Jr-to-Mid AI/ML Engineer – RAG Pipeline Development
About The Position
SimVentions is seeking a Junior/Mid-Level AI/ML Engineer specializing in Retrieval-Augmented Generation (RAG) to support the development of AI capabilities within an emerging MLOps platform. The engineer will help architect and implement reusable RAG pipelines that transform domain-specific documents and knowledge repositories into searchable, AI-enabled resources. The role will involve developing document ingestion and processing workflows, integrating embedding models and vector databases, implementing retrieval and LLM-based generation capabilities, and evaluating the quality and reliability of AI-generated responses. The engineer will work alongside software developers, AI/ML engineers, and systems architects to integrate these capabilities into a scalable, secure platform supporting multiple customer projects.
Requirements
- Hands on experience with software development languages like GO, Python, Javascript, and Vue.js
- Understanding of data storage and retrieval utilizing databases, S3 storage containers and/or VAST storage environments
- Entry/Foundational knowledge of ML concepts, intelligent automation capabilities, and the ML model lifecycle (training, validation, deployment, monitoring)
- Understanding on the utilization of CPU and GPU for Machine Learning and Model Training
- Experience with integrating open source, commercial, and internally developed toolsets using Software Development Kits (SDKs) and Application Programming Interfaces (APIs)
- An interim Secret Clearance is required for this position.
- US Citizenship is required to obtain a clearance.
Nice To Haves
- Familiarity or experience with components of a RAG pipeline for domain-based knowledge queries
- Familiarity with Docker and containerized applications
- Familiarity with MongoDB, PostgressSQL, and common SQL and Graph database interactions
Responsibilities
- Work within the current development environment and toolsets to expand and enhance automation capabilities within the Machine Learning Operations (MLOPS) ecosystem.
- Automate model training processes to allow efficient repeatability.
- Utilize data and model requirements to design architecture to scale.
- Inject configuration management of the data sources and model output.
Benefits
- Medical, dental, vision, and prescription drug coverage
- Employee Stock Ownership Plan (ESOP)
- Competitive 401(k) programs
- Retirement and Financial Counselors
- Health Savings and Health Reimbursement Accounts
- Flexible Spending Accounts
- Life insurance, short- & long-term disability
- Continuing Education Assistance
- Paid Time Off, Paid Holidays, Paid Leave (e.g., Maternity, Paternity, Jury Duty, Bereavement, Military)
- Third Party Employee Assistance Program that offers emotional and lifestyle well-being services, to include free counseling
- Supplemental Benefit Program
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Entry Level
