- Company Name
- Open Systems Inc.
- Job Title
- Entry-Level ML/AI Engineer (Only USC)
- Job Description
-
Job title: Entry‑Level ML/AI Engineer
Role Summary: Design, build, and deploy AI solutions focused on large language models (LLMs), agentic pipelines, and Retrieval‑Augmented Generation (RAG). Enable automation of engineering workflows, knowledge retrieval, and decision support through advanced NLP and orchestration frameworks.
Expections: Construct end‑to‑end systems that integrate LLMs with vector databases, develop multi‑agent pipelines, fine‑tune models on proprietary data, and monitor performance while ensuring privacy, compliance, and cost efficiency.
Key Responsibilities:
- Architect AI‑driven workflows using LLMs (Azure OpenAI, Claude, Llama, Mistral, Gemini).
- Develop agentic pipelines and chain‑of‑thought systems via LangChain, LlamaIndex, Semantic Kernel, Haystack, or CrewAI.
- Implement RAG solutions with vector stores (Pinecone, Weaviate, FAISS, ChromaDB, Elasticsearch) for document analysis and Q&A.
- Fine‑tune, deploy, and monitor LLMs on private datasets, applying guardrails and synthetic data when necessary.
- Evaluate and integrate emerging AI tools, APIs, and infrastructure, including LLMOps, prompt management, and orchestration frameworks.
- Optimize AI pipelines for latency, cost, reliability, and scalability in production.
- Document design decisions, model behavior, and compliance measures; communicate with cross‑functional teams.
Required Skills:
- Python programming; libraries: Transformers, Hugging Face, FastAPI, Pydantic.
- Prompt engineering, model selection, fine‑tuning, and performance evaluation.
- Experience with agentic pipelines and workflow automation (LangChain, LlamaIndex, Semantic Kernel, Haystack).
- RAG design, vector DB management, chunking, and search optimization.
- Knowledge of multimodal AI, knowledge graphs, and semantic search.
- MLOps/LLMOps fundamentals; cloud deployment (Azure ML, AWS SageMaker, GCP Vertex AI) preferred.
- Strong analytical, research, and documentation skills; ability to thrive in fast‑paced, collaborative settings.
Required Education & Certifications:
- Bachelor’s, Master’s, or PhD in Computer Science, Artificial Intelligence, or related field.
- Relevant AI/ML certifications (e.g., Microsoft Certified: Azure AI Engineer Associate, AWS Certified Machine Learning – Specialty) are a plus.