Machine Learning Engineer

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📍 Plano, Texas, United States

About this role

Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.


We are looking for an experienced AI/ML Lead with deep expertise in designing and deploying high-performance APIs and microservices on AWS Fargate (ECS). The ideal candidate will have hands-on experience in generative AI integrationLLM API development, and AWS Bedrock services, contributing to building scalable GenAI and Agentic AI applications.

Key Responsibilities:

  • Design, build, and optimize high-performance APIs and microservices using Python (Fast API) deployed on AWS Fargate (ECS).
  • Integrate LLM and Generative AI APIs using providers such as AWS BedrockOpenAI, and others.
  • Collaborate with ML and DevOps teams to design CI/CD and MLOps pipelines within the AWS ecosystem.
  • Contribute to architectural decisions around scalability, latency management, and backend efficiency for AI-powered systems.
  • (Preferred) Leverage familiarity with Bedrock Agent Core services to integrate intelligent agent capabilities.
  • Develop and maintain JSON RESTful APIs, adhering to OpenAI API conventions and best practices.

Required Skills & Experience:

  • 5+ years of hands-on software development experience with Python.
  • Proven expertise in FastAPI and microservice architecture.
  • Strong understanding of cloud-native applicationscontainer orchestration (ECS, Docker), and AWS tools.
  • Proficiency in LLM API integration and working with Generative AI frameworks.
  • Experience implementing CI/CD, IaC, and ML pipelines across AWS environments.
  • Familiarity with Bedrock AgentCore or other agentic systems (nice to have).

Why Join Us:

You’ll be part of an innovative team building the next generation of AI-driven applications, where scalability, performance, and intelligent automation converge. This is an opportunity to push boundaries in Agentic AI infrastructure development in a supportive, fast-moving environment.

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.

Frequently Asked Questions

Is the salary disclosed for the Machine Learning Engineer position at sJUKvzuwkZUks5P23HYp2P?
The salary for this Machine Learning Engineer role at sJUKvzuwkZUks5P23HYp2P is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Machine Learning Engineer position at sJUKvzuwkZUks5P23HYp2P located?
This Machine Learning Engineer role at sJUKvzuwkZUks5P23HYp2P is based in Plano, Texas, United States. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
How do I apply for the Machine Learning Engineer position at sJUKvzuwkZUks5P23HYp2P?
Click the "Apply Now" button on this page. You will be redirected to sJUKvzuwkZUks5P23HYp2P's official application portal hosted on workable where you can submit your application directly.
When was the Machine Learning Engineer job at sJUKvzuwkZUks5P23HYp2P posted?
This Machine Learning Engineer position at sJUKvzuwkZUks5P23HYp2P was posted on Jan 14, 2026. Apply as soon as possible — early applications are often reviewed first.
Machine Learning Engineer
sJUKvzuwkZUks5P23HYp2P
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