Machine Learning Engineer

Tiger Analytics; Plano (TX); On-site; USD 120,000 - 150,000; Full time

Job summary

A fast-growing advanced analytics consulting firm is seeking an experienced Machine Learning Engineer with expertise in designing and deploying high-performance APIs and microservices, particularly with generative AI integration. The ideal candidate should have extensive experience with AWS Fargate and a strong understanding of cloud-native applications. This role offers an opportunity to push boundaries in AI-driven applications within a supportive and innovative team environment, emphasizing career development.

Qualifications

• 5+ years of hands-on software development experience.
• Proven expertise in FastAPI and microservice architecture.
• Strong understanding of cloud-native applications.

Responsibilities

• Design, build, and optimize high-performance APIs and microservices.
• Integrate LLM and Generative AI APIs using various providers.
• Collaborate with teams to design CI/CD and MLOps pipelines.

Skills

Python

FastAPI

microservice architecture

LLM API integration

container orchestration (ECS, Docker)

Generative AI frameworks

Tools

AWS Fargate (ECS)

OpenAI API

Job description

Overview

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 integration, LLM 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 Bedrock, OpenAI, 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 applications, container 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.