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Strong global brand, remote role and popular ML engineering title increase applicant competition.
Requires specialized ML engineering, deep learning and MLOps expertise, limiting cross-industry portability.
Explicit 7+ years, mandatory ML production experience and specific technical stack increase hiring strictness.
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Scope, design, and deploy scalable machine learning systems in production across Twilio's AI/ML products and services.
Partner with product, engineering, and data platform teams to define requirements, build data pipelines, and execute large scale ML solutions end-to-end.
Mentor and uphold engineering standards including code reviews, automated testing, and model monitoring to maintain high quality ML deployments.
7+ years of applied Machine Learning experience with proficiency in Python.
Strong foundation in Machine Learning and Deep Learning frameworks (PyTorch, TensorFlow, or Keras).
Experience building, shipping, and maintaining ML models in production within ambiguous and fast-paced environments.
Remote work based in India; experience with big data technologies (Kafka, Spark, Hadoop, DynamoDB, etc.) and working in agile teams.
Experienced in architecting and running large scale ML experiments and analysis to influence product roadmaps.
Able to rapidly understand and operate within diverse application/business domains and collaborate cross-functionally.
Skilled in ML Ops practices related to testing, retraining, and monitoring of models in production environments.