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  • Machine Learning Engineer - 2025 Grad

    S&P Global (New York, NY)



    Apply Now

    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 upcoming graduates 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.

     

    Kensho is committed to offering hybrid and flexible work arrangements that balance both in-office and remote work. This approach allows us to accommodate personal circumstances while ensuring strong collaboration and productivity.

     

    Kensho states that the anticipated base salary range for the position is 120k - 140k. 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. This opportunity is based in Cambridge, MA or New York City.

    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:

    + Work with unique 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.

    + Actively participate in the ML model 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.

    + 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:

     

    + Bachelor's degree or higher with relevant classwork or internships in Machine Learning

    + Experience with advanced machine learning methods

    + Strong 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 ability to effectively express complicated methods and results to a broad, often non-technical, audience

    + [optionally] Publication(s) in top-tier journals and conferences in the ML domain

    At Kensho, we pride ourselves on providing top-of-market benefits, including:

    +  Medical, Dental, and Vision insurance

    + 100% company paid premiums

    + Unlimited Paid Time Off

    + 26 weeks of 100% paid Parental Leave (paternity and maternity)

    + 401(k) plan with 6% employer matching

    + Generous company matching on donations to non-profit charities

    + Up to $20,000 tuition assistance toward degree programs, plus up to $4,000/year for ongoing professional education such as industry conferences

    + Plentiful snacks, drinks, and regularly catered lunches

    + Dog-friendly office (CAM office)

    + Bike sharing program memberships

    + Compassion leave and elder care leave

    + Mentoring and additional learning opportunities

    + Opportunity to expand professional network and participate in conferences and events

    Recruitment Fraud Alert:

    If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to [email protected] . S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, “pre-employment training” or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity here (https://www.spglobal.com/content/dam/spglobal/corporate/en/documents/careers/Corp\_0525-Recruitment-Fraud-Alert.pdf) .

     

    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.

     

    **Job ID:** 308970

    **Posted On:** 2025-06-27

    **Location:** Cambridge, Massachusetts, United States

     


    Apply Now



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