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

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.

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!

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.

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!

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!

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.