Remote Machine Learning Engineer

Description:

• Tiger Analytics is a global leader in AI and advanced analytics consulting, empowering Fortune 1000 companies to solve their toughest business challenges.
• The company is on a mission to push the boundaries of what AI can do, providing data-driven certainty for a better tomorrow.
• The diverse team consists of over 6,000 technologists and consultants operating across five continents, building cutting-edge ML and data solutions at scale.
• The position requires 5+ years of professional software development experience, with strong proficiency in Python, and applying software engineering and design principles such as OOP, functional programming, design patterns, testing frameworks, and CI/CD fundamentals.
• A deep understanding of cloud-based data platforms (Azure, Databricks, etc.) is necessary, including cluster configuration, Spark optimization techniques, and best practices.
• Candidates should have a 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 is required.
• The role demands a proven ability to work effectively in cross-functional teams (DS, DE, Cloud Ops, Product) with a proactive, inquisitive, and go-getter mindset.
• Candidates must be able to translate ambiguous business or analytical requirements into scalable technical solutions, with a solid grounding in code quality, reliability, observability, and engineering best practices.
• Additional qualifications that are nice to have include experience in operationalizing and deploying machine learning models using production-grade MLOps frameworks (MLflow, AzureML, Databricks Model Serving), and familiarity with modern data and ML architecture patterns such as feature stores, vector stores, and low-latency inference pipelines.
• Significant career development opportunities exist as the company grows, offering a unique opportunity to be part of a small, fast-growing, challenging, and entrepreneurial environment with a high degree of individual responsibility.

Requirements:

• Candidates must have 5+ years of professional software development experience.
• Strong proficiency in Python and applying software engineering and design principles is essential.
• A deep understanding of cloud-based data platforms, including cluster configuration and Spark optimization techniques, is required.
• Candidates should have hands-on experience with distributed data processing systems and building data pipelines.
• Exposure to DevOps practices such as containerization, infrastructure-as-code, and CI/CD pipelines is necessary.
• Proven ability to work effectively in cross-functional teams is required.
• Candidates must be able to translate ambiguous business or analytical requirements into scalable technical solutions.
• A solid grounding in code quality, reliability, observability, and engineering best practices is essential.
• Additional qualifications include experience with MLOps frameworks and familiarity with modern data and ML architecture patterns.

Benefits:

• The position offers significant career development opportunities as the company grows.
• Employees will be part of a small, fast-growing, challenging, and entrepreneurial environment.
• The role comes with a high degree of individual responsibility.
• Tiger Analytics provides equal employment opportunities to applicants and employees without regard to various protected statuses.