Machine Learning Scientist - NLP

What you’ll do day to day

• Research and Development: Conduct rigorous research and develop new approaches to machine learning and NLP that can eventually be transformed into scalable, production-ready solutions.
• Model Innovation: Focus on creating novel models and architectural innovations to address emerging business needs, exploring areas not covered by existing solutions.
• Solution Crafting: Work closely with our partners and product managers to understand their specific problems and develop tailored ML solutions to address these challenges effectively.
• Domain Research to Production: Conduct domain-specific research that is directly applicable to our core business areas. Collaborate closely with Machine Learning Engineers to translate these research insights into robust, production-ready services that meet the stringent requirements of our production systems in terms of scalability, reliability, and efficiency.
• Risk Management: Navigate the inherent risks and ambiguities of new research projects, developing strategies to mitigate potential setbacks in exploratory research.
• Academic Collaboration: Engage with the academic community by attending conferences, publishing research findings, and staying connected with the latest research trends and breakthroughs in ML and AI.Strategic
• Influence: Influence the strategic direction of our NLP and AI initiatives by providing expert insights and recommendations based on your research findings.

What you’ll bring to the role

• Educational Background: PhD or Master’s degree in Computer Science, AI, or a closely related field, with a specialization in Machine Learning, Deep Learning, or NLP.
• Research Experience: Extensive experience in ML and NLP research, demonstrated by a track record of peer-reviewed publications and active participation in the scientific community.
• Technical Expertise: Profound knowledge of advanced ML techniques, especially in Python and frameworks like Pytorch, and TensorFlow.
• Innovative Thinking: Ability to conceptualize new and effective approaches to complex problems, pushing the boundaries of current knowledge and technology.
• Communication Skills: Strong ability to communicate complex ideas effectively, both verbally and in writing, to both technical and non-technical audiences.
• Additional Qualifications: Experience in Spoken Language Understanding or Conversational AI is highly valued, along with contributions to relevant open-source projects.