AI Machine Learning Engineer
Confirmed on the employer's own hiring board on Oct 20, 2026. First seen by Alion on Dec 4, 2025. Silver Bell Group scores C on the Alion truth index.
AI Engineer / Machine Learning Engineer
Role Overview
We are seeking a highly skilled AI Engineer / Machine Learning Engineer with deep expertise in building, optimizing, and deploying advanced AI systems. The ideal candidate has strong experience with LLM-based architectures, vector databases, distributed AI agents, and end-to-end machine learning lifecycle management.
Key Responsibilities
Design, develop, and deploy ML/DL models for production environments.
Build and optimize LLM-based systems including RAG pipelines, embeddings, and retrieval workflows.
Architect, implement, and maintain vector database solutions (Weaviate, Pinecone, Chroma, Qdrant).
Develop backend systems using FastAPI and microservice patterns.
Implement distributed AI agent systems and multi-agent orchestration.
Integrate ML models into full-stack applications (Python backend, Next.js frontend).
Oversee MLOps processes including model training, versioning, deployment, monitoring, and CI/CD integration.
Collaborate with product, data, and engineering teams to deliver scalable AI solutions.
Required Skills & Qualifications
ML / Deep Learning: Advanced expertise in training and deploying models.
LLM, RAG & Embeddings: Advanced proficiency with modern LLM frameworks and retrieval-augmented generation.
Vector Databases: Expert-level experience with Weaviate, Pinecone, Chroma, or Qdrant.
Backend Architecture: High-level proficiency with FastAPI, microservices, and modern API design.
Python & PyTorch: Strong development and deployment experience.
Next.js: Practical understanding of client/server communication and integration with AI backends.
Distributed AI Agents: Deep understanding of agent-based AI systems.
MLOps: Experience with model lifecycle management is a strong advantage.