5+ years of hands-on experience in NLP or related fields, with a strong portfolio of successful projects, emphasizing the development and deployment of NLP solutions.
Deep expertise in leading the development and implementation of state-of-the-art NLP models, including the fine-tuning of Large Language Models (LLMs) for a variety of applications.
Strong programming skills in Python, with significant experience using machine learning libraries for tasks in Natural Language Understanding (NLU) and Generation (NLG), covering everything from developing and fine-tuning models to deploying them.
A commitment to continuous learning and staying updated with the latest technological developments, academic papers, and trends in the AI field, ensuring the application of cutting-edge methods in projects.
Previous experience with real-time systems, demonstrating the ability to design, implement, and optimize NLP solutions that require high availability and low latency, will be considered an advantage.
Experience in voice modality applications, such as speech recognition or voice synthesis will be highly valued.
Degree in Computer Science, Engineering, or related technical field.
5+ years of experience in DevOps or software engineering, with a proven track record in deploying, automating, maintaining, and managing high-availability systems.
Expertise in using a wide range of cloud services (e.g., AWS, Azure, GCP), container orchestration tools (e.g., Kubernetes, Docker), and infrastructure as code (e.g., Terraform, CloudFormation).
Strong background in Linux/Unix Administration.
Proficiency in scripting languages (e.g., Bash, Python) and automation tools (e.g., Ansible, Puppet, Chef).
Experience with continuous integration and deployment (CI/CD) pipelines and tools (e.g., Jenkins, GitLab CI, CircleCI).
Solid understanding of network protocols and services (TCP/IP, HTTP/S, SSH, FTP).
Strong problem-solving skills and the ability to work in a fast-paced, evolving environment.
Excellent communication and teamwork skills, with experience collaborating with software development teams to implement DevOps practices.
