RAG AI/ML Engineer: Build Scalable Knowledge Pipelines

Simvention

Dahlgren (VA)

Vor Ort

USD 79.000 - 140.000

Vollzeit

Vor 5 Tagen
Sei unter den ersten Bewerbenden

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Benefits dieser Stelle

ESOP
Competitive 401(k) programs
Continuing Education Assistance
Paid Time Off
Family-friendly environment

Zusammenfassung

SimVentions seeks a Junior/Mid-Level AI/ML Engineer specializing in Retrieval-Augmented Generation (RAG) to architect reusable pipelines transforming domain documents into searchable AI resources. You will ingest data, integrate embeddings and vector stores, and enable LLM-based generation within a scalable MLOps platform.

The role collaborates with software and systems teams, requires security clearance eligibility, and offers ESOP and comprehensive benefits. Minimal travel.

Qualifikationen

  • Hands on experience with Go, Python, JavaScript and Vue.js.
  • Understanding of data storage and retrieval using databases, S3 and/or vector storage.
  • Foundational knowledge of ML concepts and lifecycle (training, validation, deployment).
  • Familiarity with CPU/GPU use for ML and model training.
  • Experience assembling tools via SDKs and APIs from open source, commercial, and in-house sources.

Aufgaben

  • Expand and enhance automation within the MLOps ecosystem.
  • Automate model training processes for repeatable workflows.
  • Design scalable architecture based on data/model requirements.
  • Inject configuration management for data sources and model outputs.

Kenntnisse

Go
Python
JavaScript
Vue.js
Databases
S3 storage
Vector databases
ML concepts
CPU/GPU ML
SDKs & APIs
Docker

Ausbildung

Bachelor's degree in engineering, science or technical discipline

Tools

MongoDB
PostgreSQL
SQL
Graph databases

Jobbeschreibung

SimVentions seeks a Junior/Mid-Level AI/ML Engineer specializing in Retrieval-Augmented Generation (RAG) to architect reusable pipelines transforming domain documents into searchable AI resources. You will ingest data, integrate embeddings and vector stores, and enable LLM-based generation within a scalable MLOps platform.

The role collaborates with software and systems teams, requires security clearance eligibility, and offers ESOP and comprehensive benefits. Minimal travel.

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