Senior Data Scientist - Ai Infra

Job Description

As an experienced software engineer, data scientist, or applied ML professional with 8 years of experience, you will have a strong computer science foundation. Your role will involve managing applied AI/ML or Data Science teams for 2-3 years and demonstrating a proven track record of shipping and operating production AI/ML systems in a product or platform environment. It is essential to have a background in data science, applied ML, or ML engineering, as analytics-only profiles will not be a fit for this position.Key Responsibilities:- Demonstrating strong system design skills and comfort in making architectural decisions.- Operating effectively in fast-moving, ambiguous, growth-stage environments.- Collaborating excellently and managing stakeholders effectively.- Utilizing experience with LLMs, NLP, document intelligence, or retrieval-augmented generation (RAG).- Building shared AI platforms or internal ML infrastructure.- Having prior experience in B2B SaaS, fintech, or workflow-heavy products.- Exposure to AI systems at scale with cost and performance constraints.Qualifications Required:- 8 years of total experience in software engineering, data science, or applied ML.- Possession of a CS degree or equivalent practical experience.- Experience managing applied AI/ML or Data Science teams for 2-3 years.- Proven track record of shipping and operating production AI/ML systems in a product or platform environment.- Background in data science, applied ML, or ML engineering.- Strong system design skills and comfort making architectural decisions.- Ability to operate effectively in fast-moving, ambiguous, growth-stage environments.- Excellent collaboration and stakeholder management skills.- Experience with LLMs, NLP, document intelligence, or retrieval-augmented generation (RAG).- Experience building shared AI platforms or internal ML infrastructure.- Prior experience in B2B SaaS, fintech, or workflow-heavy products.- Exposure to AI systems at scale with cost and performance constraints. As an experienced software engineer, data scientist, or applied ML professional with 8 years of experience, you will have a strong computer science foundation. Your role will involve managing applied AI/ML or Data Science teams for 2-3 years and demonstrating a proven track record of shipping and operating production AI/ML systems in a product or platform environment. It is essential to have a background in data science, applied ML, or ML engineering, as analytics-only profiles will not be a fit for this position.Key Responsibilities:- Demonstrating strong system design skills and comfort in making architectural decisions.- Operating effectively in fast-moving, ambiguous, growth-stage environments.- Collaborating excellently and managing stakeholders effectively.- Utilizing experience with LLMs, NLP, document intelligence, or retrieval-augmented generation (RAG).- Building shared AI platforms or internal ML infrastructure.- Having prior experience in B2B SaaS, fintech, or workflow-heavy products.- Exposure to AI systems at scale with cost and performance constraints.Qualifications Required:- 8 years of total experience in software engineering, data science, or applied ML.- Possession of a CS degree or equivalent practical experience.- Experience managing applied AI/ML or Data Science teams for 2-3 years.- Proven track record of shipping and operating production AI/ML systems in a product or platform environment.- Background in data science, applied ML, or ML engineering.- Strong system design skills and comfort making architectural decisions.- Ability to operate effectively in fast-moving, ambiguous, growth-stage environments.- Excellent collaboration and stakeholder management skills.- Experience with LLMs, NLP, document intelligence, or retrieval-augmented generation (RAG).- Experience building shared AI platforms or internal ML infrastructure.- Prior experience in B2B SaaS, fintech, or workflow-heavy products.- Exposure to AI systems at scale with cost and performance constraints.

Keyskills :
software engineeringdata sciencecomputer scienceData Sciencesystem designNLPfintechapplied MLAIMLLLMsdocument intelligenceretrievalaugmented generationAI platformsML infrastructure