Note: This is a remote role with occasional office visits. Candidates from Mumbai or Pune will be preferred
About The Company
Operating at the intersection of
Artificial Intelligence, Cloud Infrastructure, and Enterprise SaaS
, we create data-driven products that power decision-making for Fortune 500 companies and high-growth tech firms. Our multidisciplinary teams ship production-grade
generative-AI and Retrieval-Augmented Generation (RAG)
solutions that transform telecom, finance, retail, and healthcare workflows—without compromising on scale, security, or speed.Role & Responsibilities
- Build & ship LLM/RAG solutions: design, train, and productionize advanced ML and generative-AI models (GPT-family, T5) that unlock new product capabilities.
- Own data architecture: craft schemas, ETL/ELT pipelines, and governance processes to guarantee high-quality, compliant training data on AWS.
- End-to-end MLOps: implement CI/CD, observability, and automated testing (Robot Framework, JMeter, XRAY) for reliable model releases.
- Optimize retrieval systems: engineer vector indices, semantic search, and knowledge-graph integrations that deliver low-latency, high-relevance results.
- Cross-functional leadership: translate business problems into measurable ML solutions, mentor junior scientists, and drive sprint ceremonies.
- Documentation & knowledge-sharing: publish best practices and lead internal workshops to scale AI literacy across the organization.
Skills & Qualifications
- Must-Have – Technical Depth: 6 + years building ML pipelines in Python; expert in feature engineering, evaluation, and AWS services (SageMaker, Bedrock, Lambda).
- Must-Have – Generative AI & RAG: proven track record shipping LLM apps with LangChain or similar, vector databases, and synthetic-data augmentation.
- Must-Have – Data Governance: hands-on experience with metadata, lineage, data-cataloging, and knowledge-graph design (RDF/OWL/SPARQL).
- Must-Have – MLOps & QA: fluency in containerization, CI/CD, and performance testing; ability to embed automation within GitLab-based workflows.
- Preferred – Domain Expertise: background in telecom or large-scale B2B platforms where NLP and retrieval quality are mission-critical.
- Preferred – Full-Stack & Scripting: familiarity with Angular or modern JS for rapid prototyping plus shell scripting for orchestration.
Benefits & Culture Highlights
- High-impact ownership: green-field autonomy to lead flagship generative-AI initiatives used by millions.
- Flex-first workplace: hybrid schedule, generous learning stipend, and dedicated cloud credits for experimentation.
- Inclusive, data-driven culture: celebrate research publications, OSS contributions, and diverse perspectives while solving hard problems together.
Skills: data,modern javascript,cloud,vector databases,angular,pipelines,ci,containerization,ml,aws,langchain,shell scripting,mlops,performance testing,knowledge-graph design (rdf/owl/sparql),feature engineering,ci/cd,python,aws services (sagemaker, bedrock, lambda),synthetic-data augmentation,generative ai,data-cataloging,metadata management,lineage,data governance
