AI Researcher

3 days ago

Mumbai, India Weekday AI Full time

This role is for one of the Weekday's clients Salary range: Rs - Rs (ie INR 8-15 LPA)Min Experience: 2 years Location: Pune, Mumbai, Rajasthan, GUJRAT, Ahmedabad JobType: full-time Requirements What You’ll Do Explore Emerging AI Models: Continuously assess cutting-edge LLMs and multimodal systems—including next-gen interaction models like voice interfaces, agentic UIs, and adaptive experiences—across platforms such as OpenAI, Anthropic, Mistral, DeepSeek, and Meta. Build Rapid Prototypes: Develop high-fidelity proof-of-concepts using modern agent frameworks and architectures (LangGraph/LangChain-style workflows, retrieval pipelines, structured output, tool orchestration, etc.). Design + Run Experiments: Create and execute experiments to evaluate agent behaviors, fine-tuning strategies, memory models, and new interaction patterns. Partner with Engineering Teams: Work closely with AI Engineers to convert research prototypes into scalable, production-ready systems. Benchmark Models: Create evaluation setups to measure model accuracy, latency, cost, hallucination behavior, and reliability. Stay Ahead of AI Evolution: Track advancements in model architecture, inference optimization, adapters, multimodal I/O, and emerging research. Document & Present Findings: Publish internal research summaries, share insights, and recommend future platform or product improvements. You Might Be a Strong Fit If You Have 2+ years of hands-on AI/ML research or engineering experience (industry or academic). Deep understanding of LLM architecture—transformers, attention, fine-tuning, LoRA/QLoRA, inference scaling, etc. Proficiency in Python and at least one ML framework (PyTorch, JAX, Hugging Face, etc.). Experience building or fine-tuning retrieval-augmented pipelines, agent systems, or tool-using models. Familiarity with cloud compute, GPUs, vector databases, and model deployment stacks. Ability to prototype quickly—turning research concepts into working demos in days, not months. Strong communication skills—able to translate complex research into actionable insights for product, design, and engineering teams. Nice to Have Experience with LangGraph, LangChain, DSPy, or similar orchestration tools. Background in multimodal AI (vision, speech, video, ASR/TTS). Knowledge of evaluation, red teaming, safety, or alignment techniques. Contributions to open-source LLM projects or published research papers. Experience in enterprise AI, governance, compliance-aware systems, or safety-based architectures.

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