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Piyush MittalPM

Piyush Mittal

Lead AI Engineer | LLM | MLOps | LLMops

€980/day
Frankfurt am Main, DE
8-15 years

Average response time: 1 hour

About Piyush

Machine Learning Engineer / AI Engineer with 14+ years of experience building
and scaling LLM-powered search, retrieval-augmented generation (RAG), and AI
agent platforms in production. Proven track record delivering high-reliability, multi-
tenant AI systems across cloud and hybrid environments, spanning semantic
search, hybrid retrieval (vector + keyword), ranking, evaluation frameworks, and
LLMOps. Strong collaborator with Product and ML teams
  • English

    Native or bilingual

  • German

    Conversational

Can work on-site
Frankfurt am Main (up to 50km)

Experience

  • Centric software
    AI and MLops Lead
    DIGITAL AND IT
    January 2025 - Today (1 year and 5 months)
    Berlin, Germany
    • Enterprise Product Lifecycle Management (PLM) & Pricing Platform
    • Built and scaled a production RAG-based AI agent serving enterprise PLM andpricing use cases; deployed to production, staging, and demo environments.
    • Architected a multi-tenant retrieval platform with vector search, structured knowledge bases, and section-based chunking, improving answer accuracy and contextual relevance.
    • Implemented API-driven context management, reducing conversation instability and improving response consistency across sessions.
    • Designed offline and online LLM evaluation pipelines (faithfulness, accuracy, regression), preventing quality degradation across releases.
    • Delivered rule-based plausibility and investigative workflows, enabling bulk analysis and reducing post-sales investigation effort.
    • Optimized latency and cost via cache TTLs and tool-call optimization, significantly reducing redundant LLM calls.
    • Applied parameter-efficient fine-tuning (PEFT) techniques, including LoRA, to adapt LLMs and embedding models for domain-specific PLM and pricing knowledge, improving retrieval relevance, reasoning accuracy, and response faithfulness in production RAG workflows.
    • Led production readiness, customer onboarding, and EU→US data-center migrations, ensuring enterprise-grade reliability and compliance.
    • Mentored engineers on LLMOps, RAG design, and production reliability.
    LLMOps MLFlow RAG Langchain PGVecotr
  • Verve Group
    Machine Learning Lead
    September 2022 - Today (3 years and 9 months)
    Verve is a market leader in AdTech domain offering programmatic solutions that connect advertisers and publishers to people in real-time. Orchestrated Language Model (LLM)-driven ad personalization initiatives, resulting in a remarkable 15% increase in conversion rates. Led the Adaptive Demand Shaping (ADS) project, optimized model that filtered low-value traffic to optimize query per second (qps) while aligning supply with demand in auction dynamics. This initiative resulted in a 10% increase in revenue. Orchestrated the deployment of machine learning models into production, resulting in a 25% improvement in operational efficiency. Implemented CI/CD pipelines for entire projects, incorporating continuous model retraining, monitoring, and infrastructure as code practices. Led the integration of models into an in-house A/B test framework, playing a key role in parallel experimental design, data preparation, feature engineering, model integration, and statistical analysis. This effort resulted in optimized product performance and facilitated data- driven decision-making
  • German Edge Cloud
    Principal Data Scientist
    December 2019 - September 2022 (2 years and 9 months)
    Eschborn, HE, Germany
    Leading, defining, and implementing end-to-end modern data platforms in support of analytics and AI use cases. Addressing aspects such as data privacy & security, data ingestion & processing, data storage & compute, analytical & operational consumption, data modeling, data virtualization, self-service data preparation & analytics, AI enablement, and API integrations Define and support data transformation and preparation activities independently and in conjunction with data scientists. Advise on, design, and deploy models and solutions built around deep and machine learning technologies. Research, evaluate, and recommend process improvements, including automated systems and enhanced models in support of activities.

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Education

  • Master of Science in Computer Science
    National Institute of Technology Rourkela
    2013
    Master's degree, Computer Science
  • Bachelor of Engineering in Computer Science and Engineering
    Gautam Buddha University
    2011
    Bachelor's degree, Computer Science and Engineering

Certifications

Skill set

Categories

  • Other