Machine Learning Engineer II - Kensho Technologies : Job Details

Join to apply for the Machine Learning Engineer II role at Kensho Technologies

Continue with Google Continue with Google

Join to apply for the Machine Learning Engineer II role at Kensho Technologies

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.The Vector Team at Kensho is focused on designing and deploying production-grade machine learning systems that power our next-generation retrieval-augmented generation (RAG) pipelines. We specialize in building robust retrieval systems, scalable embedding infrastructure, and tightly integrated LLM pipelines that leverage unstructured data sources.Our mission is to make complex unstructured data easily discoverable and actionable by building intelligent, retrieval-driven systems that enhance enterprise search, question answering, deep research, report generation, and knowledge discovery experiences across S&P Global platforms.We are seeking a mid-level Machine Learning Engineer to help develop and scale RAG systems across the company. This is a hands-on, full-lifecycle ML role with a strong emphasis on retrieval models, LLM orchestration, and system-level thinking.Kensho states that the anticipated base salary range for the position is 150k - 190k. 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

• Design and implement end-to-end RAG pipelines that integrate embedding models, vector databases, and data retrieval agents
• Build and optimize retrieval systems over large-scale proprietary datasets using advanced embedding techniques
• Develop LLM-based solutions that orchestrate retrieval, generation, and ranking to deliver high-quality, context-aware responses
• Investigate and solve challenges in vector search, chunking and indexing strategies, and GraphRAG
• 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

Who 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), information retrieval systems and large-scale text processing, including designing, shipping, and maintaining production systems
• Strong programming skills in Python, with a working knowledge of data processing tools and ML frameworks such as PyTorch, Transformers, and HuggingFace
• Experience working with machine learning libraries/frameworks for Large Language Model (LLM) orchestration, such as Langchain, LLamaIndex, etc
• Proven experience building ML pipelines for data processing, training, inference, maintenance, evaluation, versioning, and experimentation
• Experience working with vector databases (e.g., PGVector, OpenSearch, Pinecone) and understanding of similarity search techniques and vector indexing algorithms
• 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 We Love

• ML: PyTorch, Transformers, HuggingFace, LangChain, LlamaIndex
• Tools/Toolkits: LabelBox, Weights & Biases, OpenSearch, PGVector, LiteLLM
• Techniques: RAG, Prompt Engineering, Information Retrieval, Data Embedding
• Deployment: Airflow, Docker, Kubernetes, Jenkins, AWS

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 AlertIf 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.Job ID: 317450Posted On: 2025-06-26Location: Cambridge, Massachusetts, United States

Seniority level

• Seniority levelMid-Senior level

Employment type

• Employment typeFull-time

Job function

• Job functionEngineering and Information Technology
• IndustriesSoftware Development

Referrals increase your chances of interviewing at Kensho Technologies by 2x

Sign in to set job alerts for “Machine Learning Engineer” roles.

Continue with Google Continue with Google

Continue with Google Continue with Google

New York, NY $150,000 - $220,000 1 day ago

Machine Learning Engineer I - Windreich Department of Artificial Intelligence & Human Health

New York, NY $109,000 - $163,695 2 days ago

New York, NY $100,000 - $250,000 2 weeks ago

New York, NY $120,000 - $160,000 1 week ago

New York, NY $180,000 - $290,000 2 months ago

Machine Learning Engineer, Personalization

New York, NY $136,878 - $195,540 4 days ago

New York, NY$160,000.00-$280,000.001 year ago

New York, NY$180,000.00-$210,000.003 days ago

New York, NY$220,000.00-$260,000.003 days ago

New York, NY$140,000.00-$200,000.008 months ago

New York, NY$187,000.00-$270,000.002 weeks ago

New York, NY$140,000.00-$200,000.008 months ago

Machine Learning Engineer I - Windreich Department of Artificial Intelligence & Human Health

New York, NY$109,000.00-$163,695.002 days ago

New York, NY$128,000.00-$160,000.003 days ago

New York, NY$150,000.00-$200,000.001 month ago

New York, NY$180,000.00-$240,000.002 months ago

Machine Learning Engineer, GenRecs, Personalization

New York, NY$138,250.00-$197,500.004 days ago

New York, NY$175,000.00-$265,000.003 weeks ago

New York, NY$110,000.00-$250,000.002 months ago

Machine Learning Engineer, GenAI Applied ML

New York, NY$176,000.00-$220,000.002 weeks ago

New York, NY$140,000.00-$140,000.002 weeks ago

Senior Software Engineer I, Machine Learning

Brooklyn, NY$183,000.00-$216,000.001 week ago

New York, NY$190,000.00-$285,000.005 days ago

New York, NY$130,000.00-$180,000.005 months ago

Software Engineer II | Full Stack Developer

New York, NY $164,000 - $198,000 1 day ago

New York, NY $132,000 - $154,000 2 weeks ago

Staff Applied Scientist I, Machine Learning Recommendations

Brooklyn, NY $218,000 - $257,000 2 weeks ago

We're unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.

#J-18808-Ljbffr