Machine Learning Engineer

Tiger Analytics Inc.

  • Plano, TX
  • 30+ days ago
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    Skills

    • Amazon Web Services (AWS)unmatched
    • Application Programming Interface (API)unmatched
    • Architectural Servicesunmatched
    • Artificial Intelligence (AI)unmatched
    • Best Practicesunmatched
    • Channel Strategiesunmatched
    • Cloud Applicationsunmatched
    • Consultingunmatched
    • Continuous Deployment/Deliveryunmatched
    • Continuous Integrationunmatched
    • Data Scienceunmatched
    • DevOpsunmatched
    • Dockerunmatched
    • Ecosystemsunmatched
    • Entrepreneurshipunmatched
    • Fortune 500 Customersunmatched
    • JSONunmatched
    • Leadershipunmatched
    • Machine Learningunmatched
    • Market Researchunmatched
    • Microservicesunmatched
    • Performance Tuning/Optimizationunmatched
    • Python Programming/Scripting Languageunmatched
    • REST (Representational State Transfer)unmatched
    • Scalable System Developmentunmatched
    • Software Developmentunmatched

    Description

    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.

    Requirements

    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.

    Benefits

    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.

    Numbers & Facts

    LocationPlano, TX

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