scratch

  • Experience in speech recognition or NLP & transformer models (TTS, STT)

  • Engineering excellence with CI/CD for example Docker, Kubernetes

  • Nice to have: German language skills would be a bonus

🚀 Your Daily Business – No two days are alike

  • Take ownership for the design, training, evaluation, and deployment of our deep learning models in the space of speech recognition and NLP

  • The models you build and refine are at the heart of our applications and directly impact the end-user

  • You'll get to engineer large self-supervised trainings as well as fast inference for mobile devices and hosted environments

🎯 Our Success Mindset – How we work at voize

  • Resilience is one of your strengths – you see challenges as opportunities, not obstacles

  • Iterative working suits you – you test, learn, and improve constantly instead of waiting for perfection

  • Communication & feedback come naturally to you – you openly address issues and both give and receive constructive feedback

🌱 Growing together – what you can expect at voize

  • Become a co-creator of our success with virtual stock options

  • Our office is in Berlin, and we offer remote work

  • We provide flexible working hours because you know best when you work most efficiently!

  • Access to various learning platforms (e.g., Blinkist, Audible, etc.)

  • We have an open culture and organize regular work weeks and team events to collaborate and bond

  • We are a fast-growing startup, so you'll encounter various challenges, providing the perfect foundation for rapid personal growth

  • Your work will make a real impact, helping alleviate the workload for healthcare professionals

  • Free Germany Ticket and Urban Sports Club membership

  • 30 days of vacation – plus your birthday off

Ready to talk? Apply now! 🚀

We look forward to your application and can’t wait to meet you – no matter who you are or what background you have!

What You Should Know About Senior ML Engineer - NLP (m/f/d), Voize

At voize, we’re redefining the healthcare landscape with innovative AI solutions, and we are looking for a talented Senior ML Engineer - NLP to join our dynamic Berlin team! Imagine being able to help nurses save an average of 39 minutes per day simply by speaking their documentation into their smartphones. How cool is that? Our AI automatically generates the correct entries, transforming tedious paperwork into seamless documentation, enhancing the quality of care while making the workday more fulfilling for healthcare professionals. With our YCombinator funding and current usage in over 600 senior care homes, we have already saved more than 3.5 million hours annually, allowing staff to spend more time with patients. As a Senior ML Engineer with a focus on NLP, you will be at the forefront of product design and applied ML research, directly impacting our user experience. You will take ownership of the design, training, evaluation, and deployment of our cutting-edge deep learning models in the realms of speech recognition and natural language processing. Your days will be varied and exciting, filled with building and refining large self-supervised trainings while ensuring fast inference for mobile and hosted environments. Join us if you are ready to tackle real-world problems, thrive in an iterative environment, and embrace feedback. At voize, your work won’t just make a difference; it will revolutionize the way healthcare is delivered. Ready to dive in? Let’s make an impact together!

Frequently Asked Questions (FAQs) for Senior ML Engineer - NLP (m/f/d) Role at Voize
What are the key responsibilities of a Senior ML Engineer - NLP at voize?

As a Senior ML Engineer - NLP at voize, your main responsibilities will include designing, training, evaluating, and deploying deep learning models focused on speech recognition and natural language processing. You will take ownership of the entire model lifecycle, with a focus on building products that are influenced by direct user feedback. Additionally, you will work on the engineering aspects, ensuring robust CI/CD processes, and collaborate closely with other team members to refine our AI technologies.

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What qualifications are needed to apply for the Senior ML Engineer - NLP position at voize?

To qualify for the Senior ML Engineer - NLP position at voize, you should have several years of experience successfully shipping machine learning models, particularly large language models (LLMs). Proficiency with deep learning frameworks, especially PyTorch, is essential. Experience in speech recognition and NLP, as well as working with transformer models, will be crucial. An understanding of CI/CD practices and tools like Docker and Kubernetes is also needed. Bonus points for German language skills!

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How does working at voize differ from other companies for Senior ML Engineers?

At voize, Senior ML Engineers in NLP will find a unique and dynamic work environment that emphasizes rapid personal growth and the opportunity to make a real impact in the healthcare sector. Unlike many companies, voize encourages an iterative work process where you're not just waiting for perfection but constantly testing and improving. Our open culture promotes communication and constructive feedback, enabling you to thrive and excel in your role while tackling exciting challenges on a daily basis.

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What is the daily routine like for a Senior ML Engineer - NLP at voize?

The daily routine of a Senior ML Engineer - NLP at voize is anything but mundane. You'll find yourself taking ownership of various challenging tasks each day, including designing and refining deep learning models, working with real data to train advanced AI technologies, and deploying features to production. With a focus on collaboration, your day will also involve engaging with your team for feedback and iterating on your work continuously. Flexibility is a key aspect—working hours are adapted to your most productive times!

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What are the benefits of working as a Senior ML Engineer - NLP at voize?

Working as a Senior ML Engineer - NLP at voize comes with a host of benefits designed to support your career and personal growth. You'll have access to various learning platforms, virtual stock options, and the flexibility of remote work with adaptable hours to fit your schedule. Plus, enjoy 30 days of vacation, including your birthday off, along with perks like a free Germany Ticket and an Urban Sports Club membership. More importantly, you'll be part of a forward-thinking startup making a significant impact on the healthcare industry!

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Common Interview Questions for Senior ML Engineer - NLP (m/f/d)
Can you describe your experience with NLP and how it applies to the role of Senior ML Engineer at voize?

In interviews, emphasize specific projects where you've used NLP techniques, detailing the challenges faced and how your contributions led to success. Discuss the frameworks and models you utilized, the datasets you worked with, and any direct impact your work had on user experiences or outcomes.

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What methods do you use to evaluate machine learning models, especially for NLP tasks?

When answering this question, highlight your approach to model evaluation, including metrics such as accuracy, precision, recall, and F1 score. Discuss the importance of using a validation set and cross-validation techniques, as well as how you incorporate user feedback into model performance assessments.

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How do you handle challenges when deploying models into production?

Discuss your experience with CI/CD practices, the importance of monitoring models post-deployment, and strategies to address potential issues, like performance drops or bugs. Point out specific tools and technologies you have used, such as Docker and Kubernetes, and emphasize your focus on continuous improvement based on user data.

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What is your experience with deep learning frameworks, particularly PyTorch?

Highlight specific projects where you've used PyTorch, focusing on the depth of your knowledge and technical skills. Mention how it has helped you in building and training neural networks for NLP tasks, and discuss any optimizations or innovations you implemented using the framework.

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Can you explain transformer models and their significance in speech recognition?

Give a brief yet informative overview of transformer architecture, emphasizing its role in natural language processing. Discuss self-attention mechanisms and how they improve contextual understanding in speech recognition applications. Use examples from your previous work to showcase your expertise.

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Describe a project where you implemented CI/CD for ML models.

Provide a detailed account of a specific project where you successfully implemented CI/CD pipelines, outlining the tools used, the challenges faced, and the results. Emphasize the importance of automation and how it improved the deployment process and overall efficiency.

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What techniques do you use to handle imbalanced datasets when training NLP models?

Discuss a couple of techniques you might employ, such as re-sampling methods, synthetic data generation, or adjusting class weights. Illustrate your answer with examples from past experiences where you overcame similar challenges.

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How do you stay updated with the latest advancements in machine learning and NLP?

Share your strategies for keeping current, such as attending conferences, participating in online courses, following key influencers in the field on social media, and reading relevant research papers or articles. Emphasize your enthusiasm for continuous learning and adaptation to new technologies.

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What role does user feedback play in improving ML models at voize?

Highlight the importance of integrating user feedback into the iterative model development process. Discuss how you might collect and analyze user input to inform model adjustments and optimizations, ultimately enhancing user experience and effectiveness of the AI solution.

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Why do you want to work at voize as a Senior ML Engineer - NLP?

Tailor your answer to reflect your passion for healthcare technology and your alignment with voize's mission. Discuss how the company's innovative approach to utilizing AI to improve healthcare resonates with you personally and professionally, and express your eagerness to contribute to meaningful changes.

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EMPLOYMENT TYPE
Full-time, hybrid
DATE POSTED
March 12, 2025

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