Ankan Pal
AI EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Engineer with 1+ years in Generative AI, LLMs & Machine Learning.
Results-driven AI/ML Engineer with 16+ months of hands-on industry experience designing and deploying production-grade Generative AI systems, LLM pipelines, RAG architectures, and multi-agent frameworks. Proven track record building real-world AI applications from intelligent multi-model coding assistants to industrial predictive maintenance systems deployed across 5 to 7 manufacturing plants, monitoring around 100 sensors with 95%+ model accuracy. Skilled in end-to-end AI product development from requirements and prototyping through cloud deployment on GCP (Vertex AI) and production monitoring.
University of Engineering & Management (UEM), Kolkata
B.Tech · Computer Science & Engineering
August 1, 2021 – June 30, 2025
IEMA Research & Development Pvt. Ltd.
System Analyst AI/ML
September 1, 2025 – Present
Kolkata, West Bengal, India
IEMA Research & Development Pvt. Ltd.
AI Engineer Intern
March 1, 2025 – August 31, 2025
India
iema.ai AI Coding Assistant & Generative AI Platform
March 1, 2025 – June 1, 2026
• Multi-Model LLM Orchestration: Built a unified AI backend integrating OpenAI GPT models and Google Gemini (Vertex AI), enabling seamless provider switching without frontend modifications. • AI Coding Assistant: Developed scalable backend services powering an intelligent coding assistant with conversational AI workflows, code generation, and production-grade API architecture. • AI Image Generation Platform: Engineered image-generation services using Google Vertex AI Imagen models with prompt presets, aspect-ratio customization, cloud storage integration, and real-time image delivery. • AI Video Generation Platform: Built production-grade text-to-video generation services using Veo 3, supporting multiple resolutions, customizable aspect ratios, cinematic camera-angle controls, and style presets including Realistic, Anime, Cartoon, and Artistic modes. • AI Email Assistant: Developed configurable email-generation pipelines with tone control, creativity tuning, keyword-guided generation, readability optimization, and automated feedback collection. • Educational AI Assistants: Designed and deployed Gemini-powered Physics, Chemistry, and General-purpose AI tutors with domain-specific prompting and response orchestration. • Multilingual Transliteration: Implemented real-time phonetic transliteration for 5+ Indian languages (Bengali, Hindi, Tamil, Telugu, Kannada), improving accessibility for regional users. • Billing, Credits & Feedback Engine: Engineered token-based credit deduction, usage tracking, and multi-signal feedback loops to continuously improve AI service quality. • Cloud Infrastructure: Deployed and scaled the platform on GCP using Vertex AI, Cloud Run, and Firebase services, delivering low-latency inference and production-grade reliability.
Predictive Maintenance on Asset Health Monitoring (AHM)
March 1, 2025 – June 1, 2026
• Multi-Plant Deployment: Deployed across 5 to 7 industrial plants, each with 1020 sensors per motor; models calibrated per plant using site-specific sensor weightings to maintain 95%+ prediction accuracy across all deployments. • Forecasting Model: Designed and trained multiple models on multi-sensor time-series data; achieves 95%+ prediction accuracy with plant-specific model weights ensuring robust performance across varying industrial environments. • Anomaly Detection Engine: Built a multi-threshold anomaly detection pipeline with gap-merging and fault period reporting, significantly reducing false positive alerts vs. single-metric approaches. • Analytics Dashboard: Delivered an interactive real-time dashboard visualising live sensor trends, RUL trajectory, anomaly events, and health zone transitions across all monitored assets. • Cloud & Scale: Entire pipeline deployed on cloud with production-grade API endpoints serving multiple plant sites simultaneously; supports real-time sensor ingestion and on-demand RUL inference.
Cultural Fit Analysis
The candidate's project portfolio showcases a strong alignment with an AI Engineer role, particularly in Generative AI and ML system deployment. The diversity of projects, from coding assistants to industrial predictive maintenance and educational AI, indicates adaptability and a broad interest in applying AI across different domains. Their experience with multi-plant deployments and multilingual transliteration suggests an ability to work with diverse requirements and user bases. The rapid promotion within their current company also points to a proactive and high-performing individual who can integrate well into a technically demanding environment.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative and technical ownership, evidenced by their promotion from intern to full-time within six months. Their project descriptions highlight problem-solving skills (e.g., reducing false positives in anomaly detection, achieving high prediction accuracy across diverse environments) and an ability to deliver robust, scalable solutions. The focus on user feedback loops and multilingual support indicates a user-centric approach. However, without specific psychometric or English test scores, a deeper assessment of communication clarity, work attitude, stress handling, and team collaboration is not possible.