{"id":103475,"url":"https://alion.io/job/sp-global-machine-learning-engineer-ii-2","title":"Machine Learning Engineer II","company":{"id":8679,"name":"S&P Global","domain":"spglobal.com","url":"https://alion.io/company/spglobal","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":85,"open_postings":50,"ghost_share":0.06,"stale_share":0.32,"repost_share":0.2,"time_to_fill_p50_days":22,"computed_at":"2026-10-16T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States","Cambridge, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":123000,"max_usd":231000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":451},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AI Agents","optional":false},{"name":"Airflow","optional":false},{"name":"Amazon S3","optional":false},{"name":"Arize Phoenix","optional":false},{"name":"AWS","optional":false},{"name":"Claude","optional":false},{"name":"Claude Code","optional":false},{"name":"Context Engineering","optional":false},{"name":"DeepSpeed","optional":false},{"name":"Docker","optional":false},{"name":"DVC","optional":false},{"name":"FastAPI","optional":false},{"name":"Gradio","optional":false},{"name":"Grafana","optional":false},{"name":"Jenkins","optional":false},{"name":"LangChain","optional":false},{"name":"Langfuse","optional":false},{"name":"LangGraph","optional":false},{"name":"LiteLLM","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"OpenSearch","optional":false},{"name":"pgvector","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Pydantic AI","optional":false},{"name":"Python","optional":false},{"name":"Ray","optional":false},{"name":"SQLite","optional":false},{"name":"Streamlit","optional":false},{"name":"vLLM","optional":false},{"name":"Hugging Face","optional":true},{"name":"LightGBM","optional":true},{"name":"Matplotlib","optional":true},{"name":"Pandas","optional":true},{"name":"PyTorch","optional":true},{"name":"RAG","optional":true},{"name":"Semantic Search","optional":true},{"name":"Semantic Search","optional":true},{"name":"Spark","optional":true},{"name":"Transformers","optional":true},{"name":"Weights & Biases","optional":true},{"name":"XGBoost","optional":true}],"status":"live","first_seen_at":"2026-08-13T00:00:00Z","employer_posted_date":"2026-08-13","last_verified_at":"2026-10-16T02:32:37Z","board_verified":true,"closed_at":null,"days_open":64,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":64},"description":"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.\nAt 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.\nThe Machine Learning (ML) Team at Kensho is redefining how powerful financial data fuels the next generation of data-driven AI workflows.\nWe 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.\nOur 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.\nWe 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.\nIf 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!\nKensho 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.\nWhat You’ll Do:\nSolve 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.\n\nParticipate 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.\n\nLeverage unique proprietary unstructured and structured datasets, applying advanced NLP techniques to extract insights and build solutions that drive business value.\n\nWork closely with Data, Product, Design, and Engineering teams to design and develop Agents to enhance user experiences and meet business objectives.\n\nCollaborate closely with the ML Operations team to create automated solutions for managing the entire ML systems lifecycle, from initial technical design to seamless implementation.\n\nWhat You'll Need:\nBachelor's degree or higher in Computer Science, Engineering, or a related field.\n\n3+ 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.\n\nExperience with all stages of the ML life-cycle including designing and experimenting to deploying and maintaining production systems.\n\nStrong proficiency in Python, with a solid understanding of best practices in software development.\n\nExperience working with machine learning libraries and frameworks for agent orchestration, such as LangGraph, pydanticAI, etc.\n\nExperience in agentic design, understanding user interactions, and evaluating agent performance to enhance user experiences.\n\nDemonstrated effective coding, documentation, collaboration, and communication habits.\n\nStrong problem-solving skills and a proactive approach to addressing challenges.\n\nAbility to adapt to a fast-paced and dynamic work environment.\n\nTechnologies & Tools We Use:\nAgentic systems:Agentic Orchestration, Deep Research, Information Retrieval, Semantic Search, LLM code generation, LLM tool utilization, Textual RAG systems\n\nCore ML/AI:LangGraph, Transformers, HuggingFace, LightGBM, PyTorch, SKLearn, XGBoost\n\nData Exploration & Visualization:Jupyter, Matplotlib, Pandas, Weights & Biases, Langfuse\n\nData Management & Storage:Apache Spark, AWS Athena, DVC, LabelBox, OpenSearch, Postgres/Pgvector, S3, SQLite\n\nDeployment & MLOps:Arize, Airflow, AWS, DeepSpeed, Docker, Grafana, Jenkins, LangFuse, LiteLLM, Ray, vLLM\n\nPrototyping & Development: Claude Code, FastAPI, Streamlit, Gradio\n\nAt Kensho, we pride ourselves on providing top-of-market benefits, including:\nMedical, Dental, and Vision insurance\n\n100% company paid premiums\n\nUnlimited Paid Time Off\n\n26 weeks of 100% paid Parental Leave (paternity and maternity)\n\n401(k) plan with 6% employer matching\n\nGenerous company matching on donations to non-profit charities\n\nUp to $20,000 tuition assistance toward degree programs, plus up to $4,000/year for ongoing professional education such as industry conferences\n\nPlentiful snacks, drinks, and regularly catered lunches\n\nDog-friendly office (CAM office)\n\nBike sharing program memberships\n\nCompassion leave and elder care leave\n\nMentoring and additional learning opportunities\n\nOpportunity to expand professional network and participate in conferences and events\n\nRecruitment Fraud Alert:\nIf you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported . 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.\nWe 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. 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