Kensho is a Machine Learning (ML) and Natural Language Processing (NLP) company, centered around providing cutting-edge solutions to meet the challenges of some of the largest and most successful businesses and institutions. We are owned by S&P Global and operate independently. Our toolkit illuminates insights by helping the world better understand, process, and leverage messy data. Specifically, Kensho’s solutions largely involve speech recognition (ASR), entity linking (NED), structured document extraction, automated database linking, text classification, and more.

The NLP team at Kensho Technologies is at the forefront of designing and applying cutting-edge machine learning in the domains of natural language processing, natural language interfaces, and information retrieval paradigms over some of the richest and most complex financial and market datasets in the world. We are continuously expanding our portfolio of projects and are looking for passionate researcher-engineers to help us build and deploy state-of-the-art ML systems!

Recently RAG-based systems that integrate structured and unstructured data are at the core of our team's projects. These solutions are integrated into the S&P Global platforms, providing users with the ability to find and analyze complex financial data efficiently.

The NLP team works closely with the Data, Product, Design, Backend & Frontend teams, and has the full support of our ML Ops and Infrastructure teams.

We are seeking a Senior ML Engineer to help accelerate and improve our ML development cycle, continually raising standards of prototyping, building, and maintaining SOTA ML solutions.

At Kensho, we believe in flexibility-first, and give our employees the opportunity to work from where they feel most productive and engaged (must be in the United States). We also value in-person collaboration, so there may be times when travel to one of our Kensho hubs (e.g., Cambridge, MA or NYC) will be required for team meetings or company events.

Kensho states that the anticipated base salary range for the position is 175k - 225k. In addition, this role is eligible for an annual incentive bonus and equity plans. At Kensho, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case.

What You’ll Do:

• Work closely with Data, Product, Design, and Engineering teams to design and develop Large Language Model (LLM)-based systems that integrate structured and unstructured data, ensuring the delivery of innovative ML solutions that meet customer needs
• Solve unique challenges around LLM-orchestration, such as data access patterns, memory and context management, and conducting thorough evaluations
• Actively participate in all stages of the ML lifecycle, from problem framing and data exploration to model experimentation, deployment, and monitoring in production, ensuring the continuous improvement and optimization of our ML solutions
• Work with unique, proprietary data from both unstructured and structured datasets, applying advanced NLP techniques to extract insights and build solutions that drive business value
• Work closely with Product and Design teams to build ML-based solutions that enhance user experiences and meet business objectives
• Collaborate closely with the ML Operations team to create automated solutions for managing the entire ML systems lifecycle, from initial technical design to seamless implementation

What You'll Need:

• Bachelor's degree or higher in Computer Science, Engineering, or a related field
• 4+ years of significant, hands-on industry experience with machine learning, natural language processing (NLP), and information retrieval systems, including designing, shipping, and maintaining production systems
• Strong proficiency in Python
• Experience with natural language generation or code generation and familiarity with evaluative processes
• Experience working with machine learning libraries/frameworks for Large Language Model (LLM) orchestration, such as Langchain, Semantic Kernel, LLamaIndex, etc
• Proven experience building ML pipelines for data processing, training, inference, maintenance, evaluation, versioning, and experimentation
• Demonstrated effective coding, documentation, collaboration, and communication habits
• Strong problem-solving skills and a proactive approach to addressing challenges
• Ability to adapt to a fast-paced and dynamic work environment

Technology You'll Encounter:

• ML: PyTorch, Transformers, HuggingFace, LangChain, Semantic Kernel
• Tools/Toolkits: Weights & Biases, DVC, LabelBox
• Techniques: RAG, Tool Utilization, Information Retrieval, Prompt Management, Fine-tuning
• Deployment: Airflow, Docker, Kubernetes, Jenkins, AWS