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Lead Machine Learning Engineer with extensive experience architecting and deploying enterprise-grade AI solutions, specializing in Agentic AI, Virtual Agents, and Generative AI systems. Proven ability to lead cross-functional teams delivering production-ready LLM applications using advanced MLOps practices across the full ML lifecycle. Skilled in Python and transformer-based architectures (BERT/GP T/T5 family), performance optimization with CUDA/Triton, and scalable cloud-native deployment with Docker/Kubernetes. Experienced building RAG systems, autonomous multi-step AI agents, and ML evaluation/CI/CD pipelines for reliable, reproducible model operations.…Lead Machine Learning Engineer with extensive experience architecting and deploying enterprise-grade AI solutions, specializing in Agentic AI, Virtual Agents, and Generative AI systems. Proven ability to lead cross-functional teams delivering production-ready LLM applications using advanced MLOps practices across the full ML lifecycle. Skilled in Python and transformer-based architectures (BERT/GP T/T5 family), performance optimization with CUDA/Triton, and scalable cloud-native deployment with Docker/Kubernetes. Experienced building RAG systems, autonomous multi-step AI agents, and ML evaluation/CI/CD pipelines for reliable, reproducible model operations.

Manny Ahmed

Developer, AI Engineer, Web Developer, +3

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Lead Machine Learning Engineer with extensive experience architecting and deploying enterprise-grade AI solutions, specializing in Agentic AI, Virtual Agents, and Generative AI systems. Proven ability to lead cross-functional teams delivering production-ready LLM applications using advanced MLOps practices across the full ML lifecycle. Skilled in Python and transformer-based architectures (BERT/GP T/T5 family), performance optimization with CUDA/Triton, and scalable cloud-native deployment with Docker/Kubernetes. Experienced building RAG systems, autonomous multi-step AI agents, and ML evaluation/CI/CD pipelines for reliable, reproducible model operations.…Lead Machine Learning Engineer with extensive experience architecting and deploying enterprise-grade AI solutions, specializing in Agentic AI, Virtual Agents, and Generative AI systems. Proven ability to lead cross-functional teams delivering production-ready LLM applications using advanced MLOps practices across the full ML lifecycle. Skilled in Python and transformer-based architectures (BERT/GP T/T5 family), performance optimization with CUDA/Triton, and scalable cloud-native deployment with Docker/Kubernetes. Experienced building RAG systems, autonomous multi-step AI agents, and ML evaluation/CI/CD pipelines for reliable, reproducible model operations.

Available to hire

Lead Machine Learning Engineer with extensive experience architecting and deploying enterprise-grade AI solutions, specializing in Agentic AI, Virtual Agents, and Generative AI systems. Proven ability to lead cross-functional teams delivering production-ready LLM applications using advanced MLOps practices across the full ML lifecycle.

Skilled in Python and transformer-based architectures (BERT/GP T/T5 family), performance optimization with CUDA/Triton, and scalable cloud-native deployment with Docker/Kubernetes. Experienced building RAG systems, autonomous multi-step AI agents, and ML evaluation/CI/CD pipelines for reliable, reproducible model operations.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Language

English

Advanced

Work Experience

Lead Machine Learning Engineer at Klarity Labs

January 1, 2021 - Present

Architected and deployed a virtual AI agent for customer service, leveraging multilingual NLP and fine-tuned transformer models to understand and resolve queries across multiple languages. Led the design and implementation of AI agents for anomaly detection over operational KPIs, enabling real-time monitoring, autonomous issue flagging, and root-cause analysis in cloud infrastructure. Built and productionized scalable virtual agents for text classification and information extraction, including end-to-end ETL and model orchestration pipelines with automated drift detection and seamless retraining. Developed modular LLM evaluation tooling for automated prompt engineering and rigorous performance/safety standards. Implemented performance optimization for real-time inference and engineered production ML APIs with FastAPI, Docker, and Kubernetes. Drove MLOps best practices by establishing robust CI/CD pipelines for model packaging, validation, and deployment on AWS and GCP.

Lead Machine Learning Engineer - Orchestrator at Klarity Labs

January 1, 2021 - Present

Architected and led development of an agentic AI platform for autonomous enterprise support resolution. Implemented Now Assist technologies for real-time guidance to human agents. Designed and deployed scalable virtual agents for financial document analysis using RAG over FAISS and Pinecone. Built modular LLM evaluation frameworks for prompt engineering automation and multi-run experiment tracking with MLflow/Weights & Biases. Optimized transformer inference using parameter-efficient fine-tuning (PEFT) and quantization (LoRA/QLoRA). Engineered high-performance ML APIs (FastAPI) and containerized services with Docker/Kubernetes. Established CI/CD pipelines for model packaging, validation, and deployment to AWS and GCP; reduced GPU inference latency via profiling and kernel-level optimization.

Senior Machine Learning Engineer at Cognitive Scale

July 1, 2019 - December 1, 2020

Established ML best practices including rigorous version control, documentation, reproducible codebases, and robust unit testing. Led development of a multilingual virtual agent using fine-tuned transformer models (BERT, XLNet). Designed and implemented AI agents for anomaly detection across operational KPIs with real-time data stream monitoring and root-cause analysis. Built large-scale text classification services using TensorFlow Serving and Flask. Developed end-to-end ETL and model orchestration pipelines using Apache Airflow and Docker with drift detection for seamless retraining. Built automated workflows for transfer learning and improved domain adaptation efficiency. Collaborated with product and engineering stakeholders to define ML problem statements and success metrics.

Machine Learning Engineer at Sofi

June 1, 2017 - June 1, 2019

Developed time-series forecasting models using LSTM and GRU networks to predict market trends and optimize investment strategies. Built and deployed an NER system using spaCy and Hugging Face transformers for information extraction from legal/financial documents, automating data entry and processing workflows. Created interactive dashboards and reports using Tableau and Plotly for executive reporting. Implemented data governance and lineage frameworks to ensure compliance with financial regulations and data quality standards.

Data Scientist at Upstart

August 1, 2015 - May 1, 2017

Developed data-driven ML systems, focusing on extracting structured signals from large datasets and building production-ready pipelines. (Resume content emphasizes early-career ML engineering/data science contributions and governance practices.)

Data Scientist Technical at Upstart

August 1, 2015 - May 1, 2017

Created systems and pipelines related to NLP and credit-risk decisioning. Built an end-to-end credit risk assessment system to process borrower financial data and automate underwriting decisions and personalized loan offers.