Job Title

Job Title: Data Scientist Location:Remote Team:AI & Data Science Engagement:Full-Time Industry:Real Estate Tech / Smart Infrastructure Seniority:Mid to Senior-LevelAbout Us We are a stealth-mode startup at the forefront of real estate transformation — where physical infrastructure meets digital intelligence. We’re on a mission to createautonomous, data-driven, and adaptive living environmentsby embedding AI across the value chain of urban development. Our work spansintelligent agent ecosystems ,generative AI platforms , andmulti-modal ML solutions . As we scale our AI capabilities, we’re seeking aData Scientistwho not only brings modeling expertise but also understands modern AI engineering stacks likeLangChain ,transformers , andMCP-based orchestration .Job Objective This role combines classic data science modeling with modern AI engineering. You will help design, prototype, and productionize ML/AI pipelines across various domains — from predictive modeling to conversational AI agents. Your work will directly impact strategic decisions, operational automation, and customer experience across the product ecosystem.Key Responsibilities Data Exploration & Business Contextualization Perform advanced exploratory data analysis (EDA) to uncover insights, detect anomalies, and guide modeling strategy. Collaborate with product and domain leads to scope high-impact ML use cases and identify key success metrics. Machine Learning & Generative AI Development Design and implement predictive and generative models using: Regression, classification, clustering LSTM, Transformers (e.g., BERT, T5, GPT-based models) Fine-tuning and prompt engineering for LLMs Build retrieval-augmented generation (RAG) pipelines usingLangChainor equivalent agentic frameworks. ⚙️ AI Engineering & MCP Server Design Develop and deployMCP (Model Context Protocol) serversthat coordinate AI tools, prompts, and agent workflows. Implement tool-calling, function-chaining, and human-in-the-loop validation in agentic systems. Build scalable APIs that serve model outputs, streaming responses, or vector search results from internal knowledge bases. ML Lifecycle & MLOps Own full ML pipeline — from experimentation to deployment — usingVertex AI ,Databricks , orAWS SageMaker . Integrate model monitoring, feedback loops, and rollback strategies into production. Optimization & Experimentation Tune hyperparameters, optimize latency, and reduce model drift using continuous evaluation and A/B testing. Establish benchmarks and experiment tracking for various modeling approaches. Communication & Reporting Translate technical insights into actionable business recommendations. Present results to executives and cross-functional teams using clear, visual narratives and interpretable metrics.Qualifications & Experience Education Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, Applied Mathematics, or related fields. Experience Minimum 5 years of professional experience in data science, machine learning, or AI research & development. Strong exposure to bothML modelingandLLM-driven AI application development .Behavioral Competencies Strong problem-solving and structured thinking for ambiguous challenges. Ability to designscalable AI architectures , not just throw models at data. Comfortable working across code, cloud, and concept — from model design to business impact. Team player with mentoring capability for junior engineers or data scientists.Why Join Us? Build state-of-the-artagentic AI solutionsin a fast-growing stealth startup. Work on complexmulti-agent LLM orchestrationproblems rarely solved in the wild. Join a hands-on, high-performance culture withdirect influence on product and platform decisions . Contribute to real-world AI that redefines how people interact with urban environments.Application Process Shortlisted candidates will go through: Technical Deep-Dive Interview System Design or Agent Architecture Case