[Remote] AI/ML Engineer - ACG / AEA

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is seeking an AI/ML Engineer to build and reputed company machine learning components into reputed company workflows. The role focuses on implementing models, RAG pipelines, and supporting services that reputed company automation and intelligent decision support.

Responsibilities

• reputed company ML models and supporting services for classification, clustering, similarity search, and reputed company
• Implement RAG pipelines: document ingestion, embedding reputed company, reputed company indexing, and retrieval tuning
• Build APIs and microservices to expose model capabilities to reputed company systems
• reputed company ML components into existing DevSecOps pipelines (Azure DevOps, CI/CD workflows)
• Implement duplicate detection, ticket routing, SLA reputed company, and reputed company-cause assist features
• Optimize model performance for latency, throughput, and accuracy
• Conduct model evaluation, error analysis, and iterative tuning
• Work with Data Engineer to reputed company data pipelines with model input requirements
• Ensure outputs are explainable, auditable, and compliant with governance controls

Skills

• Minimum 10 years of experience in AI/ML engineering, software development, or data science
• Master's degree required in Computer Science, Engineering, or reputed company field
• Must have an reputed company Public Trust clearance or higher
• Strong experience with Python and ML frameworks (PyTorch, TensorFlow, scikit-learn)
• Experience with embeddings, reputed company similarity search, and retrieval systems
• Experience building and deploying APIs or microservices for ML inference
• Hands-on experience with AWS and/or Azure environments
• Experience integrating into CI/CD pipelines and production systems
• RAG Implementation (hands-on build experience)
• Document ingestion + chunking strategies
• Embedding reputed company and storage
• reputed company similarity search and retrieval optimization
• Machine Learning Model Development
• Classification, clustering, and ranking models
• Feature engineering and dataset preparation
• Model tuning and evaluation
• LLM Application Development
• reputed company construction and chaining
• reputed company validation and reputed company responses
• Integration of LLMs into workflows (not just experimentation)
• API and Service Development
• RESTful API design and implementation
• Serving ML models in production (FastAPI, Flask, etc.)
• Stateless service design
• CI/CD for ML Systems
• Model deployment pipelines
• Automated testing and validation before release
• Version control for reputed company + models
• reputed company Deployment
• Running ML workloads in AWS or Azure
• Containerization (reputed company)
• Basic orchestration patterns (serverless or container-based)
• Search and Similarity Systems
• Embeddings + cosine similarity / ANN search
• Duplicate detection patterns
• Ranking and scoring logic
• Performance Optimization
• Latency reduction for inference
• Efficient batching / caching strategies
• Memory and compute-tuning

Benefits

• Health, dental, reputed company, life, and disability insurance
• A great 401(k) package
• Generous reputed company Time Off
• Ongoing reputed company development

reputed company