AI/ML ENGINEER Role
3B Staffing LLC, Austin, TX, United States
Job title: AI/ML Engineer
It is critical that the candidate has solid experience in Classical ML, GenAI Fundamentals, Model Training, Agentic Frameworks, and FinTech Domain experience.
Minimum Qualifications
Education: Bachelor's degree in Computer Science, AI, Machine Learning, or equivalent.
Classical ML: 2+ years of experience building solutions using supervised/unsupervised learning, classification, recommendation systems, and clustering algorithms.
GenAI Fundamentals: In-depth knowledge of Transformer architecture, LLMs, and Agentic AI concepts.
Model Training: Hands-on experience fine-tuning Large Language Models (LLMs) using PEFT/LoRA for domain-specific tasks.
Agentic Frameworks: Proven experience building and extending RAG, MCP (Model Context Protocol), and multi-agent frameworks (e.g., LangChain, LlamaIndex, AutoGen).
Communication: Strong written and verbal communication skills with the ability to explain complex AI concepts to business stakeholders.
Preferred Qualifications
Master's degree in CS, specialized in AI/ML.
FinTech Experience: 3+ years deploying production-grade AI/ML solutions in the FinTech domain.
Advanced LLM Training: Experience with the full LLM lifecycle including pre-training, SFT, and Reinforcement Learning techniques (RLHF, PPO, GRPO).
Advanced Agentic Systems: 2+ years building conversational assistants or autonomous agents using advanced techniques (LangGraph, CrewAI, A2A, CoT, ReAct, Reflection).
Adaptability: Demonstrated ability to quickly master emerging AI tools and integrate them into legacy stacks.
It is critical that the candidate has solid experience in Classical ML, GenAI Fundamentals, Model Training, Agentic Frameworks, and FinTech Domain experience.
Minimum Qualifications
Education: Bachelor's degree in Computer Science, AI, Machine Learning, or equivalent.
Classical ML: 2+ years of experience building solutions using supervised/unsupervised learning, classification, recommendation systems, and clustering algorithms.
GenAI Fundamentals: In-depth knowledge of Transformer architecture, LLMs, and Agentic AI concepts.
Model Training: Hands-on experience fine-tuning Large Language Models (LLMs) using PEFT/LoRA for domain-specific tasks.
Agentic Frameworks: Proven experience building and extending RAG, MCP (Model Context Protocol), and multi-agent frameworks (e.g., LangChain, LlamaIndex, AutoGen).
Communication: Strong written and verbal communication skills with the ability to explain complex AI concepts to business stakeholders.
Preferred Qualifications
Master's degree in CS, specialized in AI/ML.
FinTech Experience: 3+ years deploying production-grade AI/ML solutions in the FinTech domain.
Advanced LLM Training: Experience with the full LLM lifecycle including pre-training, SFT, and Reinforcement Learning techniques (RLHF, PPO, GRPO).
Advanced Agentic Systems: 2+ years building conversational assistants or autonomous agents using advanced techniques (LangGraph, CrewAI, A2A, CoT, ReAct, Reflection).
Adaptability: Demonstrated ability to quickly master emerging AI tools and integrate them into legacy stacks.