Akash Kumar Pandey

About Akash Kumar Pandey

My areas of technical expertise are: Intelligent Process Automation, Machine Learning, Deep Learning, Artificial Intelligence, Data Mining, Natural Language Processing (NLP), Image Processing, AI Tools, Prompt Engineering and LLM (GenAI) enabled Applications.Hands-on growth leader specialized in taking early-stage B2B SaaS startups from ideation to scale. I help founders and B2B startups solve critical challenges when it comes growth and product market fit. When I\'m not crafting GTM strategies or diving into date analytics, you\'ll find me exploring new cultures or attempting to explain my job to my mom (still working on that!) Product-Market Fit:Finding and validating your ideal customer profile.Turning customer feedback into actionable messaging and marketing initiatives.Building scalable acquisition channels that actually generate revenues.Developed GTM strategies leading to successful market entry.Established product messaging that resonates with target audiences. Growth & Revenue:Creating GTM strategies for pre-revenue to first 1M.Establishing product-led growth frameworks that scale.Converting early adopters into paying customers.Building predictable pipeline generation engines. Resource Optimization:Maximizing impact with limited marketing budgetsSetting up lean but effective marketing operationsImplementing cost-effective growth experiments

Experience

1. Chief Technology Officer

   Techverse Automation & Robotic Systems

   May 2024 — Present

   Trained and evaluated large language models (LLMs) on complex mathematical reasoning and programming logic, enhancing model accuracy and responsiveness by over 25% through systematic quality assessment and prompt optimization. Curated and engineered large-scale datasets (100K+ samples) tailored for AI model training across multiple domains including mathematics, code understanding, and reasoning, improving fine-tuning efficiency and reducing model drift. Applied Python-based debugging and data refinement pipelines to identify and correct logical inconsistencies in LLM outputs, resulting in a 30% reduction in model hallucination and response latency. Collaborated with cross-functional AI research teams to design structured annotation frameworks and evaluation rubrics, improving training throughput by 40% while maintaining high-quality model alignment. Implemented reinforcement learning feedback loops and response ranking systems to iteratively improve LLM behavior, directly contributing to measurable gains in task completion accuracy and contextual coherence. Authored and reviewed complex AI tasks across reasoning, code generation, and multi-step logic categories, providing actionable insights that guided data annotation standards and model retraining strategies. Leveraged Python, NumPy, and prompt-engineering techniques to automate evaluation workflows, achieving 20% faster training data throughput and significantly improving model scalability for enterprise clients.

Education

• KUKA CERTIFICATE (german)

  BASIC AND ADVANCE, Mechanical Engineering

• Greater Noida Institute of Technology(GNIOT)

  Bachelor of Engineering - BE, Mechanical Engineering

  2014 — 2018