Founding ML Engineer (India)
About the role
Founding ML Engineer to own research and engineering behind Crustdata's core ML intelligence layer, focusing on web-scale, multilingual data processing, retrieval, and structured extraction. Build and ship models from paper to production (not MLOps).
Responsibilities
- Own the ML systems that turn messy, multilingual, web-scale data into structured intelligence
- Research, train, and ship models from paper to production
- Develop and improve retrieval systems, classifiers, and embedding models
- Handle multilingual data scenarios (English, French, German) and cross-language normalization
- Infer org charts and data relationships from raw data
- Detect technologies used by companies from unstructured signals
- Classify job changes (promotion, lateral move, demotion, etc.) across millions of transitions
- Map raw job titles to canonical titles, seniority levels, and job functions across languages
Qualifications
- 3+ years building and shipping ML models in production — NLP, information retrieval, or entity resolution
- Strong with transformer architectures — trained and fine-tuned encoder models
- Experience building and evaluating retrieval systems, classifiers, and embedding models
- Comfortable with contrastive learning, metric learning, and representation learning
- Experience using LLMs for structured extraction, classification, or data generation at scale
- Strong Python and PyTorch
- Founder mentality or interest in founding a company in future OR previous founder experience
- Not a MLOps role; able to go from research to production
Skills
Benefits
- Will sponsor visa
- Competitive compensation ₹7M - ₹18.5M INR
- Equity in the founding phase
- Opportunities to impact core platform and data at scale
- Collaborative startup environment with leadership to shape ML roadmap

About Crustdata
Real-time B2B data via simple APIs
Crustdata provides live company and people data via APIs and full dataset delivery. We make hard to get data easy to use at scale. We have developed technology that allows us to pipe in live data from over a dozen different data sources and deliver this data instantly to our customers. We serve use cases like: automatic pipeline building, pipeline prioritization, champion watching, company and people triggers for sales and marketing automation, investment deal sourcing Our goal is index all the important data on the web and deliver it to customers in an easy-to-use way.
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