Machine Learning Team Lead
LanguageWire, Denmark
Job Description
LanguageWire is seeking an experienced Machine Learning Team Lead with expertise in product and API development to spearhead our AI/NLP initiatives. Does this role seem interesting? Yes? You should definitely read on!
The role you’ll play
In this critical role, the successful candidate will leverage advanced AI and NLP technologies to enhance our product offerings and expand our capabilities, both for internal and external use. The Team Lead will play a key role in ensuring that our AI innovations are integrated into intuitive products and made available through reliable and robust APIs, significantly benefiting our customers. As a Tech Team Lead, you will provide technical leadership and be responsible for adjacent services and developing the next generation of neural models for machine translation and content generation.
The team you’ll be a part of
The successful candidate will join a dynamic, cross-functional team at the forefront of AI and NLP technology, dedicated to revolutionizing language services. As a ML Tech Team Lead, you will collaborate closely with Full-Stack Engineers, QA Engineers, Machine Learning Engineers, Data Engineers and report to the Director of Machine Learning.
If you want to make a difference, make it with us by
- Oversee a talented team of 5-6 engineers with expertise in machine learning, NLP, full-stack development, AI applications, quality assurance, and product management.
- You will steer the technical direction in AI and NLP, establish objectives for your team, foster their career advancement, offer mentorship, and guide them through resolving intricate challenges. Act as a growth catalyst for your team members, spread primarily across Copenhagen and Valencia.
- Be the technical authority and product visionary, ensuring our machine learning and AI capabilities are seamlessly integrated into products and exposed through powerful APIs. Take ownership of the AI services lifecycle within your team. Partake in customer support and actively contribute to documenting resolutions and problems.
- Advocate for the you build it, you run it" philosophy to promote a culture of end-to-end ownership and continuous improvement.
- Apply a data-driven approach to decision-making, utilizing metrics and feedback to guide product development and API strategy. Guarantee that our machine translation and next gen AI services are not only innovative but also reliable, scalable, available, and speedily delivered to meet the demands of clients.
- In this pivotal role, you will lead the charge in engineering groundbreaking AI solutions, pushing the boundaries of what's possible in the language industry. Your mission will be to develop innovative next Gen AI products, transforming how languages are learned, processed, and understood on a global scale.
In one year, you’ll know you were successful if
- You have successfully navigated the team through the challenges of integrating AI technologies into user-friendly products, as evidenced by positive feedback from internal and external stakeholders. You have established robust monitoring and prediction services that support the continuous improvement and scalability of our product offerings.
- You have introduced innovative machine translation and content generation tools that have measurably improved efficiency and customer satisfaction.
- You have cultivated a culture of excellence within your team, promoting collaboration, innovation, and professional growth, resulting in high team engagement and retention.
Desired experience and competencies
What does it take to work for LanguageWire?
What you’ll need to bring
- Expert Knowledge in Python and especially using frameworks like Huggingface Transformers, TensorFlow or PyTorch, Scikit-learn.
- Experience with neural models based on Transformer architectures.
- Expert Knowledge in JavaScript/TypeScript for full-stack development and interaction with APIs on the front end. Frameworks like Node.js, Vue.js, Express.js.
- API Development: RESTful API principles, understanding how to design stateless, secure, and scalable APIs.
- Expertise in MLOps Tools - Docker: For containerizing applications and models.
- Kubernetes: For orchestration of containers.
- CI/CD Tools (e.g., Jenkins, GitLab CI, GitHub Actions): For continuous integration and deployment pipelines. Terraform (IaC).
- MLflow or Kubeflow: For managing the machine learning lifecycle.
- Cloud Platforms: Azure, AWS, Google Cloud
- Data Management: SQL/NoSQL
- Data Lakes/ Data Warehousing: Solutions like Amazon S3, Redshift, or Google BigQuery. Apache Kafka or other streaming services for real-time data processing.
- Redux o