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Salary
$21k – $63k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Junior · 1+ year exp
Overview
Company
Impact
Profile match
GeoIQ empowers business analysts to data scientists, to turn location data into business outcomes. Its platform and APIs offer insights on where things happen, why they happen and helps predict what will happen.

We are a growing team of 40+ innovators, led by a founding team with expertise in AI, data analytics, and product development. Our culture thrives on experimentation, rapid prototyping, and innovation, allowing AI engineers to directly shape intelligent products at scale.

Responsibilities:

  • Design and implement AI-driven solutions across domains such as LLMs, Generative AI, NLP, and Computer Vision.
  • Research, prototype, and evaluate state-of-the-art AI models and architectures for real-world applications.
  • Build retrieval-augmented generation (RAG) pipelines and integrate AI models into customer-facing products.
  • Work with engineers and product teams to embed AI capabilities into platforms and workflows.
  • Optimise AI models for accuracy, scalability, and production efficiency.
  • Stay up to date with advancements in Generative AI, foundation models, and applied AI frameworks.

Requirements:

  • Bachelor's/Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.
  • 1-2 years of experience in building and deploying AI applications.
  • Strong proficiency in Python and AI/ML libraries such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, and Scikit-learn.
  • Hands-on experience with LLMs, embeddings, prompt engineering, or fine-tuning foundation models.
  • Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes) is a plus.
  • Understanding of vector databases (Pinecone, Qdrant, Weaviate, FAISS) is desirable.
  • Strong problem-solving skills with the ability to translate business needs into applied AI solutions
  • Excellent communication and cross-team collaboration skills.

Preferred Qualifications:

  • Experience with Generative AI (LLMs, diffusion models, multimodal AI).
  • Familiarity with RAG, orchestration frameworks (LangChain, LlamaIndex, Haystack).
  • Exposure to MLOps/AI Ops practices and CI/CD pipelines for AI workflows.
  • Contributions to AI/ML open-source projects.
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