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Jobs / Reddit

Machine Learning Engineer

Reddit·San Francisco, CAsenior

In short

  • →Ingeniero de ML que construye infraestructura escalable para notificaciones personalizadas a millones de usuarios.
  • →Diseña y mantiene pipelines de ML completos: desde ingesta de datos hasta despliegue en producción.
  • →Destacado: trabaja en sistemas de recomendación a gran escala con impacto directo en la experiencia del usuario.

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The questions they'll ask you

1. ¿Cómo diseñarías un pipeline de ML para notificaciones en tiempo real con baja latencia?

2. ¿Qué consideraciones clave incluirías al escalar un sistema de recomendación a 100M+ usuarios?

3. ¿Cómo medirías el impacto de un nuevo modelo de ranking en notificaciones usando A/B testing?

🔒 +7 more questions

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💵 USD · Remote · No visa

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What they ask for

  • ✓5 años de experiencia en ingeniería de ML o puesto relacionado
  • ✓Diseño de sistemas de software a gran escala
  • ✓Experiencia en sistemas de recomendación a gran escala
  • ✓Dominio de Python, Golang o Java
  • ✓Construcción de modelos con PyTorch o TensorFlow
  • ✓Experiencia con Kafka, Redis, DynamoDB y BigQuery

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

PythonGolangJavaPyTorchTensorFlowRESTHTTPThriftgRPCRedis

Who should you write to at Reddit?

Your free dossier identifies the people who'd interview you — their background, what they value, and how to reach out so you stand out before applying.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Job Duties: Design, build, and maintain scalable ML infrastructure to support notification relevance, targeting, ranking, and personalization across channels (e.g. push, email, in-app notifications) for millions of users. Architect and implement end-to-end ML pipelines for notifications, including data ingestion, feature computation, model training, evaluation, deployment, and online serving in production environments. Collaborate cross-functionally with data scientists, product managers, and engineers across teams to define requirements, align on priorities, and deliver end-to-end notification solutions. Lead design and implementation of experimentation frameworks (e.g. A/B testing, multi-armed bandits, or similar methods) to evaluate new notification models, ranking strategies, and targeting policies. Mentor and provide technical guidance to engineers, sharing best practices in machine learning engineering, distributed systems, and ML infrastructure design. Full-time telecommuting is an option. Requirements: Bachelor’s degree in Computer Science, Engineering (any field) or related quantitative discipline and five (5) years of experience in the job offered or related occupation. Special Skill Requirements: (1) designing, building, and iterating large-scale scalable software systems; (2) designing and building ML recommender systems at high scale; (3) Delivering large and complex systems with significant business impact; (4) Cross-functional collaboration on large-scale projects with complex dependencies across teams; (5) Object-oriented programming (Python, Golang, or Java); (6) Building ML models with PyTorch or TensorFlow; (7) API design and integration with REST, HTTP, Thrift, or gRPC; (8) Working with largescale key-value and NoSQL storage and caching systems (Redis, Cassandra, DynamoDB); (9) Working with large-scale messaging and event-driven systems (Apache Kafka, AWS SQS, SNS, SES ); (10) Building workflows using orchestration systems (Kubeflow, Ray, Apache Airflow, AWS Step Functions); (11) Working with large-scale analytics and data warehousing platforms (Google BigQuery, Amazon Redshift); (12) Experience with observability, logging, tracing and monitoring tools such as Prometheus, Grafana, AWS Cloudwatch; (13) Designing, running, and analyzing A/B experiments to measure and optimize system performance Benefits: • Comprehensive Healthcare Benefits and Income Replacement Programs • 401k with Employer Match • Global Benefit programs that fit your lifestyle, from workspace to

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