Provide technical leadership in NLP projects, guiding the team in the implementation of cutting-edge solutions.
Stay updated on industry trends and advancements, ensuring our NLP offerings remain at the forefront of technology.
Project Management:
Manage end-to-end NLP projects, collaborating with project managers, developers, and other stakeholders to ensure successful delivery within defined timelines and budgets.
Define project scopes, objectives, and resource requirements.
Client Interaction:
Act as a technical point of contact for clients, understanding their NLP requirements, and providing expertise in crafting effective solutions.
Collaborate with the sales and business development teams in pre-sales activities.
Team Development:
Lead and mentor a team of NLP engineers, fostering a culture of innovation, collaboration, and continuous learning.
Conduct training sessions to enhance the team's NLP skills.
Solution Architecture:
Work closely with the architecture team to design scalable and efficient NLP solutions that meet client needs.
Contribute to the development of technical documentation and best practices.
Quality Assurance:
Ensure the quality of NLP solutions through rigorous testing, code reviews, and the implementation of best practices.
Identify and address performance bottlenecks and optimize algorithms.
Research and Development:
Engage in ongoing research activities, experimenting with new algorithms and methodologies to enhance our NLP capabilities.
Collaborate with the research community and academia to stay informed about the latest developments.
Qualifications:
12+ years of experience in NLP research-- and development within an IT services environment.
Proven track record of successfully delivering NLP projects for clients.
Strong programming skills, particularly in Python, and familiarity with relevant libraries and frameworks.
Excellent communication and client-facing skills.
Must Have Skills:
Ensure the quality of NLP solutions through rigorous testing, code reviews, and the implementation of best practices.
Identify and address performance bottlenecks and optimize algorithms.
Research and Development:
Engage in ongoing research activities, experimenting with new algorithms and methodologies to enhance our NLP capabilities.