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tiger-analytics

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Machine Learning Engineer

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Tiger Analytics is a global leader in AI and advanced analytics consulting, empowering Fortune 1000 companies to solve their toughest business challenges. We are on a mission to push the boundaries of what AI can do, providing data-driven certainty for a better tomorrow. Our diverse team of over 6,000 technologists and consultants operates across five continents, building cutting-edge ML and data solutions at scale. Join us to do great work and shape the future of enterprise AI.

Requirements

  • 5+ years of professional software development experience, with strong proficiency in Python, and applying software engineering and design principles (OOP, functional programming, design patterns, testing frameworks, CI/CD fundamentals).
  • Deep understanding of cloud-based data platforms (Azure, Databricks etc.), including cluster configuration, Spark optimization techniques and best practices.
  • Strong understanding of distributed data processing systems (Spark, Delta tables, cloud storage layers) with hands-on experience in building data pipelines, optimizing performance, and handling large-scale datasets.
  • Exposure to DevOps and engineering hygiene practices such as containerization (Docker), infrastructure-as-code, CI/CD pipelines, and automated testing for workflows.
  • Proven ability to work effectively in cross-functional teams (DS, DE, Cloud Ops, Product) with a proactive, inquisitive, and go-getter mindset
  • Ability to translate ambiguous business or analytical requirements into scalable technical solutions, with solid grounding in code quality, reliability, observability, and engineering best practices.

Additional qualifications (Nice to have):

  • Experience in operationalizing and deploying machine learning models using production-grade MLOps frameworks (MLflow, AzureML, Databricks Model Serving), with a strong understanding of model lifecycle management such as versioning, lineage, monitoring, retraining workflows, and deployment automation.
  • Familiarity with modern data and ML architecture patterns such as feature stores, vector stores, low-latency inference pipelines.

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.

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What this application asks

workable

First name, Last name, Email, Headline, Phone, Photo, Education, Experience, Summary, Resume

  • What kind of US work authorization do you have (resident, visa - please specify type)? written answer
  • Provide an example of a recent design challenge where you leveraged a specific design pattern (e.g., Factory, Observer, Singleton) to make a Python application more scalable, maintainable, or testable. written answer
  • Describe your hands-on experience with containerization (Docker) and how you've used CI/CD pipelines to ensure code quality and automated deployment for data or machine learning workflows. written answer
  • How did you ensure the final solution adhered to code quality, reliability, and observability standards? written answer
  • Can you describe a complex, large-scale data pipeline you built using Spark and Delta tables on a cloud platform (like Azure/Databricks)? written answer
  • Please share a link to your LinkedIn profile. written answer
  • This position is for full-time W2 employment with Tiger Analytics (we can also consider contract-to-hire, but not c2c). Please state your preference (W2 vs c2h). written answer

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