- Company Name
- Netflix
- Job Title
- Machine Learning/AI Scientist Intern (PhD), 2026
- Job Description
-
**Job title**
Machine Learning/AI Scientist Intern (PhD), 2026
**Role Summary**
Conduct advanced research and develop production‑grade ML solutions across recommender systems, NLP, RL, CV, multimodal, and model optimization domains. Build scalable infrastructure for training, inference, and deployment, and collaborate with cross‑functional teams on AI research and engineering initiatives.
**Expectations**
- Pursuing a PhD in Computer Science, ML/AI, or related quantitative field.
- Demonstrated expertise in at least one core domain (e.g., personalization, NLP, RL, CV, multimodal).
- Strong programming skills, experience with deep learning frameworks, and knowledge of distributed training.
- Proactive learning, effective communication, and commitment to research rigor.
**Key Responsibilities**
- Design, implement, and evaluate novel ML algorithms for personalization, language, vision, or multimodal tasks.
- Optimize models for training/inference efficiency, benchmark performance, and conduct robustness/evaluation studies.
- Develop end‑to‑end ML pipelines, including data ingestion, feature engineering, model training, and deployment in production environments.
- Build and maintain scalable ML infrastructure (distributed compute, GPU clusters, data pipelines) to support research and operational workloads.
- Collaborate with science, engineering, and product teams to translate research insights into product features.
- Document experiments, publish findings, and present results to internal stakeholders.
**Required Skills**
- • PhD candidate in CS, ML, AI, statistics, math, or related field.
- • Deep knowledge of one or more domains: personalization, NLP (LLMs), RL, CV, multimodal, causal, agentic AI.
- • Proficient in Python (and optionally Java/Scala/C++).
- • Experience with PyTorch, TensorFlow, or Keras; GPU training; distributed frameworks (DDP, FSDP, DeepSpeed).
- • Familiarity with end‑to‑end ML pipelines, model explainability, and operationalization challenges.
- • Strong written and oral communication, self‑motivation, and collaborative mindset.
**Required Education & Certifications**
- Current PhD enrollment in Computer Science, Machine Learning, Artificial Intelligence, or a closely related discipline.
- No additional certifications required.
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