We are a rapidly growing SaaS company with a pre-IPO valuation of $7 billion. Our platform serves over 1 million enterprise users across 30,000 customers in 130 countries, generating more than $600 million in annual recurring revenue (ARR).
Building from a blank sheet of paper, this is an exciting opportunity to work on a range of cutting-edge projects involving Natural Language Processing (NLP), Large Language Models (LLMs), and advanced AI methodologies. You will work with both sensitive customer content and publicly available documents, enhancing our products with document set comprehension, longitudinal insight extraction, semantic search capabilities, and retrieval augmented generation.
We are seeking experts in Applied Science or Machine Learning for Mid, Senior/Staff, and Principal level positions. Candidates should be proficient in Python, with experience using libraries like NumPy, scikit-learn, Pandas, NLTK, spaCy, or PyTorch. Additionally, expertise in building ML/AI pipelines and using tools such as MLFlow or AWS SageMaker is required.
JOB DESCRIPTION
We are seeking talented and driven Applied Scientists to join our growing team. Reporting to Applied Science Manager, this exciting role involves working on state-of-the-art projects in Natural Language Processing (NLP), Large Language Models (LLMs), and other advanced AI methodologies. Your contributions will be crucial in developing platform-level AI capabilities, such as document set comprehension, longitudinal insight extraction, semantic search, and structured retrieval augmented generation, to accelerate AI adoption across our diverse product suite.
Experience Level:
• Applied Scientist I: 0-2 years of relevant experience.
• Applied Scientist II: 2-5 years of relevant experience.
• Senior Applied Scientist: 5+ years of relevant experience.
• Staff/Principal Applied Scientist: 10+ years of relevant experience.
JOB RESPONSIBILITIES
• Design and develop machine learning models and algorithms for various applications.
• Test and evaluate the performance of these models and algorithms.
• Collaborate with the applied science teams to develop and implement NLP solutions for processing large document sets.
• Collaborate with machine learning engineers and software engineers to productize AI-based capabilities.
• Work on projects involving sensitive customer content used for our customers’ board communications, which requires stringent privacy and security measures.
• Develop and support semantic search, structured retrieval, and RAG use cases across our various products.
• Utilize LLMs, knowledge graphs, traditional NLP methods, and custom models to provide document set comprehension capabilities and facilitate insight extraction.
• Focus on complex legal and regulatory language within the GRC industry, ensuring accurate and relevant model outputs.
• Implement and fine-tune models using Python and PyTorch, leveraging AWS infrastructure.
• Document and communicate your approach, progress, and results to the broader team.
• Staying up-to-date with the latest research and developments in the field of machine learning and AI.
• [Staff/Senior] Lead and oversee research projects, design and analyze experiments, build evaluation frameworks to measure the quality of our solutions.
EXPERIENCE
• Proficiency in Python, NumPy, scikit-learn, Pandas, NLTK, spaCy, PyTorch, or similar.
• Experience with model deployment and scaling.
• Strong foundational knowledge in NLP, machine learning, and statistical modeling.
• Proficiency in building ML/AI pipelines and relevant tools such as MLFlow, AWS SageMaker, or similar.
REQUIRED EXPERIENCE
Technical Skills:
• Hands-on experience with LLMs including prompt engineering, fine-tuning, model evaluation, and building RAG-based functionality.
• Experience with semantic search and information retrieval systems.
• Familiarity with reinforcement learning methods.
Soft Skills:
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.
• Self-motivated with a proactive approach to project management.
• Ability to work effectively in a hybrid or remote environment.
REQUIRED EDUCATION
• Bachelor’s degree in Computer Science, Machine Learning, Mathematics, or a related field.
• Master’s or PhD preferred.