Machine Learning Engineer - NLP

Responsibilities:

• Design and develop state-of-the-art LLM-powered AI capabilities and agentic AI/multi-agent systems end-to-end, from ideation to production for Observe. AI product offerings in a fast-paced startup environment.
• Work with cutting-edge tools and technologies in machine learning, deep learning, and natural language processing, including LLMs and LLM-powered technologies/paradigms, including agentic AI.
• Build/maintain highly scalable production systems that power AI capabilities on Observe. AI product/platform.
• Optimize ML models and processing pipelines for performance, cost-effectiveness, and scale.
• Work with a world-class ML team in building exciting stuff, mentor juniors, and influence peers/stakeholders.
• Collaborate cross-team with engineers, product managers, customer-facing teams, and customers to understand pain points and business opportunities to build the right solution for the right problem.
• Keep up-to-date with the latest ML/DL/NLP literature and influence the technological evolution of the Observe AI platform.
• Contribute to the community through tech blogs and publishing papers in ML/NLP conferences like EMNLP, ACL, etc.

Requirements:

• Bachelor's or master's degree in computer science or related disciplines from a top-tier institution with exposure to ML/DL/NLP/NLU.
• An engineering mindset with the competencies of an applied scientist.
• 1+ years of industry experience in building large-scale NLP/NLU systems, with recent experience in building LLM-powered applications and agentic systems.
• Strong understanding of the fundamentals of ML and NLP and practical aspects of building ML systems in production, backed by extensive hands-on experience in building/scaling customer-facing ML/NLP/NLU applications.
• Good understanding of recent advances in building LLM-powered applications and multi-agent systems at scale.
• Excellent implementation skills in Python and machine learning frameworks such as PyTorch, TensorFlow, Hugging Face, etc., and deploying/maintaining scalable machine learning systems in production.
• Ability to provide thought leadership in one or more technical areas of interest to Observe. AI and influence product development.
• Excellent communication, collaboration skills, and presentation skills.
• Experience with Spoken Language Understanding is a plus.
• Published papers in top NLP/NLU conferences or workshops are a plus.
• Relevant open-source contributions are a plus.