AI Research Scientist

About US

Shunya Labs is building the Voice AI Infrastructure Layer for Enterprises powering speech intelligence, conversational agents, and domain-specific voice applications across industries. Born from deep work in mental-health AI and built for global enterprise scale, our stack combines state-of-the-art ASR/TTS models with an open-weights philosophy , driving accuracy, privacy, and scalability.

About the Role

AI Research Scientist

Key Responsibilities -

Industry Research & Opportunity Discovery

• Study operational workflows across diverse industries (insurance, healthcare, logistics, financial services, manufacturing, etc.).
• Identify

  high-impact automation and augmentation opportunities

  using AI and LLM-based systems.
• Conduct

  process diagnostics

  mapping inefficiencies, manual dependencies, and automation gaps.
• Collaborate with domain experts to design

  AI-driven transformation blueprints

  for clients and internal use cases.

AI Research & Model Development

• Continuously track

  latest AI research

  , model architectures, and open-source innovations (LLMs, vision models, multimodal systems).
• Conduct deep technical analysis of foundation models transformer internals, embeddings, retrieval architectures, diffusion, etc.
• Build and fine-tune custom AI models for tasks such as language understanding, summarization, transcription, classification, and reasoning.
• Experiment with

  emerging architectures

  (Mixture of Experts, RAG, GraphRAG, multi-agent systems) to enhance accuracy and adaptability.
• Develop evaluation frameworks for model performance, fairness, and interpretability.

Productization & Innovation

• Work with engineering teams to translate research prototypes into

  market-ready products

  .
• Define technical strategy and architecture for AI-driven product lines.
• Contribute to internal IP creation model enhancements, pre-training pipelines, or domain-specific datasets.
• Lead feasibility assessments for model-hosting infrastructure, inference optimization, and deployment scalability.

Thought Leadership & Continuous Learning

• Stay ahead of global AI trends by following leading research labs, open-source communities, and academic breakthroughs.
• Produce internal whitepapers, presentations, and tech briefs summarizing emerging technologies.
• Represent the organization in conferences, panels, and AI research forums.
• Mentor junior researchers and engineers in AI methodologies and experimentation.

Strategic Collaboration & Solutioning

• Partner with business and product leaders to align research outcomes with commercial goals.
• Participate in

  client discussions

  , understanding pain points and shaping AI-powered solutions.
• Provide strategic inputs on go-to-market initiatives for AI offerings.

Required Skills -

• Strong foundation in

  AI/ML algorithms

  ,

  deep learning architectures

  , and

  transformer-based models

  .
• Experience with

  Python

  ,

  PyTorch

  ,

  TensorFlow

  ,

  Hugging Face

  , and

  LangChain

  ecosystems.
• Hands-on experience with

  model training, fine-tuning, and evaluation

  .
• Ability to read and interpret

  AI research papers

  , reproduce experiments, and assess feasibility.
• Understanding of

  LLM internals

  (tokenization, attention, context windows, embeddings, quantization).
• Strong analytical skills to connect

  technical innovation with business value

  .
• Excellent written and verbal communication for presenting research and influencing stakeholders.

Nice to Have -

• Experience building

  domain-specific AI models

  (e.g., financial document analysis, claims automation, customer service bots).
• Exposure to

  retrieval-augmented generation (RAG)

  ,

  graph-based reasoning

  , or

  multi-agent orchestration

  .
• Background in

  data curation

  ,

  synthetic data generation

  , or

  evaluation pipelines

  .
• Familiarity with

  AWS Sagemaker

  ,

  Vertex AI

  , or

  custom training environments

  .
• Published research or contributions to open-source AI projects.

Soft Skills -

• Strong curiosity and comfort with

  ambiguous, open-ended problems

  .
• Strategic mindset can balance research creativity with product pragmatism.
• Ability to distill complex technical ideas into business-friendly narratives.
• Collaborative and entrepreneurial spirit; thrives in fast-moving innovation environments.