Senior Generative AI scientist
At a glance
Senior AI Research role at Weekday AI. Pune · full-time.
Pay not stated AI Research salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build conversational models for chat, voice and multimodal interfaces, then take them through implementation
- Create RAG workflows spanning data preparation, semantic indexing and retrieval methods
- Track LLM latency, hallucinations and bias, and use testing to improve model results and user experiences
- Work with product, engineering and data teams to shape roadmaps and measure AI’s effect on business KPIs
- Guide junior scientists and data engineers, and develop policies for responsible AI use
What you bring
- At least six years applying AI, with a focus on conversational or voice systems
- You have built and scaled RAG pipelines using retrieval methods and knowledge graphs
- You understand LLM architecture and can put monitoring and observability systems in place
- You bring practical Python skills and experience with at least one named machine-learning framework and cloud platform
Who this fits
This senior role suits someone who can lead AI work from research and model development through production, while guiding junior teammates. It is an on-site position in Pune.
From the employer
𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀
𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟮𝟱𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟱𝟬𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟮𝟱-𝟱𝟬 𝗟𝗣𝗔)
Experience: 6+ yrs
Location: pune, bangalore, chennai
As a Senior Generative AI Scientist, you will spearhead the design and deployment of cutting‑edge conversational and voice intelligence solutions, driving the integration of large language models with real‑world applications. You will architect and optimize retrieval‑augmented generation pipelines, ensuring robust LLM observability and performance at scale. Collaborating closely with product, engineering, and data teams, you will translate business challenges into AI-enabled products that deliver measurable impact. Your role will involve continuous experimentation, model fine‑tuning, and the development of best‑practice guidelines for responsible AI use.
Requirements
𝗞𝗲𝘆 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀
• Lead the research, design, and implementation of conversational AI models that power chat, voice, and multimodal interfaces.
• Develop and maintain end‑to‑end RAG systems, including data curation, semantic indexing, and retrieval heuristics.
• Implement observability frameworks for LLMs, monitoring metrics such as latency, hallucination rates, and bias indicators.
• Conduct rigorous A/B testing and real‑world validation to refine model outputs and user experiences.
• Mentor junior scientists and data engineers, fostering a culture of experimentation and continuous learning.
• Collaborate with cross‑functional teams to define product roadmaps and quantify AI impact on key business KPIs.
• Spearhead the adoption of open‑source and proprietary tools for model training, evaluation, and deployment in cloud environments.
• Drive the creation of guidelines and policies for responsible AI, ensuring compliance with regulatory and ethical standards.
• Engage with academic and industry communities to stay abreast of emerging research and technologies.
• Present findings and strategic insights to senior leadership, shaping the organization’s AI strategy.
𝗪𝗵𝗮𝘁 𝗠𝗮𝗸𝗲𝘀 𝗬𝗼𝘂 𝗮 𝗚𝗿𝗲𝗮𝘁 𝗙𝗶𝘁
• 6+ years of experience in applied AI, with a strong focus on conversational and voice AI systems.
• Proven expertise in building and scaling RAG pipelines, leveraging retrieval techniques and knowledge graphs.
• Deep knowledge of LLM architecture and the ability to implement observability and monitoring solutions.
• Hands‑on experience with major frameworks (PyTorch, TensorFlow, Hugging Face, LangChain) and cloud platforms (AWS, GCP, Azure).
• Strong programming skills in Python, along with proficiency in data engineering tools such as Apache Spark or Dask.
• Track record of publishing research papers or delivering open‑source contributions in AI and NLP domains.
• Excellent collaboration and communication skills, with the ability to translate technical concepts to non‑technical stakeholders.
• Demonstrated leadership in guiding cross‑functional teams through end‑to‑end AI projects from ideation to production.
• Ability to think strategically about AI product roadmaps and articulate long‑term vision.
• Passion for staying current with AI advancements and integrating the latest innovations into practical solutions.
AI Research work from LinkedIn, X, Reddit and Upwork, in one list.
Each morning you get everything that fits, strongest first.
AI Research
Find me workBy the team behind aimlroles.