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Builds and operates AI-powered backend pipelines (LLM/STT) for a construction intelligence platform, focusing on non-determinism, reliability metrics, and scalable cloud services.
Designs and maintains scalable Azure-based data pipelines and platforms for government datasets, enabling AI/ML and analytics. Builds ETL/ELT workflows using tools like ADF, Databricks, Spark, Kafka, and SQL, collaborating with data scientists and MLOps teams.
Hands-on AI Architect designing and deploying production-grade Generative AI systems (LLMs, RAG pipelines, chatbots) on AWS for enterprise clients, working onsite 3 days/week in Raleigh.
Leads AI/ML projects from ideation to production, specializing in LLM/Agentic AI development, cloud-based model deployment, and MLOps best practices for fintech applications.
Build and optimize AI/ML models for computer vision tasks using TensorFlow/PyTorch, deploying scalable solutions on AWS with CI/CD pipelines.
AI Architect leading complex, high-scale system design and architectural decisions while mentoring cross-functional teams, using AI/ML frameworks, Python, cloud platforms (AWS/Azure), and DevOps practices.
Lead AI/ML Engineer architecting mission-critical AI/ML systems at scale using deep learning, LLMs, RAG, and cloud platforms (AWS/GCP/Azure) in a hybrid role based in Coimbatore.
Lead AI Engineer architecting and delivering end-to-end AI solutions—classical ML, deep learning, LLMs, multimodal systems, and MLOps—while mentoring a team of AI/ML engineers, based in Pune.
Builds and maintains scalable ML pipelines for model training, deployment, and monitoring, collaborating with data scientists and engineers to optimize AI workflows and cloud infrastructure.
Develop and maintain AI-driven conversational systems and chatbots while advising customers on GenAI/ML best practices, using Python, JavaScript/TypeScript, LLM frameworks (LangGraph, Llamaindex, DSPy), and major cloud platforms (AWS, Azure, GCP).
Freelance AI Solutions Engineer owning end-to-end feature development, collaborating with product/design, and mentoring juniors on a remote team. Core tech includes Python, cloud platforms (AWS/Azure/GCP), LLM/GenAI frameworks, and MLOps.
Build and deploy AI-powered features using Python, React, and ML frameworks like TensorFlow/PyTorch, collaborating with product teams to ship scalable GenAI applications.
Build and maintain production AI and data infrastructure on Palantir Foundry/AIP using TypeScript, Python, PySpark, and React as a remote forward deployed engineer working directly with customer teams.
Build and deploy AI/ML models (LLMs, RAG, NLP, generative AI) on a large-scale platform using Python, TensorFlow, Scikit-learn, and AWS, with full MLOps and data engineering responsibilities.
Lead the design and implementation of a large-scale AI/ML platform focused on intelligent automation, predictive analytics, NLP, and generative AI using Python, LLMs, RAG, AWS, TensorFlow, and MLOps in a fully remote freelance role.
Design and implement scalable AI architectures, collaborating with cross-functional teams to drive innovation and efficiency using technologies like AWS Bedrock, SageMaker, Azure OpenAI, Vertex AI, Python, PyTorch, and RAG.
Leads AI-driven product initiatives and the product lifecycle from conception to launch, collaborating with cross-functional teams using agile methodologies and technologies like Generative AI, LLMs, and cloud AI platforms.
Lead MLOps strategy and production ML system deployment for an AI company, defining multi-year technical roadmaps, architecting scalable systems, and establishing engineering standards—onsite in Delhi.
An MLOps Engineer leads technical initiatives, designs scalable ML systems, and mentors teams to implement end-to-end ML workflows using AWS/Azure, Kubernetes, and MLOps tools like MLflow and Kubeflow.
Design and deploy ML systems (CNN, RNN, LSTM), optimize MLOps pipelines, and run distributed training using Spark and Kubernetes in a fully remote, short-term contract role.
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