Artificial Intelligence Researcher

Location: India (Remote / Hybrid)Employment Type: Full-timeSalary Range: $220,000 USD (depending on experience)Zapeon is hiring an AI Researcher to design, evaluate, and advance applied AI systems used in real-world enterprise workflows.This role focuses on research-driven development of AI models and agents, with an emphasis on reliability, evaluation, and deployment in production environments rather than purely academic research.Company DescriptionZapeon builds applied AI systems that help organizations operationalize intelligent agents in real business settings.We work at the intersection of large language models, data pipelines, and human-in-the-loop workflows—turning research into systems that can be deployed, evaluated, and trusted in production. Zapeon focuses on practical AI: models and agents that deliver measurable value, not demos.What You’ll DoResearch and prototype AI models and agent architectures for enterprise use casesDesign and run experiments to evaluate model performance, robustness, and failure modesWork with large-scale structured and unstructured data, including text and operational dataDevelop evaluation frameworks for AI agents, including benchmarks and test harnessesCollaborate closely with engineering and product teams to transition research into productionInvestigate model alignment, safety, bias, and reliability in applied settingsDocument research findings clearly for technical and non-technical stakeholdersTrack and assess relevant academic and industry research for practical applicabilityWhat We’re Looking ForExperience in AI research, applied machine learning, or advanced data science rolesStrong grounding in machine learning fundamentals (e.g. NLP, deep learning, evaluation methods)Proven ability to design experiments and reason rigorously about resultsStrong Python skills and experience with ML frameworks (e.g. PyTorch, TensorFlow, JAX)Ability to work across research, engineering, and product functionsBonus SkillsExperience working with large language models (LLMs) or AI agentsBackground in evaluation, data annotation, or human-in-the-loop systemsFamiliarity with model deployment considerations in production environmentsResearch publications, open-source contributions, or technical writingSuccess Looks LikeResearch outputs that measurably improve AI system performance and reliabilityPrototypes that successfully transition into deployed systemsClear evaluation methodologies that guide product and engineering decisionsStrong collaboration between research, engineering, and product teamsInterested? Apply on LinkedIn by sending your profile + CV, or message us directly on LinkedIn.

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