Machine Learning Scientist - NLP

at  ObserveAI

ABOUT US

Observe.AI is the fastest way to boost contact center performance with live conversation intelligence. Built on the most accurate AI engine in the industry, Observe.AI uncovers insights from 100% of customer interactions and maximizes frontline team performance through coaching and end-to-end workflow automation. With Observe.AI, companies can act faster with real-time insights and guidance to improve performance, from more sales to higher retention.
Observe.AI is trusted by hundreds of customers and partners, including Pearson, Accolade, Group 1 Automotive, Southeast Trans, and Public Storage. Our recent $125 million Series C led by Softbank Vision Fund 2 with participation from Zoom Video Communications, Inc., brings our total funding to date to $213M, with investments from Menlo Ventures, Next47, NGP Capital, Emergent Ventures, Scale Ventures, Nexus Ventures, and Y-Combinator. For more information, visit www.observe.ai.

THE OPPORTUNITY

We are seeking a Machine Learning Scientist to join our advanced research team focused on Natural Language Processing and Conversational AI. This role is ideal for those with a passion for pioneering new models, architectures, and approaches to solve complex business problems. You will engage in long-term, green-field projects characterized by high ambiguity and significant innovation potential, differentiating this position from roles with more defined scopes and immediate product impact.
As a Machine Learning Scientist, your work will be foundational, setting the stage for future technologies and methodologies in our product development. This position requires a strong theoretical grounding in machine learning and NLP, as well as the creativity and research skills necessary to navigate uncharted technological territories.

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.