Manav Anandani

AI Researcher

San Francisco, California, United States11 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Designed production-scale AI systems with real-world reliability.
Spearheaded enterprise-scale GenAI pipeline development.
Developed AI-powered exam proctoring platform enhancing accuracy.

Stackforce AI infers this person is a SaaS and EdTech specialist with a strong focus on AI systems and machine learning.

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Skills

Core Skills

Artificial Intelligence (ai)Large Language Models (llms)Machine Learning

Other Skills

Generative AIGenAILLM SummarizationComputer VisionDeep LearningTime Series AnalysisData AnalysisCloud ComputingAI Systems EngineeringSoftware EngineeringTeam LeadershipProgram ManagementEvent ManagementStrategic PlanningOperations Management

About

I design and own production-scale AI systems, with a strong focus on LLM-based and agentic AI workflows that operate reliably in real-world environments. I’m currently pursuing a Master’s in Data Science at San Jose State University and working as an AI Engineer Intern at Lumen, where I build and deploy AI-driven systems that process data at scale and support critical business workflows. My work sits at the intersection of AI, software engineering, and system design turning models into dependable, scalable products. My experience includes: - Designing and operating agentic LLM pipelines for tasks such as summarization, intent extraction, and intelligent decisioning - Building AI systems with evaluation, reliability, and performance as first-class concerns, not just model accuracy - Developing backend AI services that integrate with production APIs and downstream platforms - Applying machine learning and deep learning to real-world problems including anomaly detection, forecasting, and content analysis I’m particularly focused on agentic AI and LLM systems areas where reasoning, orchestration, evaluation, and engineering discipline matter as much as the model itself. I’m looking to contribute to teams building high-impact, production-grade AI systems, where thoughtful system design and AI rigor drive real-world outcomes. Reach out at: manavanandani304@gmail.com

Experience

11 mos

Total Experience

11 mos

Average Tenure

Current Experience

Fydo

AI Systems Engineer

Sep 2025 – Dec 2025 · 3 mos · San Francisco Bay Area · Hybrid

Worked on the AI engineering and infrastructure behind Money Arena, Fydo’s interactive negotiation training platform.
Engineered core AI-driven system workflows powering real-time negotiation simulations.
Implemented end-to-end Voice AI interaction pipelines including transcript capture, scoring logic, and evaluation workflows.
Designed structured logging, observability pipelines, and performance monitoring to improve system reliability and debugging visibility.
Strengthened authentication, session management, and real-time interaction stability for production-ready user engagement.
Collaborated directly with the founding team to build and iterate on AI-powered product features in a fast-moving startup environment.

Artificial Intelligence (AI)Generative AI

Lumen technologies

AI Engineer Intern

May 2025 – Aug 2025 · 3 mos · San Jose, California, United States · Hybrid

Spearheaded the development of an enterprise-scale GenAI pipeline to autonomously analyze multi-million-row conversational datasets using Google Cloud, BigQuery, and production-grade NLP components.
Engineered a fully modular data-to-insight system integrating LLM-powered summarization, subintent detection, and sentiment scoring, driving automation and decision intelligence across customer operations.
Designed high-throughput, checkpoint-aware batch processing architecture with auto-recovery, parameterized querying, and fault tolerance, enabling scalable ingestion across diverse customer channels.
Led experimentation and benchmarking of summarization models using Google ADK, prompt-tuned LLMs, and fallback heuristics (VADER, rule-based classifiers), reducing hallucinations and improving interpretability.
Collaborated with engineering, analytics, and GTM teams to align AI-driven insights with business KPIs; contributed to solution documentation, team enablement, and architecture reviews in a cloud-native MLOps environment.

GenAILLM SummarizationLarge Language Models (LLMs)

Dots & coms

Software Engineer-Data Platform

Jun 2023 – May 2024 · 11 mos · Gujarat, India · Hybrid

Designed and implemented an AI-powered online exam proctoring platform, leveraging data analytics, machine learning, and automation to enhance real-time monitoring, review processes, and automated alert generation, achieving a 35% improvement in accuracy over industry benchmarks.
Integrated computer vision, face detection, and speech recognition to analyze behavioral patterns and detect anomalies, ensuring academic integrity and fraud prevention with high precision.
Developed and optimized a built-in plagiarism detection system, enhancing exam security, data-driven decision-making, and compliance with academic standards.
Collaborated with cross-functional teams, including software engineers, data scientists, and UX designers, to refine user experience and scalability of the proctoring system.
Utilized SQL, Python, and data visualization tools to extract insights, track anomalies, and improve exam monitoring efficiency, reducing manual intervention and false positives.

Computer VisionDeep LearningArtificial Intelligence (AI)

Sopra steria

Machine Learning Engineer

Mar 2023 – Jun 2023 · 3 mos · Noida, Uttar Pradesh, India · Remote

Designed and deployed an advanced economic forecasting model, improving prediction accuracy by 15% and securing a top 5% ranking among 50+ interns.
Optimized and automated data preprocessing workflows, reducing manual effort by 20 hours per week, significantly enhancing operational efficiency.
Developed and implemented a sophisticated predictive model leveraging machine learning algorithms and economic indicators to analyze and forecast national economic trends.
Utilized Python (Pandas, NumPy, Scikit-learn), Time Series Analysis, and Statistical Modeling to derive actionable insights for strategic planning and decision-making.
Collaborated with data scientists and economists to refine model performance, improve feature selection, and enhance the interpretability of economic forecasts.

Time Series AnalysisData AnalysisMachine Learning