Senior AI/ML Engineer - MLOps & RAG (Plano)

MACHINE LEARNING TECHNOLOGIES LLC; Plano (TX); On-site; USD 130,000 - 210,000; Full time

Job summary

MACHINE LEARNING TECHNOLOGIES LLC in Plano, TX seeks an AI/ML Engineer with 7–8 years total experience and at least 5 years as an individual contributor in ML. You will collaborate with ML engineers and scientists to design and implement advanced models and production workflows.

Responsibilities include building agent-based workflows, prompt strategies (CoT/ToT/GoT), and applying MLOps across AWS SageMaker, Bedrock, GCP, and Azure.

Qualifications

• Total experience 7–8 years in ML/AI domains.
• Minimum 5 years as an individual contributor in ML engineering.
• Hands-on experience with ML teams and production-grade workflows.
• Experience with agent-based workflows, prompting strategies, and RAG.
• Strong knowledge of MLOps and cloud platforms (AWS SageMaker, Bedrock, GCP, Azure).
• Ability to write clear OKRs and align with business goals.
• Solid understanding of the software development life cycle, agile methodologies, and data engineering.

Responsibilities

• Proven experience working with teams of ML engineers or scientists.
• Hands-on experience with agent based workflows, MCP, RAG and context engineering.
• Hands-on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, and Graph-of-Thoughts prompting strategies.
• Experience with MLOps practices and cloud platforms (AWS SageMaker, Bedrock, GCP, Azure).
• Ability to write clear and concise OKRs and align with business expectations.
• Experience with GitHub
• Solid understanding of software development life cycle, agile methodologies, and data engineering.

Skills

Agent-based workflows

Chain-of-Thought prompting

Tree-of-Thought prompting

Graph-of-Thought prompting

MLOps

OKRs

GitHub

SDLC

Agile methodologies

Data engineering

Tools

GitHub

Job description

MACHINE LEARNING TECHNOLOGIES LLC in Plano, TX seeks an AI/ML Engineer with 7–8 years total experience and at least 5 years as an individual contributor in ML. You will collaborate with ML engineers and scientists to design and implement advanced models and production workflows.

Responsibilities include building agent-based workflows, prompt strategies (CoT/ToT/GoT), and applying MLOps across AWS SageMaker, Bedrock, GCP, and Azure.