Maneesh Disodia
ML 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 Architect | GenAI | LLMOps | MLOps | AIOps | Ericsson | HCLTech | M.TECH
AI Researcher & Engineer | 12 years building production ML systems. 4 years in GenAI — from PoC to full-scale production deployment.Currently architecting e2e agentic workflows and multi-agent systems — designing agent coordination pipelines using LangGraph, Google ADK, A2A protocol, and Claude SDK to deliver production-grade solutions across retail and enterprise domains.Core focus areas:→ Multi-agent orchestration & e2e production agentic systems→ LLM-powered search, RAG, and intelligent catalog systems→ MLOps/LLMOps — model versioning, experiment tracking (MLflow), CI/CD for AI→ AIOps & real-time prediction frameworksResearch interests:→ Model finetuning — PEFT, LoRA, QLoRA for domain-specific LLMs→ LLM evaluation — benchmarking, hallucination detection, task-specific metrics→ Multi-agent coordination patterns & agentic reasoning→ Applied NLP, computer vision, and SLAM (M.Tech research @ DTU)Tech: Python, PyTorch, TensorFlow, LangChain, LangGraph, Claude SDK, ADK, MLflow, Kubernetes, GCPOpen to collaborations on agentic AI, LLM research, and production-scale AI systems.
Delhi Technological University (Formerly DCE)
Master of Technology - MTech, Information Technology
January 1, 2012 – January 1, 2014
Kurukshetra University
Bachelor of Technology - BTech, Computer Engineering
January 1, 2007 – January 1, 2011
Kendriya Vidyalaya
High School, Physics, Mathematics
January 1, 1995 – January 1, 2007
Altimetrik
Principal Engineer AI
September 1, 2024 – Present
India · Hybrid
HCL Technologies
Senior Data Scientist
October 1, 2021 – September 1, 2024
India · On-site
Ericsson
Data Scientist
February 1, 2019 – October 1, 2021
India
Aurum Analytica
Data Science Manager
January 1, 2018 – February 1, 2019
Noida · On-site
Startup
Bigfish Benefits
October 1, 2015 – December 1, 2017
On-site
Startup
DGM India
June 1, 2014 – October 1, 2015
On-site
NASA lunabotics excavators
April 1, 2013 – May 1, 2014
As a Team Leader, to design an autonomous robot to excavate Lunar Surface, its a challenging task for me. my work is to design an artificial intelligence based program to operate this robot. to pursue my goals I used various technologies like embedded c, Matlab, and Simulink. all decision-based diagram are built by me and my team. all communication setup and control hardware are based on open hardware and software. we are using ROS as a base and OpenNi as an open SDK
Professional Cloud Architect
Google Cloud
June 24, 2026 – Present
Structuring Machine Learning Projects
DeepLearning.AI
June 24, 2026 – Present
Exploring and Preparing your Data with BigQuery
Coursera
June 24, 2026 – Present
Machine Learning Fundamental Level
Ericsson
June 24, 2026 – Present
Professional Machine Learning Engineer
June 24, 2026 – Present
Ericsson Machine Learning Experienced
Ericsson
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
DeepLearning.AI
June 24, 2026 – Present
Google Cloud Platform Fundamentals: Core Infrastructure
Coursera
June 24, 2026 – Present
Python for Data Science and Machine Learning Bootcamp
Udemy
June 24, 2026 – Present
Neural Networks and Deep Learning
DeepLearning.AI
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has worked across various companies, from startups to large enterprises (Altimetrik, HCL, Ericsson), indicating adaptability to different organizational cultures. The project diversity, including autonomous robotics, retail analytics, network monitoring, and HR tech, suggests a broad interest and ability to apply ML/AI in different domains. The target role of ML Engineer aligns well with the candidate's extensive experience in ML/AI development and deployment. However, the 'NASA lunabotics excavators' project, while impressive, is a personal project and its direct relevance to corporate cultural fit is indirect.
Soft Skills & Operational Fit
The candidate's project descriptions indicate experience in team leadership and decision-making (e.g., 'Team Leader' for NASA project, 'all decision-based diagram are built by me and my team'). The roles held, such as Principal Engineer AI and Data Science Manager, suggest strong problem-solving and project management capabilities. However, without specific psychometric test results or interview data, a detailed assessment of soft skills and operational fit is limited.