As an Open Model AI Evangelist at ShunyaLabs.ai, you will be the catalyst for adoption of our open, builder-first AI models across the global developer ecosystem. Your mission: Get AI/ML researchers, hackers, and builders excited about Shunya Labs’ open models — from ASR to multilingual NLP — and help them integrate these into real-world applications. You’ll do this by being active where developers live (Hugging Face, GitHub, Kaggle, Reddit, Discord), creating high-quality technical content, sparking conversations, and organizing events that bring the open AI community together. Key Responsibilities: Developer Advocacy & Ecosystem Presence · Represent Shunya Labs across Hugging Face, GitHub, Kaggle, Reddit, LinkedIn, and Discord. · Engage directly with developers, researchers, and open-source maintainers to showcase our open models. · Spot opportunities for integrations, collaborations, and adoption in real-world products. Technical Content Creation · Publish tutorials, benchmarks, and sample apps demonstrating our open model stack. · Launch Hugging Face Spaces and GitHub repos showcasing use cases. · Collaborate with marketing to create engaging developer-facing content (deep dives, explainers, memes, short videos) Community Growth & Activation · Organize online hackathons, Kaggle challenges, and “build with Shunya” events. · Run AMAs, webinars, and conference talks to expand reach and influence. · Seed and mentor open-source contributions. Feedback Loop · Gather developer feedback on models, APIs, and documentation; feed actionable insights to engineering and product teams. · Track and report adoption metrics (downloads, forks, pull requests, Spaces built) to inform strategy. Qualifications: Must-Have · Graduate from a Tier-1 engineering or technical institution (IIT/NIT/BITS/IIIT or top global universities). · Passion for AI/ML, with experience in open-source AI communities. · Strong technical communication skills — able to explain complex AI concepts to both technical and semi-technical audiences. · Track record of contributions in open-source, developer relations, or ML research. Nice-to-Have · Experience with Hugging Face model hosting, Spaces, and datasets. · Familiarity with Kaggle competitions, GitHub OSS workflows, and Discord community building. · Ability to create quick demos, notebooks, or deploy lightweight models.
Role Overview We are seeking an AI Engineer with 2–4 years of experience to design, build, and optimize AI/ML models—focusing on speech, NLP, and deployment at scale. You will work closely with our research and engineering teams to bring state-of-the-art models into production. Key Responsibilities Develop and fine-tune AI/ML models (ASR, NLP, deep learning). Build scalable training and inference pipelines. Optimize models for latency, accuracy, and CPU/edge deployment. Collaborate with MLOps/DevOps to deploy APIs and services. Monitor, test, and improve production models with real-world data. Requirements 2–4 years of hands-on experience in AI/ML engineering. Strong skills in Python , PyTorch/TensorFlow , and deep learning. Knowledge of NLP, speech/audio processing, or related domains. Experience in deploying models (APIs, Docker, cloud/on-prem). Good understanding of data preprocessing, model evaluation, and optimization. Bonus: familiarity with multilingual/Indic datasets, graph models, or noise-robust ASR. Why Join Us Work on cutting-edge voice AI with global impact. Opportunity to learn and contribute across research, engineering, and deployment. Fast-paced deep-tech startup with strong ownership and growth. About Us Shunya Labs.AI is a deep-tech company building next-generation ASR and voice AI infrastructure with multilingual fluency, record-low WER, and enterprise-grade deployments.
We’re seeking a passionate AI Engineer to join our team and help build, train, and deploy intelligent systems that solve real-world problems. You’ll work on developing scalable machine learning and deep learning solutions, integrating them into production systems, and optimizing model performance for speed and accuracy. Key Responsibilities Design, develop, and deploy machine learning and deep learning models for production use cases. Fine-tune LLMs , NLP , computer vision , or predictive analytics models based on business needs. Collaborate with data engineers to prepare and preprocess large datasets. Implement model serving pipelines using tools like TensorFlow Serving , TorchServe , FastAPI , or Docker . Optimize inference performance on GPU instances or edge devices . Conduct experiments, evaluate models, and iterate based on metrics (precision, recall, F1, AUC, etc.). Integrate AI modules into web or mobile applications via APIs or microservices. Stay updated on new AI architectures, frameworks, and tools (e.g., LangChain, Hugging Face, OpenAI APIs). Requirements Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field . 1+ years of hands-on experience in machine learning or deep learning model development. Strong programming skills in Python and experience with PyTorch , TensorFlow , or Keras . Experience with data preprocessing , feature engineering , and model evaluation . Familiarity with LLM frameworks (LangChain, Hugging Face Transformers, OpenAI API) is a plus. Proficiency in SQL/NoSQL , RESTful APIs , and Docker/Kubernetes . Preferred Skills Knowledge of vector databases (Pinecone, FAISS, Weaviate). Experience in prompt engineering , fine-tuning , or RAG (Retrieval-Augmented Generation) pipelines. Exposure to Generative AI applications (text, image, or voice). Why Join Us Work with cutting-edge AI technologies and real-world datasets. Be part of a fast-growing, innovation-driven team. Competitive salary and performance-based incentives. Flexible work culture with opportunities for upskilling and research contributions. About Us Shunya Labs is a deep-tech spinout from United We Care, purpose-built to revolutionize voice AI infrastructure. With a next-generation ASR engine boasting a record-low 3.37% Word Error Rate , native fluency across 32+ Indic languages , CPU-optimized, on-prem capable deployment , and military-grade privacy and explainability , we're enabling mission-critical deployments across healthcare, defense, rural, and enterprise environments
We’re seeking a passionate AI Engineer to join our team and help build, train, and deploy intelligent systems that solve real-world problems. You’ll work on developing scalable machine learning and deep learning solutions, integrating them into production systems, and optimizing model performance for speed and accuracy. Key Responsibilities Design, develop, and deploy machine learning and deep learning models for production use cases. Fine-tune LLMs , NLP , computer vision , or predictive analytics models based on business needs. Collaborate with data engineers to prepare and preprocess large datasets. Implement model serving pipelines using tools like TensorFlow Serving , TorchServe , FastAPI , or Docker . Optimize inference performance on GPU instances or edge devices . Conduct experiments, evaluate models, and iterate based on metrics (precision, recall, F1, AUC, etc.). Integrate AI modules into web or mobile applications via APIs or microservices. Stay updated on new AI architectures, frameworks, and tools (e.g., LangChain, Hugging Face, OpenAI APIs). Requirements Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field . 1+ years of hands-on experience in machine learning or deep learning model development. Strong programming skills in Python and experience with PyTorch , TensorFlow , or Keras . Experience with data preprocessing , feature engineering , and model evaluation . Familiarity with LLM frameworks (LangChain, Hugging Face Transformers, OpenAI API) is a plus. Proficiency in SQL/NoSQL , RESTful APIs , and Docker/Kubernetes . Preferred Skills Knowledge of vector databases (Pinecone, FAISS, Weaviate). Experience in prompt engineering , fine-tuning , or RAG (Retrieval-Augmented Generation) pipelines. Exposure to Generative AI applications (text, image, or voice). Why Join Us Work with cutting-edge AI technologies and real-world datasets. Be part of a fast-growing, innovation-driven team. Competitive salary and performance-based incentives. Flexible work culture with opportunities for upskilling and research contributions. About Us Shunya Labs is a deep-tech spinout from United We Care, purpose-built to revolutionize voice AI infrastructure. With a next-generation ASR engine boasting a record-low 3.37% Word Error Rate , native fluency across 32+ Indic languages , CPU-optimized, on-prem capable deployment , and military-grade privacy and explainability , we're enabling mission-critical deployments across healthcare, defense, rural, and enterprise environments
About Shunya Labs 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 and CPU-first infrastructure, driving accuracy, privacy, and scalability. You will join at a pivotal moment — where GTM precision meets ecosystem expansion, defining how Voice AI enters the enterprise mainstream. Role Overview As Director – Ecosystem & Growth (Voice AI), you will be the GTM engine of Shunya Labs — responsible for architecting, operationalizing, and scaling the company’s enterprise growth motion across verticals and geographies. You’ll own revenue strategy, pipeline velocity, GTM partnerships, and demand generation, while leveraging community and ecosystem programs as scalable acquisition channels. You’ll work shoulder-to-shoulder with the CBO to define where and how Shunya Labs grows, who we sell to, and what partnerships accelerate our expansion in the Voice AI infrastructure market. Key Responsibilities 1. GTM Strategy & Execution • Define and implement the end-to-end GTM strategy across target industries — Healthcare, Contact Centers, Media, BFSI, and Developer Platforms. • Develop segmented value propositions for each buyer persona (CXOs, IT Heads, Product Leaders, Developer teams). • Design and own the sales playbook — from outbound prospecting, inbound qualification, demos, and proof-of-concepts to contract closure and expansion. • Lead pipeline generation, deal acceleration, and forecast accuracy; collaborate with Marketing for demand-gen campaigns, case studies, and field events. • Partner with the CEO/CBO to establish pricing strategy, revenue model, and tiered customer monetization (usage-based, API, and enterprise subscription models). • Set up a scalable GTM rhythm — from CRM hygiene, sales ops, and dashboards to win/loss analysis. 2. Ecosystem & Community Growth • Build and lead a Voice AI ecosystem of developers, integrators, and research collaborators on Discord, Hugging Face, and GitHub. • Design co-innovation programs, partner integrations, and hackathons to drive visibility and organic adoption. • Recruit and mentor community advocates and technical evangelists who represent Shunya Labs across developer and AI forums. • Translate community momentum into pipeline and brand equity, creating an always-on feedback loop between market, product, and GTM . 3. Strategic Partnerships • Identify and close strategic alliances with ISVs, System Integrators, and OEMs to drive enterprise distribution. • Build referral and reseller partnerships that scale reach and lower CAC. • Explore co-marketing and integration partnerships with major AI ecosystems (AWS, NVIDIA, OpenAI, Hugging Face). 4. Revenue & Metrics • Own ARR, MRR, CAC, LTV, and conversion metrics across direct and indirect channels. • Build a data-driven GTM engine — dashboards, reporting cadences, pipeline velocity analysis, and ROI attribution. • Create GTM OKRs that tie community health, pipeline growth, and revenue outcomes together. Required Experience & Skills • 10–12 years in enterprise GTM / revenue leadership (SaaS, AI/ML, Infrastructure). • Demonstrated success in developing and executing multi-channel GTM strategies — outbound, inbound, partner, and community-led. • Strong experience in enterprise sales, with exposure to large-deal structuring, multi-stakeholder negotiation, and long-cycle B2B selling. • Prior experience building or leveraging developer or open-source communities for market expansion. • Analytical and operational fluency: forecasting, pricing models, funnel analytics, and GTM automation tools (HubSpot, Salesforce, etc.). • Excellent communication and storytelling; can inspire confidence across leadership and developer audiences alike. • Bonus: Prior work in Voice AI, ASR/TTS, conversational AI, or speech-tech ecosystems (Deepgram, Speechmatics, ElevenLabs, OpenAI, etc.). Success Metrics (First 12 Months) • Revenue and pipeline growth (direct + ecosystem channels). • CAC and LTV improvements through GTM efficiency. • Conversion rate from community and partnership-led channels. • Enterprise logo acquisition and expansion across verticals. • Partner integrations launched and co-selling motions activated. • Brand visibility and developer engagement on Hugging Face, Discord, GitHub. What You’ll Get • End-to-end ownership of the Voice AI GTM engine — from strategy to execution. • A leadership role defining how enterprises adopt speech intelligence at scale. • Exposure to C-suite collaboration, investor conversations, and global partnerships. • Competitive compensation + variable linked to revenue and GTM KPIs. • Full-time, on-site role at Shunya Labs HQ, Gurgaon.
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 We’re seeking an AI Systems Engineer who thrives at the intersection of AI model optimization , infrastructure engineering , and applied research . You will evaluate, host, and optimize a wide range of AI models—spanning ASR, LLMs, and multimodal systems and build the orchestration layer that powers scalable, low-latency deployments. This is a role for someone who’s comfortable navigating ambiguity , researching emerging AI methods , and translating client requirements into robust, production-ready solutions. You’ll work across the full stack—from GPU inference tuning to React-based control dashboards building a resilient and scalable AI delivery platform. Key Responsibilities - AI Model Evaluation & Optimization · Evaluate, benchmark, and optimize AI models (speech, text, vision, multimodal) for latency, throughput, and accuracy. · Implement advanced inference optimizations using ONNX Runtime , TensorRT , quantization , and GPU batching . · Continuously research and experiment with the latest AI runtimes , serving frameworks, and model architectures. · Develop efficient caching and model loading strategies for multi-tenant serving. AI Infrastructure & Orchestration · Design and develop a central orchestration layer to manage multi-model inference, load balancing, and intelligent routing. · Build scalable, fault-tolerant deployments using AWS ECS/EKS , Lambda , and Terraform . · Use Kubernetes autoscaling and GPU node optimization to minimize latency under dynamic load. · Implement observability and monitoring (Prometheus, Grafana, CloudWatch) across the model-serving ecosystem. DevOps, CI/CD & Automation · Build and maintain CI/CD pipelines for model integration, updates, and deployment (GitHub Actions, CodePipeline, etc.). · Manage Dockerized environments , version control, and GPU-enabled build pipelines. · Ensure reproducibility and resilience through infrastructure-as-code and automated testing. Frontend & Developer Tools · Create React/Next.js -based dashboards for performance visualization, latency tracking, and configuration control. · Build intuitive internal tools for model comparison, experiment management, and deployment control. · Utilize Cursor , VS Code , and other AI-powered development tools to accelerate iteration. Client Interaction & Solutioning · Work closely with clients and internal stakeholders to gather functional and performance requirements . · Translate abstract business needs into deployable AI systems with measurable KPIs. · Prototype quickly, iterate with feedback, and deliver robust production systems. Research & Continuous Innovation · Stay on top of the latest AI research and model releases (OpenAI, Anthropic, Hugging Face, Meta, etc.). · Evaluate emerging frameworks for model serving, fine-tuning, and retrieval (LangChain, LlamaIndex, GraphRAG, etc.). · Proactively identify and implement performance or cost improvements in the model serving stack. · Share learnings and contribute to the internal AI knowledge base. Ambiguous Problem Solving · Work effectively in undefined problem spaces , identifying optimal paths forward through experimentation. · Break down high-level goals into actionable technical strategies. · Balance trade-offs between accuracy, latency, and cost while innovating under uncertainty. Required Skills · Strong proficiency in Python , TypeScript/JavaScript , Bash , and modern software development practices. · Deep understanding of Docker , Kubernetes , Terraform , and AWS (ECS, Lambda, S3, CloudFront) . · Experience with inference optimization (ONNX, TensorRT, quantization, batching). · Proven ability to design and scale real-time inference pipelines . · Experience building and maintaining CI/CD pipelines and monitoring systems . · Hands-on experience with React/Next.js or similar frameworks for dashboard/UI development. · Strong grasp of API design , load balancing , and GPU resource management . Nice to Have · Experience with LangChain , LlamaIndex , GraphRAG , or vector databases (FAISS, Neo4j) . · Familiarity with speech processing models (Whisper, Silero, NeMo, etc.). · Prior work with serverless inference or edge AI architectures. · Knowledge of data pipelines , model versioning , and MLOps best practices . Soft Skills · Excellent problem-solving in ambiguous, evolving environments. · Strong ability to research, self-learn, and prototype emerging AI technologies. · Confident communicator who can translate technical findings to business impact. · Ownership mindset with a collaborative, solution-oriented approach.
As an AI Systems Engineer at Shunya Labs, you will play a crucial role in optimizing AI models, designing infrastructure, and conducting research. You will be responsible for evaluating, hosting, and optimizing a variety of AI models including ASR, LLMs, and multimodal systems. Your key responsibilities will include: - **AI Model Evaluation & Optimization** - Evaluate, benchmark, and optimize AI models for latency, throughput, and accuracy. - Implement advanced inference optimizations using ONNX Runtime, TensorRT, quantization, and GPU batching. - Continuously research and experiment with the latest AI runtimes, serving frameworks, and model architectures. - Develop efficient caching and model loading strategies for multi-tenant serving. - **AI Infrastructure & Orchestration** - Design and develop a central orchestration layer to manage multi-model inference, load balancing, and intelligent routing. - Build scalable, fault-tolerant deployments using AWS ECS/EKS, Lambda, and Terraform. - Use Kubernetes autoscaling and GPU node optimization to minimize latency under dynamic load. - Implement observability and monitoring (Prometheus, Grafana, CloudWatch) across the model-serving ecosystem. - **DevOps, CI/CD & Automation** - Build and maintain CI/CD pipelines for model integration, updates, and deployment. - Manage Dockerized environments, version control, and GPU-enabled build pipelines. - Ensure reproducibility and resilience through infrastructure-as-code and automated testing. - **Frontend & Developer Tools** - Create React/Next.js-based dashboards for performance visualization, latency tracking, and configuration control. - Build intuitive internal tools for model comparison, experiment management, and deployment control. - Utilize Cursor, VS Code, and other AI-powered development tools to accelerate iteration. - **Client Interaction & Solutioning** - Work closely with clients and internal stakeholders to gather functional and performance requirements. - Translate abstract business needs into deployable AI systems with measurable KPIs. - Prototype quickly, iterate with feedback, and deliver robust production systems. - **Research & Continuous Innovation** - Stay updated on the latest AI research and model releases. - Evaluate emerging frameworks for model serving, fine-tuning, and retrieval. - Implement performance or cost improvements in the model serving stack and contribute to the internal AI knowledge base. In terms of qualifications, you should have strong proficiency in Python, TypeScript/JavaScript, Bash, and modern software development practices. Deep understanding of Docker, Kubernetes, Terraform, and AWS is required. Experience with inference optimization, CI/CD pipelines, and React/Next.js is essential. Additionally, soft skills like problem-solving in ambiguous environments, research abilities, and strong communication skills are highly valued. Shunya Labs is at the forefront of building Voice AI Infrastructure for Enterprises, focusing on speech intelligence and domain-specific voice applications. If you are passionate about AI, infrastructure engineering, and research, this role offers a unique opportunity to make a significant impact in the field.,
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 We’re looking for an AI Research Scientist who combines deep technical understanding of AI systems with the curiosity to explore how emerging models can reshape real-world industries. This role sits at the intersection of research, strategy, and applied innovation identifying automation opportunities, developing proofs-of-concept, and translating cutting-edge AI into scalable products. You’ll work closely with leadership, engineering, and clients to define the company’s AI product roadmap , continuously evaluate the evolving AI landscape, and design systems that deliver measurable operational impact. 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.
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 We're looking for an AI Research Scientist who combines deep technical understanding of AI systems with the curiosity to explore how emerging models can reshape real-world industries. This role sits at the intersection of research, strategy, and applied innovation identifying automation opportunities, developing proofs-of-concept, and translating cutting-edge AI into scalable products. You'll work closely with leadership, engineering, and clients to define the company's AI product roadmap , continuously evaluate the evolving AI landscape, and design systems that deliver measurable operational impact. 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.
Role Overview: You will be joining Shunya Labs as an AI Research Scientist, where you will have the opportunity to combine your deep technical understanding of AI systems with the curiosity to explore emerging models that can reshape real-world industries. Your role will involve research, strategy, and applied innovation to identify automation opportunities, develop proofs-of-concept, and translate cutting-edge AI into scalable products. You will work closely with leadership, engineering teams, and clients to define the company's AI product roadmap, continuously evaluate the evolving AI landscape, and design systems that deliver measurable operational impact. Key Responsibilities: - Conduct industry research and opportunity discovery by studying operational workflows across diverse industries such as insurance, healthcare, logistics, financial services, and manufacturing. - Identify high-impact automation and augmentation opportunities using AI and LLM-based systems. - Conduct process diagnostics to map inefficiencies, manual dependencies, and automation gaps. - Collaborate with domain experts to design AI-driven transformation blueprints for clients and internal use cases. - Continuously track the latest AI research, model architectures, and open-source innovations. - Conduct deep technical analysis of foundation models such as transformer internals, embeddings, retrieval architectures, and diffusion. - Build and fine-tune custom AI models for tasks like language understanding, summarization, transcription, classification, and reasoning. - Experiment with emerging architectures to enhance accuracy and adaptability. - Develop evaluation frameworks for model performance, fairness, and interpretability. - 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 and lead feasibility assessments for model-hosting infrastructure, inference optimization, and deployment scalability. - 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. - 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. Qualifications Required: - 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 such as tokenization, attention, context windows, embeddings, and quantization. - Strong analytical skills to connect technical innovation with business value. - Excellent written and verbal communication skills for presenting research and influencing stakeholders. (Note: Nice to Have and Soft Skills sections have been omitted as per the provided instructions),
About Shunya Shunya is a deep-tech AI company building CPU-native, multilingual speech and language systems with a strong focus on security, reliability, and on-device intelligence. We operate at the intersection of cutting-edge technology, enterprise deployments, and global scale. Role Overview We are looking for a high-trust, high-ownership professional who will manage talent acquisition, HR operations, and executive support for the Founder. This is a critical role that sits at the center of hiring, people operations, and leadership execution. Experience: 0-3 years Key Responsibilities · Maintain organized entity-wise documentation for India, US and Singapore entities (invoices, corporate records, contracts, ESOP records). · Record and process expenses, vendor invoices, reimbursements, and inter-company entries. · Perform bank, card, and upcoming obligations; flag issues early. · Track receivables, payables, cash flow on a periodic basis and upcoming obligations across entities. · Assist and support in monthly, quarterly, and annual financial close processes and preparation of MIS reports, budgets, and financial summaries. · Assist with bank operations, KYC updates, and payment processing for India and offshore accounts. · Coordinate with external consultants for accounting and book-keeping. · Support inter-company cost allocations, invoicing, and transfer documentation. · Compliance, Governance & Record-Keeping · Ensure documents are properly archived and readily available for audits, due diligence, and investor reviews. · Support audit processes by compiling schedules, confirmations, and documentation. · Support corporate filings and documentation as required for India and off-shore entities · Payroll & Administration · Coordinate payroll execution through India and offshore payroll vendors, as applicable. · Maintain ESOP documentation, and expense reimbursements. · Manage office administration, subscriptions, renewals, and office-related expenses. · Maintain organized records of agreements, invoices, approvals, and correspondence. · Assist in coordination with external consultant for organising of board, shareholder, or internal meetings as required. · Arrange domestic and international travel, hotel bookings, and ground transportation for founders, leadership, and visiting team members. What Success Looks Like (First 6–9 Months) · Key roles hired efficiently with strong candidate quality. · Smooth HR operations with minimal escalations. · Founder’s time optimized through effective prioritization and follow-ups. · High trust relationship with leadership and teams. Why Join Shunya · Work directly with the Founder with high visibility and impact. · Be part of a globally ambitious deep-tech company. · Opportunity to grow into a Chief of Staff / People Lead role over time. · High ownership, learning, and long-term growth.