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Revature

Senior Trainer – Artificial Intelligence & Machine Learning

Revature, Dallas, Texas, United States, 75215

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Senior Trainer – Artificial Intelligence & Machine Learning About the Role We are seeking a passionate and technically strong

Senior Trainer - Artificial Intelligence & Machine Learning

to deliver our advanced AI curriculum focused on LLMs, Retrieval‑Augmented Generation (RAG), Agentic AI, and end‑to‑end deployment.

The ideal candidate will have a deep understanding of modern AI architectures and the ability to mentor learners in building autonomous, production‑grade AI systems — integrating retrieval pipelines, intelligent agents, and deployment workflows across real‑world scenarios.

About Revature Revature is one of the largest and fastest‑growing employers of technology talent across the U.S., partnering with Fortune 500 companies, leading System Integrators, and Government Contractors to identify experienced professionals who can be effective leaders.

Key Responsibilities

Deliver

engaging, project‑based sessions

on advanced topics in

AI, LLMs, and agentic AI development .

Train and mentor learners on:

Core AI/ML concepts:

supervised & unsupervised learning, deep learning, and NLP.

Large Language Models (LLMs):

transformer architecture, fine‑tuning, and prompt optimization.

Retrieval‑Augmented Generation (RAG):

vector databases, document retrieval, embeddings, and knowledge‑grounded responses.

Agentic AI Systems:

Designing and orchestrating

AI agents

capable of autonomous decision‑making.

Using

LangGraph ,

CrewAI , or

AutoGen

for

multi‑agent frameworks .

Integrating external tools, APIs, and reasoning loops for

dynamic task execution .

Understanding

memory management ,

context persistence , and

tool use

in agent frameworks.

AI Deployment & MLOps:

Building scalable APIs with

FastAPI

or

Flask .

Model packaging and orchestration with

Docker ,

Kubernetes , and

CI/CD pipelines .

Model tracking, experimentation, and monitoring with

MLflow ,

Weights & Biases , or

Vertex AI Pipelines .

Cloud AI Integration:

deploying and managing systems on

AWS (SageMaker) ,

Azure ML , or

GCP Vertex AI .

Lead

hands‑on projects

where learners build

RAG‑based chatbots ,

autonomous AI assistants , and

deployed LLM applications .

Collaborate on curriculum development to integrate

cutting‑edge AI research and tools

into the training modules.

Mentor learners through technical challenges, performance optimization, and model deployment.

Keep up to date with

LLM ,

agentic AI , and

generative AI

innovations to ensure curriculum relevance.

Required Skills & Qualifications

Experience:

4 to 5+ years in

AI/ML engineering ,

Data Science ,

Applied NLP , or

MLOps

roles.

Technical Expertise:

Proficiency in

Python

and AI libraries such as

PyTorch ,

TensorFlow , and

Transformers (Hugging Face) .

Strong experience with

LLMs ,

prompt engineering , and

fine‑tuning .

Practical understanding of

RAG systems

using

LangChain

and

vector databases

(e.g.,

FAISS ,

Chroma ,

Pinecone ).

Hands‑on experience in

agentic AI frameworks

(e.g.,

CrewAI ,

AutoGen ,

LangGraph , or

LangChain Agents ).

Knowledge of

tool integration ,

memory management , and

multi‑agent orchestration .

Experience deploying AI models with

FastAPI ,

Docker ,

Kubernetes , or

cloud‑native tools .

Familiarity with

MLOps pipelines ,

CI/CD automation , and

monitoring frameworks .

Exposure to

Generative AI APIs

such as

OpenAI ,

Anthropic Claude ,

Google Gemini , or

Azure OpenAI .

Education:

Bachelor’s or Master’s degree in Computer Science, Data Science, or Artificial Intelligence or similar technical discipline.

Excellent communication, mentoring, and technical training skills.

Proven experience conducting

technical workshops ,

bootcamps , or

corporate AI training programs

preferred.

Ready to

deliver on‑site and virtual training .

Preferred Skills/Attributes:

Certifications in

Machine Learning ,

Generative AI , or

Cloud AI services .

Experience developing

autonomous AI agents

and

multi‑agent ecosystems .

Working knowledge of

vector search optimization ,

knowledge graph integration , and

RAG performance tuning .

Understanding of

AI ethics, bias mitigation , and

responsible AI deployment .

Enthusiasm for teaching and guiding professionals through

hands‑on AI and MLOps implementations .

Equal Opportunity Employer Revature (“Company”) is an equal opportunity employer. We will extend equal opportunity to all individuals without regard to race, religion, color, sex, pregnancy, childbirth or related medical conditions, sexual orientation, gender identity, national origin, disability, age, genetic information, marital status, veteran status, or any other status protected under applicable federal, state, or local laws. This policy applies to all terms and conditions of employment, including but not limited to, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, benefits, compensation, and training. If you require accommodation to work, based on any of these protected factors, please notify the Human Resources Department, and the Company will evaluate the request and provide accommodation in accordance with applicable law.

We seek to comply with all applicable federal, state, and local laws related to discrimination and will not tolerate interference with the ability of any of the Company's employees to perform their job duties. Our policy reflects and affirms the Company's commitment to the principles of fair employment and the elimination of all discriminatory practices.

Note: Work authorization in the country you are applying to is required. Revature does not sponsor work visas

Seniority level Mid‑Senior level

Employment type Full‑time

Job function Information Technology and Engineering

Industries Software Development and IT Services and IT Consulting

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