Machine Learning Team Lead

6 days ago

Copenhagen, Copenhagen, Denmark LanguageWire Full time

About the Role



LanguageWire is seeking an experienced Machine Learning Team Lead to spearhead our AI/NLP initiatives. The ideal candidate will have expertise in product and API development and will lead the charge in engineering groundbreaking AI solutions, pushing the boundaries of what's possible in the language industry.



The Role




  • Oversee a talented team of engineers with expertise in machine learning, NLP, full-stack development, AI applications, quality assurance, and product management.
  • 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.
  • 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.


Requirements




  • 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.
  • 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 or Context API: For state management in front-end applications.
  • Version Control and Collaboration: Git: For source code management. GitHub, Azure DevOps: For collaborative development and code reviews.
  • Monitoring and Logging: Prometheus, Grafana, or ELK Stack (Elasticsearch, Logstash, Kibana) for monitoring applications and infrastructure.
  • Security: OAuth, JWT, and other authentication/authorization protocols.
  • Data Visualization and BI Tools: Looker, Tableau, Power BI or similar tools for data analysis and visualization.
  • Agile methodologies and understanding of design workflows and software architecture.

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