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SquareYards
Generative AI Engineer | Artificial Intelligence | Mumbai
SquareYards
Mumbai•On-site•1-4 Yrs•Jun 22
Job description
Overview
One of our AI products built by us last year is now used by 9 million users every month!
Responsibilities
- Ideate, Design, Develop, and Implement: Create end-to-end Generative AI, Computer Vision and Audio Processing pipelines and models, including data processing, model fine-tuning, evaluation, and deployment for real-estate & fintech applications.
- LLM Application Development: Architect and build sophisticated AI solutions using frameworks like BAML, LlamaIndex, and the Hugging Face ecosystem. Apply knowledge of advanced techniques like Retrieval-Augmented Generation (RAG) and agentic systems.
- Vector Embeddings & Databases: Implement multimodal vector embedding strategies and manage vector databases for efficient similarity search and information retrieval.
- Model & Platform Ownership: Take ownership of leveraging and managing AI platforms and APIs such as Gemini API, OpenAI, Anthropic, Groq, and open-source models.
- Cross-Functional Collaboration: Work closely with product managers and software engineers to integrate AI capabilities into user-facing products and internal systems.
- Business Alignment: Collaborate effectively with Business teams to understand requirements, translate needs into technical specifications, and demonstrate the value of AI solutions.
- Continuous Learning & Innovation: Stay abreast of the rapidly evolving AI landscape, evaluate emerging models, tools, and techniques, and proactively apply them to drive innovation.
- Documentation & Best Practices: Maintain comprehensive documentation for AI models, pipelines, experiments, and deployment processes. Adhere to MLOps best practices.
Nice to have
- You have a live model of a Gen AI product that you've made.
- Contributions to open-source AI projects.
Education
- Programming: Expert-level Python proficiency and strong experience with relevant libraries.
- Generative AI Stack:
- LLMs: Deep understanding and practical experience with various LLMs and their APIs.
- Vector Technologies: Proficiency in generating and utilizing vector embeddings; hands-on experience with vector databases like Pinecone.
- API Integration: Experience consuming and integrating APIs from major AI providers (OpenAI, Azure OpenAI, Anthropic, Groq, Gemini API, Vertex AI etc.).
- Problem-Solving: Excellent analytical and problem-solving abilities with meticulous attention to detail.
- Adaptability: Proven ability to learn quickly, work independently, and adapt to new technologies and research advancements in the AI field.
- Communication: Strong verbal and written communication skills, enabling effective collaboration with technical and non-technical stakeholders.