Applied Scientist – Machine Learning

Role: Applied Scientist – Machine LearningFunction: Machine Learning / Applied ScienceLocation: Gurugram, India (Onsite)Type: Full-timeIndustry: Information Technology & Services, Computer Software, Industrial AutomationAbout CompanyAn industrial AI startup using Causal AI to help semiconductor and manufacturing companies find and fix the root causes of equipment and process failures. The company's Causal Intelligence Platform integrates multimodal factory data with explainable causal reasoning — going beyond surface-level correlations.It is seed-funded at $3M and backed by Capria Ventures and Endiya Partners. The team of 19 engineers brings deep expertise in semiconductor defect analysis, causal reasoning, and graph intelligence.The company operates with high agency, low bureaucracy, and a real-world-first culture. Solutions are built for explainability and deployed in secure, private environments — co-developed closely with customers.Position OverviewThis role sits at the intersection of applied ML research and production engineering, directly shaping the scientific direction of the company's Causal Intelligence Platform. The Applied Scientist will design and ship ML systems that turn chaotic multimodal industrial data — time-series, logs, waveforms, and documents — into reliable root-cause insights used by engineers at semiconductor fabs, utilities, and advanced manufacturing lines. The work spans LLM/RAG pipelines, time-series diagnostics, and scalable multimodal ingestion, with direct influence on product architecture and customer outcomes.Role & ResponsibilitiesDesign and develop ML algorithms for time-series, log, and waveform-based diagnostics across industrial datasetsBuild and optimize LLM/RAG pipelines including structured extraction, hybrid search, and domain-specific reasoningArchitect scalable multimodal ingestion frameworks covering documents, logs, sensor streams, alarms, and imagesProductize ML models in collaboration with engineering teams into reliable, customer-facing systemsDefine use cases, benchmarks, and evaluation frameworks with product teamsLead ML projects end-to-end and contribute to patents, technical architecture documents, and research publicationsPrototype aggressively, iterate on real customer feedback, and own outcomes from research through deploymentMust Have CriteriaBS/MS/PhD in AI/ML, Computer Science, Electrical Engineering, Applied Mathematics, or a related field2–5 years of hands-on experience in ML research or applied ML rolesStrong Python programming skills with a track record of building and scaling ML systems in productionHands-on experience with LLMs, RAG architecture, prompt engineering, or fine-tuningDemonstrated experience with time-series modeling, anomaly detection, or statistical signal processingProven ability to take ML projects from experimentation to deployed, customer-facing systemsNice to HaveStartup or early-stage product-building experienceBackground in semiconductor, manufacturing, battery systems, or industrial data domainsExperience building agents or autonomous reasoning systemsContributions to open-source ML or LLM toolingDirect experience working with customers or field engineering teamsWhat We OfferFrontier ML problems on multimodal industrial data with real, measurable customer impactHigh agency and direct influence on product and scientific direction at a seed-stage companyESOPs and rapid growth opportunities