Data Science
Description
A high-profile, globally distributed Deep Tech startup currently operating in Stealth Mode, engineering foundational Enterprise AI platforms for next-generation organizational intelligence, knowledge discovery, and LLM-driven reasoning.
Backed by tens of millions of dollars from premier Tier-1 global venture capital firms, the company operates with an intimate, world-class team of approximately 20 researchers and engineers distributed worldwide.
The platform is architected to fundamentally transform how modern enterprises structure proprietary knowledge, automate complex cognitive workflows, and derive actionable value from AI.
The company offers a rare opportunity to join the foundational AI research and engineering core, collaborating directly with executive scientific leadership (CSO) to deploy advanced models into production.
Role Description-
- Serving as a Senior Machine Learning & Applied AI Scientist / Engineer, partnering directly with the Chief Science Officer (CSO) and Core Engineering squads.
- Holding complete technical ownership over the research, design, implementation, and deployment of production-grade Machine Learning and LLM capabilities.
- Designing and engineering state-of-the-art architectures across Enterprise Search, Information Retrieval (IR), Recommendation Systems, and Autonomous AI Agents.
- Developing and optimizing advanced Retrieval-Augmented Generation (RAG) systems, domain-specific embedding spaces, and vector retrieval pipelines.
- Architecting robust Evaluation Frameworks, offline/online experimentation suites, statistical modeling, and causal inference topologies to benchmark model reliability in enterprise settings.
- Building resilient, scalable Data & ML Pipelines from data ingestion and preparation to continuous model fine-tuning and inference serving in Python and SQL.
- Driving deep-dive quantitative analyses to measure the direct product and business impact of deployed AI models.
Requirements-
- B.Sc. / M.Sc. in Computer Science, Mathematics, Statistics, Data Science, or a closely related quantitative field OR equivalent hands-on technological experience from an elite IDF unit – Mandatory
- At least 5 years of proven professional experience in Data Science, Applied Machine Learning, or AI Engineering – Mandatory
- Proven track record deploying and maintaining Machine Learning / Deep Learning models within large-scale, mission-critical Production environments – Mandatory
- Advanced programming and data manipulation expertise in Python and SQL – Mandatory
- Proven hands-on experience designing and operating robust, scalable Data and ML pipelines – Mandatory
- Deep working familiarity and hands-on experience with modern Generative AI paradigms: LLMs, Embeddings, Information Retrieval systems, RAG, or AI Agents – Mandatory
- Strong mathematical and statistical foundations, experimental design mindset, and fluent professional communication in English (written and verbal) – Mandatory
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