PythonAI Engineer – Supaboard.ai
Location: Bengaluru, India (On-site, 5 days a week)
Experience Level: 2–5 years
Compensation: ₹8 – ₹16 LPA
Tech Stack: Python, TypeScript, OpenAI/Anthropic APIs, Hugging Face, Vector DBs
Employment Type: Full-time, In-office
About Supaboard.ai
Supaboard.ai is building an intelligent data analytics platform powered by modern AI systems, enabling teams to transform their raw data into dashboards, insights, and automations—instantly.
We combine analytics, automation, and AI into a single powerful engine used by fast-growing teams.
We’re looking for an AI Engineer who loves working with models, fine-tuning, LLM orchestration, and building AI-driven features that scale.
Key Responsibilities
- Fine-tune open-source LLMs (e.g., Llama, Mistral, T5, Qwen) for internal use cases like text classification, summarization, extraction, and agent workflows.
- Develop, test, and optimize prompt engineering strategies for production use-cases.
- Build and maintain pipelines for training, evaluating, and deploying custom AI models.
- Integrate models with Supaboard’s backend using Python, TypeScript, and cloud-based AI platforms.
- Work with libraries like Hugging Face Transformers, LangChain, OpenAI, Gemini, Anthropic, and vector databases (Pinecone/Weaviate).
- Create high-accuracy evaluation datasets and design automated evaluation harnesses.
- Optimize performance, latency, and reliability of AI-powered features in production.
- Collaborate with product, engineering, and data teams to design and implement AI-driven product features.
Requirements
- Strong proficiency in Python (must) and basic experience with TypeScript (preferred).
- Solid understanding of LLMs, embeddings, tokenization, model architectures, and NLP pipelines.
- Prior experience fine-tuning or training open-source models using PyTorch, Hugging Face, or similar frameworks.
- Experience calling and orchestrating external LLM APIs (OpenAI, Anthropic, Google Gemini, etc.).
- Ability to design prompts, tune them, and create deterministic and reliable chains/flows.
- Hands-on experience with vector databases (Pinecone, Weaviate, Chroma) and retrieval pipelines.
- Familiarity with cloud environments (AWS/GCP) and deploying AI workloads.
- Good understanding of evaluation metrics and experiment tracking (W&B or similar).
- Strong debugging skills and an ownership-driven mindset.
Nice to Have
- Experience building agents, tool-calling workflows, and multi-model pipelines.
- Knowledge of distributed training, quantization (GGUF/GGML), or optimization techniques (LoRA, QLoRA, PEFT).
- Experience building AI-based features for data analytics or SaaS products.
- Familiarity with FastAPI or Node-based backend services.
Why Supaboard.ai?
- Build a core part of India’s next-gen AI analytics platform.
- Work with cutting-edge open-source AI models and real-world production workloads.
- Massive ownership, high impact, and a fast-paced startup environment.
- A culture that rewards learning, curiosity, and technical growth.
Shubham Vishwakarma
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