AI Product Developer

2 days ago


Kota, Rajasthan, India beBeeData Full time ₹ 1,50,00,000 - ₹ 2,00,00,000
Job Opportunity

We are building intelligent systems and AI-powered tools that help ventures scale faster, smarter, and more efficiently.

Our goal is to re-imagine how products are designed, deployed, and adopted across industries.

As a key member of our team, you will work at the intersection of data, machine learning, and product development. Your role will involve experimentation, turning messy data into insights, and seeing your models power real products in the wild.

Key Responsibilities
  • Model Development: Develop machine learning models and data-driven features—recommendation systems, natural language processing (NLP), generative AI, and predictive analytics.
  • Data Engineering & Analysis: Collect, clean, and analyze structured + unstructured data to uncover insights and support product decisions.
  • Prototype to Production: Rapidly test ideas in notebooks, then work with engineers to productionize models using MLOps practices.
  • Measure & Iterate: Design experiments (A/B tests, evaluation pipelines), define success metrics, and continuously improve model performance.
  • Collaborate Cross-Functionally: Partner with product managers, designers, and engineers to ensure data and AI capabilities directly support real-world use cases.
Requirements
  • 2–6 years of experience as a Data Scientist / ML Engineer.
  • Strong programming skills in Python; comfort with libraries like Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow, or Hugging Face.
  • Experience with data pipelines and storage (SQL, NoSQL, or vector databases).
  • Understanding of retrieval-augmented generation (RAG) and generative AI techniques is a plus.
  • Familiarity with MLOps, model deployment, and monitoring (Docker, Kubernetes, cloud platforms).
  • Strong analytical and communication skills.
  • Experience working in early-stage startups or venture building environments.
Why Join Our Team?
  • Build real-world AI products used across multiple ventures.
  • Work in a fast-moving, collaborative, high-trust environment.
  • Collaborate directly with founders, engineers, and creators.
  • Help shape the future of applied AI.


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