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

Description: • Build and maintain data pipelines that generate training datasets for machine learning models and experimentation. • Contribute to infrastructure that supports distributed training workflows such as PyTorch and Ray. • Work with workflow orchestration tools such as Airflow, Flyte, or similar systems 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 evolution of the offline ML platform architecture as it scales. Requirements: • PhD in Computer Science, Machine Learning, Systems, or a related field. • Strong foundation in machine learning systems, distributed systems, or large-scale data processing through research or projects. • Experience with Python and data-intensive workloads. • Familiarity with ML frameworks such as PyTorch or TensorFlow and/or distributed systems such as Ray or Spark. • Experience, academic or applied, with data pipelines, model training workflows, or large datasets. • Strong problem-solving skills and ability to translate research ideas into practical systems. • Interest in building scalable, reliable infrastructure for machine learning. • Experience with workflow orchestration systems such as Airflow or Flyte is preferred. • Exposure to large-scale data platforms such as data lakes, warehouses, or streaming systems is preferred. • Publications or research in ML systems, distributed systems, or related areas are preferred. • Strong English communication skills for professional verbal and written exchanges are required. • Relocation support is not available for this position. • Work visa or immigration sponsorship is not available for this position. Benefits: • Gross pay salary range of $112,700 to $169,100 USD. • Comprehensive health, life, and disability insurance. • Employee stock ownership. • Competitive retirement or pension plans. • Generous vacation and personal days. • Support for new parents through leave and family-care programs. • Mental health and wellbeing programs and support. • Commute subsidy. • Training and development programs. • Volunteering and donation matching program. Apply tot his job Apply To this Job