Build & Experiment
: 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.

What we're Looking for

2–6 years of experience as a
Data Scientist / ML Engineer
(startup or product environment a plus).
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 such as Pinecone, Weaviate, or FAISS).
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—able to turn data into insights and insights into product decisions.
Experience with
LLM evaluation frameworks
or prompt engineering.
Familiarity with
data visualization
(e.g., Plotly, D3.js, Tableau).
Experience working in
early-stage startups
or
venture building environments
.

Why work with us?

Build
real-world AI products
used across multiple ventures, not just prototypes.
Work in a
fast-moving, collaborative, high-trust environment
.
Collaborate directly with
founders, engineers, and creators
.
Help shape the future of
applied AI in India and beyond
.

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