AI Solutions Architects
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Design scalable AI ecosystems with AI Solutions Architects who connect models, infrastructure, and business goals into production-ready solutions.
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Recently Added AI Solutions Architects in our Network
Aakash Bhardwaj
Senior AI Consultant7.25 Years of Exp• React Native
• Docker
• Kubernetes
• LangChain
• Microservices
• Node.js
Aakash has hands-on experience working as a Front-end Developer for 5 years. He is well-versed in WebRTC,JavaScript,HTML,Python,Java,C++ and more. He possesses the qualities of a hardworking and ambitious person who has a knack for learning new things. He always stays on top of trends and technologies.
Sarat Kumar Manugula
AI Solutions Architect9.3 Years of Exp• Automated Testing
• CI/CD
• machine_learning
• MLFlow
• model tracking
Offering over 8+ years of experience in Information technology and software development field focusing on and Machine Learning, Deep Learning ,NLP and Gen AI in Mechanical Domain, Medical, BFSI
Niraj Kale
Lead Data Scientist | AI Solutions Architect11.33 Years of Exp• Cost optimizations
• Deployment
• Full-stack Engineering
A motivated professional specializing in Machine Learning, GenAI and Full-stack engineering with over 10+ years of hands-on experience and expertise in building robust, scalable enterprise-grade products covering system design, development, infrastructure setup, and deployment.
Debanka
AI Solutions Architect15 Years of Exp• GenAI
• Problem Solving
• Python
• Bss solution design
• AWS
I have spent 15+ years in the software world, and in the last few years my focus has shifted fully into Artificial Intelligence and Machine Learning. Today, as an AI/ML Architect at Ignite AI, I design and build intelligent systems that turn ambitious ideas into real, production-grade solutions.At Ignite AI I work end to end across architecture, research, and implementation. Some of the things I have been building recently:1. DynaTune Lite and DynaTune Enterprise – a no-code LLM fine-tuning framework that automates model selection, LoRA/QLoRA/full fine-tuning strategy, GPU sizing and cost estimation, with both "Auto" and "Expert" modes for teams.2. A Mixture of Recursions (MOR) model, inspired by modern small-model architectures, to get GPT-like behavior in compact, efficient models that are cheaper to serve.3. A hybrid AI search stack that fixes the limitations of vanilla Elastic based keyword search, combining vector search, query understanding and ranking to handle noisy, real user queries.4. A generic time-series recommendation and anomaly detection engine that can plug into ARIMA, NeuralProphet, Google TimesFM and similar models to surface trends, forecasts and anomalies across any tabular business data.
Shanky Sharma
AI Solutions Architect8.58 Years of Exp• AWS
• Dask
• Docker
• GenAI
• GPU
• Hive
• Iguazio
• JavaScript
• Kubeflow
• LLMs
With over a decade of experience in data science and machine learning, I specialize in building intelligent, efficient systems that bridge the gap between software and hardware.Currently serving as a Machine Learning lead at Lattice Semiconductor, where I focus on developing and optimising AI models for edge deployment. My work involves neural network quantisation, model compression, and performance tuning to meet the constraints of embedded systems - enabling powerful machine learning capabilities on resource-limited hardware.Throughout my career, I’ve worked across diverse domains, consistently applying a deep technical skill set to solve real-world problems. I’m passionate about pushing the boundaries of edge AI through rigorous engineering, cross-functional collaboration, and a relentless drive for practical innovation.
Soumyadip Bhattacharyya
AI Solutions Architect5.25 Years of Exp• Python
• PyTorch
• Keras
• Hugging Face
• PySpark
• R
• SQL
• AWS
• Bash
• Blip-2
I am passionate data scientist with nearly years of experience in building data intensive applications in Banking Sector. Business problems solved by me along with my team are running in production with desired accuracy. Developed Yes/No model to accelerate Retail SME (RSME) loan growth with new digital end-to-end experience and real-time approvals. Worked on Sampling, Segmentation, Unsupervised Clustering, Feature Engineering, EDA, Model Developement, Validation, Backtesting, Postmortem, Explainability etc. Created Limit Model of RSME to set maximum amount of loans to approved using time series clustering and neural network. Amount of loan disbursed till date is 1.7 Billon RM. Developed Neural Network Model on Keras which can target existing customers and entities that have higher propensity to buy products like Loan, Credit Card etc.
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