Machine Learning Engineer
Tiger Analytics Inc.9 months ago
Remote, United StatesSenior
Responsibilities
- Build scalable machine learning and data solutions for enterprise clients.
- Develop and optimize distributed data pipelines using Spark, Delta tables, cloud storage layers, and large-scale datasets.
- Configure cloud data clusters and apply Spark performance optimization techniques.
- Translate ambiguous business and analytical requirements into scalable technical solutions.
- Apply software engineering practices involving code quality, reliability, observability, testing, and deployment automation.
- Operationalize and deploy machine learning models using production-grade MLOps frameworks, including model versioning, lineage, monitoring, retraining workflows, and deployment automation.
- Collaborate with data science, data engineering, cloud operations, and product teams.
Requirements
- At least 5 years of professional software development experience.
- Strong Python proficiency and knowledge of software engineering and design principles.
- Deep understanding of cloud-based data platforms such as Azure and Databricks, including cluster configuration and Spark optimization.
- Hands-on experience with distributed data processing systems, Spark, Delta tables, cloud storage layers, data pipelines, and large-scale datasets.
- Exposure to Docker, infrastructure-as-code, CI/CD pipelines, automated testing, and DevOps practices.
- Ability to develop reliable, observable, maintainable technical solutions and work effectively in cross-functional teams.
- Preferred experience with MLflow, AzureML, Databricks Model Serving, model lifecycle management, feature stores, vector stores, and low-latency inference pipelines.
Benefits
- Fully remote workplace in the United States.
- Significant career development opportunities in a small, fast-growing, entrepreneurial environment.
- High degree of individual responsibility.
Tech Stack
Categories