Machine Learning Engineer

Kensho is S&P Global’s hub for AI innovation and transformation. With expertise in Machine Learning and data discovery, we develop and deploy novel solutions for S&P Global and its customers worldwide. Our solutions help businesses harness the power of data and Artificial Intelligence to innovate and drive progress. Kensho’s solutions and research focus on speech recognition, entity linking, document extraction, automated database linking, text classification, natural language processing, and more.

Kensho is looking for ML Engineer interns to join the group of Machine Learning Engineers working on developing a cutting-edge GenAI platform, LLM-powered applications, and fundamental AI toolkit solutions such as Kensho Extract. We are looking for talented people who share our passion for bringing robust, scalable, and highly accurate ML solutions to production.

Are you looking to leverage your teammates’ diverse perspectives to solve hard problems? If so, we would love to help you excel here at Kensho. You will be working on a team with experienced engineers and have an opportunity to learn and grow. We take pride in our team-based, tightly-knit startup Kenshin community that provides our employees with a collaborative, communicative environment that allows us to tackle the biggest challenges in data. In addition, as an intern you will have the opportunity to attend technical and non-technical discussions as well as company wide social events.

We value in-person collaboration, therefore interns are required to work out of the Cambridge HQ or our New York City office!

Technologies & Tools We Use:

• Agentic systems: Agentic Orchestration, Information Retrieval, LLM code generation, LLM tool utilization, Multi-modal Embeddings, Multi-turn Conversationality, Textual RAG systems

• Core ML/AI: DGL, GNNs, HuggingFace, LightGBM, NVIDIA NeMo, PyTorch, SKLearn, Transformers, XGBoost

• Data Exploration and Visualization: Jupyter, Matplotlib, Pandas, Weights & Biases

• Data Management and Storage: Apache Spark, AWS Athena, DVC, LabelBox, OpenSearch, Postgres/Pgvector, Qdrant, S3, SQLite

• Deployment & MLOps: Airflow, AWS, DeepSpeed, Docker, Grafana, Jenkins, Kubernetes, Ray, vLLM, WhyLabs

What You’ll Do:

• Assist in conducting original work on large proprietary unstructured data and structured datasets, applying advanced NLP techniques to extract insights and build solutions that drive business value.

• Design, build, and maintain scalable production-ready ML systems

• Participate in the ML model lifecycle, from problem framing to training, deployment, and monitoring in production

• Partner with our ML Operations team to deliver solutions for automating the ML model lifecycle, from technical design to implementation

• Work in a cross-functional team of ML Engineers, Product Managers, Designers, Backend & Frontend Engineers who are passionate about delivering exceptional products

What We Look For:

Outstanding people come from all different backgrounds, and we’re always interested in meeting talented people! Therefore, we do not require any particular credential or experience. If our work seems exciting to you, and you feel that you could excel in this position, we’d love to hear from you. That said, most successful candidates will fit the following profile, which reflects both our technical needs and team culture:

• Pursuing a bachelor’s degree or higher with relevant classwork or internships in Machine Learning

• Experience with advanced machine learning methods

• Statistical knowledge, intuition, and experience modeling real data

• Expertise in Python and Python-based ML frameworks (e.g., PyTorch or TensorFlow)

• Demonstrated effective coding, documentation, and communication habits

• Strong communication skills and the ability to effectively express even complicated methods and results to a broad, often non-technical, audience

We are an equal opportunity employer that welcomes future Kenshins with all experiences and perspectives. Kensho is headquartered in Cambridge, MA, with an additional office location in New York City. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.