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Applied AI Researcher (India)

Articul8· Applied Research
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Hybrid (India/Bengaluru)Full-timePosted 5mo ago

About the role

Applied AI Researcher at Articul8 to advance a domain-specific GenAI platform, designing and running experiments, building training/evaluation pipelines, and shipping research into production across model training, reinforcement learning, multimodal understanding, and knowledge representation.

Responsibilities

  • Architect and orchestrate massively parallel AI research workflows — design experiments that leverage fleets of agentic AI systems to explore hypothesis spaces, hyperparameter landscapes, and architectural variations at scale.
  • Design, train, and iterate on models across the full GenAI stack — LLMs, VLMs, embedding models, rerankers, and reward models, using agentic pipelines that autonomously manage data preprocessing, training runs, evaluation sweeps, and result synthesis
  • Go deep: push the frontier of domain-specific AI — conduct rigorous, first-principles research into model architectures, training dynamics, reinforcement learning, and knowledge representation, using AI agents to accelerate literature review, ablation studies, and mathematical analysis
  • Go broad: span disciplines and modalities — amplify expertise across NLP, computer vision, multimodal understanding, agentic reasoning, and domain science by delegating exploration, prototyping, and benchmarking to parallel agent systems
  • Build agentic research infrastructure — develop and contribute to shared tooling, libraries, and platforms that enable every researcher on the team to orchestrate autonomous experiment pipelines, data processing workflows, and evaluation harnesses at scale
  • Ship research into production at velocity — collaborate with engineering, product, and domain experts to integrate breakthroughs into the platform rapidly, using agentic CI/CD and automated integration testing to compress the research-to-deployment cycle
  • Amplify collective intelligence — document findings, publish at top-tier venues, and build internal knowledge systems that agentic tools can index and reason over
  • Continuously raise the ceiling on human potential — identify bottlenecks in workflows and design scalable solutions that augment researchers as a core output

Qualifications

  • PhD in Computer Science, Machine Learning, or a related field; or MSc with 4+ years of post-graduation research experience.
  • Trained or fine-tuned at least one neural model end-to-end — data preparation through evaluation.
  • Strong working knowledge of probability, optimization, and linear algebra applied to NLP, computer vision, reinforcement learning, or information retrieval.
  • Experience building training or evaluation pipelines that handle real data — preprocessing, distributed computation, experiment tracking, and reproducibility.
  • Production-quality Python; fluent with Git and collaborative development workflows.

Skills

Required:Neural model development
Last updated Aug 5, 2026. Interested? Apply on the company site.
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