Netflix

5 months ago

Machine Learning Scientist 5 - GenAI for Games

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Lead R&D for large language, vision-language, and multimodal foundation models for games, focusing on inference efficiency for cost, latency, and quality. Fine-tune and align LLMs/VLMs in PyTorch using preference learning and reinforcement learning, optimize models via compression techniques, and integrate ASR/TTS for low-latency cross-modal interaction. Build and improve diffusion-based generation for image, video, and 3D, partnering with ML engineers to deploy beyond research-grade performance.

Location: United States

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Design and own fine-tuning and alignment of LLMs and VLMs using preference learning and reinforcement learning for interactive game systems.
•Lead model compression efforts including knowledge distillation, structural pruning, and architectural refinement to meet latency, cost, and quality constraints.
•Adapt, optimize, and integrate ASR/TTS with language models to enable low-latency, cross-modal reasoning.
•Develop and optimize diffusion-based models for image, video, and 3D generation.
•Evaluate and integrate state-of-the-art open-source and commercial models, building internal layers/adapters to close gaps in creative control.

Pay and Benefits

Salary: USD 466,000 - 750,000 annually

Equity and Bonus:Equity

Perks:Health Insurance401kEquityDisability InsurancePaid Leave

Key Requirements

•Deep expertise in deep learning architectures, including Transformers and Diffusion architectures, for LLMs, VLMs, and generative visuals.
•Proven experience in algorithmic model optimization such as distillation, quantization-aware training, or pruning to reduce FLOPs and memory footprint.
•Strong data-centric skills including data cleaning, curation, and synthetic data creation for evaluation and training pipelines.
•Programming proficiency in Python and deep learning frameworks (such as PyTorch), collaborating with engineering on performance constraints.
•Ability to decide when to use commercial APIs/OSS weights versus proprietary R&D to solve efficiency or quality problems.

Skills:Algorithmic optimizationCross-modal reasoningCollaborationPrioritization

Tech Stack:PythonPyTorchTransformersDiffusionLLMsVLMsSpeech recognitionASRTTSReinforcement learningPreference learningKnowledge distillationQuantization-aware trainingPruning

Company Brief

Netflix

Global subscription streaming service that produces and distributes movies, TV series, and games across multiple devices, operating worldwide with extensive original content and localized offerings.

Industry: Streaming Platforms

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Los Gatos, United States

Founded: 1997

Glassdoor: 4.1

Website LinkedIn Glassdoor

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Netflix

5 months ago

Machine Learning Scientist 5 - GenAI for Games

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 19 hours agoStatus: Live

Job Summary

Location: United States

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Design and own fine-tuning and alignment of LLMs and VLMs using preference learning and reinforcement learning for interactive game systems.
•Lead model compression efforts including knowledge distillation, structural pruning, and architectural refinement to meet latency, cost, and quality constraints.
•Adapt, optimize, and integrate ASR/TTS with language models to enable low-latency, cross-modal reasoning.
•Develop and optimize diffusion-based models for image, video, and 3D generation.
•Evaluate and integrate state-of-the-art open-source and commercial models, building internal layers/adapters to close gaps in creative control.

Pay and Benefits

Salary: USD 466,000 - 750,000 annually

Equity and Bonus:Equity

Perks:Health Insurance401kEquityDisability InsurancePaid Leave

Key Requirements

•Deep expertise in deep learning architectures, including Transformers and Diffusion architectures, for LLMs, VLMs, and generative visuals.
•Proven experience in algorithmic model optimization such as distillation, quantization-aware training, or pruning to reduce FLOPs and memory footprint.
•Strong data-centric skills including data cleaning, curation, and synthetic data creation for evaluation and training pipelines.
•Programming proficiency in Python and deep learning frameworks (such as PyTorch), collaborating with engineering on performance constraints.
•Ability to decide when to use commercial APIs/OSS weights versus proprietary R&D to solve efficiency or quality problems.

Skills:Algorithmic optimizationCross-modal reasoningCollaborationPrioritization

Tech Stack:PythonPyTorchTransformersDiffusionLLMsVLMsSpeech recognitionASRTTSReinforcement learningPreference learningKnowledge distillationQuantization-aware trainingPruning

Company Brief

Netflix

Global subscription streaming service that produces and distributes movies, TV series, and games across multiple devices, operating worldwide with extensive original content and localized offerings.

Industry: Streaming Platforms

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Los Gatos, United States

Founded: 1997

Glassdoor: 4.1

Website LinkedIn Glassdoor