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Job Title: AI/ML Engineer – LLM Platform & Model Management (AWS/GCP)
Experience: 5+ Years
Location: Remote (Aligned with U.S. Working Hours)
Job Summary
We are seeking a highly skilled AI/ML Engineer with strong expertise in LLM platforms, MLOps, and cloud-based model management. The ideal candidate will have hands-on experience in deploying, scaling, and optimizing machine learning models across AWS and GCP environments, with a key focus on migrating workloads from Google Vertex AI to Amazon SageMaker.
You will play a critical role in building scalable LLM-driven systems, implementing multi-model orchestration, and designing AI-powered document processing
pipelines.
Key Responsibilities
Model Management & Deployment
• Design, deploy, and manage ML models using Amazon SageMaker
• Lead migration of ML workloads from Google Vertex AI to AWS
• Implement model versioning, monitoring, and lifecycle management
• Build scalable real-time and batch inference pipelines
• Optimize model performance, latency, and cost
LLM Integration & Optimization
• Integrate and manage LLM APIs (e.g., Gemini, Claude, Llama, Titan)
• Develop multi-model routing strategies and fallback mechanisms
• Benchmark models based on accuracy, latency, and cost efficiency
• Optimize prompt engineering and inference workflows
API Gateway & LLM Orchestration
• Deploy and configure LiteLLM as a unified LLM gateway
• Enable seamless switching across multiple LLM providers
• Design and expose scalable AI APIs for enterprise applications
Cloud Infrastructure & Security
• Build and deploy containerized applications using:
o Amazon ECS Fargate o Kubernetes (EKS preferred)
• Manage secure access using AWS IAM roles and policies
• Ensure high availability, scalability, and security compliance
Document Processing & AI Workflows
• Build pipelines for:
o Document extraction o Summarization o Classification
• Design and implement RAG-based architectures and semantic search systems
• Optimize performance for large-scale document processing workloads
Required Qualifications
• Bachelor's or Master's degree in Computer Science, Data Science, or related field • 5+ years of experience in AI/ML and MLOps • Strong hands-on experience with:
o AWS SageMaker o Google Vertex AI
• Proven experience with LLMs and Generative AI platforms
• Proficiency in containerization and distributed systems
Core Skills
• MLOps & LLMOps
• Model Deployment, Monitoring & Versioning
• API Integration & Gateway Design
• Cloud Platforms: AWS & GCP
• Microservices & Scalable Architecture
Intrested Candidates Send your Updated Resume to [Confidential Information]/[HIDDEN TEXT]
Job ID: 145635979
Skills:
prognostics , Ml, Power Bi, Tableau, Sql, Nosql, Tensorflow, Numpy, Pytorch, Pandas, MLops, Matlab, Python, Kalman Filter, Data Lakes, scikit-learn, Diagnostics, Ai, Simulink, anomaly detection, GoJS, Predictive Maintenance, Federated Learning
Skills:
prophet , Power Bi, Tableau, Sql, Deep Learning, Azure ML, Arima, Python, Machine Learning Algorithms, LSTM, ML libraries, MLOps platforms, AI systems, Classification, database structures, data visualization tools, DataRobot, ensemble methods, Abacus.ai, ML pipelines, Regression, time series forecasting
Skills:
Machine learning frameworks, Model Deployment, Model Lifecycle Management, ML Pipeline Development, Machine Learning Operations, Cloud AI services, Multi Cloud skills, Monitoring Optimization
Skills:
Machine Learning, Azure ML, Data Science, MLops, Azure Functions, Docker, Terraform, Nestjs, Kubernetes, Python, LangChain, Applied AI, Azure OpenAI, CI CD, LLM Integration, Recommendation Systems, RAG Retrieval-Augmented Generation, API-based Integrations, Scalable ML Pipelines, OpenAI
Skills:
Sqlalchemy, Tokens, FastAPI, Python, embeddings, Alembic, Hugging Face, LIWC, context engineering, Classification, prompt engineering, ML AIOps, embedding-based similarity models, NLP pipelines, Regression, AWS SageMaker, CI CD pipelines, BERT, Bag of Words
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