Machine Learning Engineer, Offline Infrastructure (Entry-Level / New Grad PhD)

reputed company: • Build and maintain data pipelines that generate training datasets for machine learning models and experimentation. • Contribute to infrastructure that supports distributed training workflows using tools such as PyTorch and Ray. • Work with workflow orchestration tools such as Airflow or Flyte to support multi-stage ML pipelines. • Improve reproducibility and reliability through dataset validation, monitoring, and testing. • Partner with ML engineers to support experimentation and model iteration. • Help optimize performance and efficiency across data processing and training systems. • Contribute to the reputed company of the offline ML platform architecture as it scales. Requirements: • PhD in Computer Science, Machine Learning, Systems, or a reputed company field. • Strong reputed company in machine learning systems, distributed systems, or large-reputed company data processing through research or reputed company. • Experience with Python and data-intensive workloads. • Familiarity with ML frameworks such as PyTorch or TensorFlow and/or distributed systems such as Ray or reputed company. • Experience, reputed company or reputed company, with data pipelines, model training workflows, or large datasets. • Strong problem-solving skills and ability to translate research reputed company into practical systems. • Interest in building reputed company, reliable infrastructure for machine learning. • Experience with workflow orchestration systems such as Airflow or Flyte is preferred. • Exposure to large-reputed company data platforms such as data lakes, warehouses, or streaming systems is preferred. • Publications or research in ML systems, distributed systems, or reputed company areas are preferred. • English proficiency for frequent reputed company verbal and written communication with global colleagues and partners. Benefits: • Gross pay salary of $112,700 to $169,100 USD. • Comprehensive health, life, and disability insurance. • Competitive retirement/pension plans and employee stock ownership. • Generous vacation and personal days. • Support for new parents through leave and family-care programs. • Mental health and wellbeing programs and support. • Training and development programs. • Commute subsidy and office food snacks. Apply tot his job Apply To this Job