Machine Learning Engineer II

Posted 3 Days Ago
2 Locations
In-Office
140K-180K Annually
Mid level
Fintech • Analytics
The Role
Build and productionize agentic AI systems that retrieve and synthesize structured and unstructured financial data. Work across the ML lifecycle: experiment, deploy, monitor, and evaluate agents and retrieval methods. Collaborate with data, product, design, and MLOps teams to create scalable, robust solutions that connect data to business insights.
Summary Generated by Built In

Kensho is S&P Global’s hub for AI innovation and transformation. With expertise in machine learning, natural language processing, and data discovery, we develop and deploy novel solutions to innovate and drive progress at S&P Global and its customers worldwide. Kensho's solutions and research focus on business and financial generative AI applications, agents, data retrieval APIs, data extraction, and much more.

At Kensho, we hire talented people and give them the autonomy and support needed to build amazing technology and products. We collaborate using our teammates' diverse perspectives to solve hard problems. Our communication with one another is open, honest, and efficient. We dedicate time and resources to explore new ideas, but always rooted in engineering best practices. As a result, we can innovate rapidly to produce technology that is scalable, robust, and useful.

The Machine Learning (ML) Team at Kensho is redefining how powerful financial data fuels the next generation of data-driven AI workflows. 

We are fundamentally shaping how AI-aided human interactions with complex financial data are facilitated. Our team focuses on creating agentic experiences that enable complex report generation, deep research workflows, and novel user journeys - all with robust evaluation. We are also at the forefront of developing novel methods for retrieving and synthesizing both structured (tabular data from relational databases) and unstructured data using natural language interfaces.
Our solutions are integrated into multiple S&P Global and third-party platforms, allowing our clients (1, 2) to leverage powerful financial data in ways that drive insights and support their strategic objectives.

We are seeking a mid-level Machine Learning Engineer to join our team and help shape the future of Agentic AI systems. This is a hands-on, full-lifecycle (from experimentation to productionization) ML role with a strong emphasis on developing and orchestrating intelligent agent frameworks, designing novel and robust retrieval methods, validating AI-generated outputs, and building scalable systems that connect data to actionable insights.

If you are passionate about building the next wave of AI-driven products, thrive in a collaborative, fast-paced environment, and are eager to push the boundaries of what’s possible with data and intelligent agents, we would love to hear from you!
Kensho states that the anticipated base salary range for the position is 140k - 180k. 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:

  • Solve unique challenges in agentic design and LLM orchestration, including context engineering, data access patterns, memory management, and evaluation of agent performance to ensure they meet user needs effectively.

  • 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 Agentic Systems.

  • Leverage unique proprietary unstructured and structured datasets, applying advanced NLP techniques to extract insights and build solutions that drive business value.

  • Work closely with Data, Product, Design, and Engineering teams to design and develop Agents to 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.

  • 3+ years of significant, hands-on industry experience with machine learning, natural language processing (NLP), and information retrieval systems, with a strong focus on practical applications.

  • Experience with all stages of the ML life-cycle including designing and experimenting to deploying and maintaining production systems.

  • Strong proficiency in Python, with a solid understanding of best practices in software development.

  • Experience working with machine learning libraries and frameworks for agent orchestration, such as LangGraph, pydanticAI, etc.

  • Experience in agentic design, understanding user interactions, and evaluating agent performance to enhance user experiences.

  • 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.

Technologies & Tools We Use:

  • Agentic systems: Agentic Orchestration, Deep Research, Information Retrieval, Semantic Search, LLM code generation, LLM tool utilization, Textual RAG systems

  • Core ML/AI: LangGraph, Transformers, HuggingFace, LightGBM, PyTorch, SKLearn, XGBoost

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

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

  • Deployment & MLOps: Arize, Airflow, AWS, DeepSpeed, Docker, Grafana, Jenkins, LangFuse, LiteLLM, Ray, vLLM

  • Prototyping & Development: Claude Code, FastAPI, Streamlit, Gradio

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.

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.

Skills Required

  • Bachelor's degree or higher in Computer Science, Engineering, or a related field
  • 3+ years of hands-on industry experience with machine learning, NLP, and information retrieval systems
  • Experience with all stages of the ML lifecycle, including experimentation, deployment, and production maintenance
  • Strong proficiency in Python and software development best practices
  • Experience with agent orchestration frameworks (e.g., LangGraph, pydanticAI) and agentic design
  • Experience designing retrieval methods, semantic search, and working with structured and unstructured datasets
  • Demonstrated coding, documentation, collaboration, and communication skills
  • Strong problem-solving skills and ability to adapt in a fast-paced environment

S&P Global Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about S&P Global and has not been reviewed or approved by S&P Global.

  • Parental & Family Support Policies include extended paid parental leave globally plus additional paid care and compassion leave, indicating strong support for families. Family-focused resources and flexibility reinforce a family-friendly approach.
  • Leave & Time Off Breadth Time off options are broad, including flexible recharge time and companywide wellness days, with additional volunteer time off highlighted. Hybrid and flexible work arrangements further complement time-off breadth.
  • Wellbeing & Lifestyle Benefits Wellbeing programs include 24/7 mental-health support, wellness reimbursements, and resources for employees and family members. Education and financial-wellness support such as tuition reimbursement and student-loan contributions expand the lifestyle offering.

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The Company
HQ: New York, NY
26,747 Employees

What We Do

At S&P Global, we accelerate progress by delivering essential intelligence that unlocks opportunity and fosters growth. For 160 years, our insights and data have helped countries, companies and investors make decisions with conviction. We’re the world’s foremost provider of transparent and independent ratings, benchmarks, analytics, data, research, commentary and ESG solution. Our divisions include: • S&P Global Ratings, which provides credit ratings, research and insights essential to driving growth and transparency. • S&P Global Market Intelligence, which provides insights into companies, markets and data so that business and financial decisions can be made with conviction. • S&P Dow Jones Indices, the world’s largest resource for iconic and innovative indices, which helps investors pinpoint global opportunities. • S&P Global Platts, which equips customers to identify and seize opportunities in energy and commodities, stimulating business growth and market transparency.

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