As a Machine Learning Engineer at the Globalization Data Science and Engineering team, you will play a pivotal role in enhancing the efficiency of Large Language Models (LLMs), Multimodal LLMs, and other media ML models by designing scalable training and inference systems. Your day-to-day responsibilities include optimizing data pipelines for high throughput, implementing distributed training strategies, and ensuring robust serving through techniques like quantization and long-context handling. You will work closely with a cross-functional team to integrate these solutions into Netflix’s workflows, driving significant improvements in scalability and reliability. Proficiency in PyTorch and solid software engineering practices are essential, along with experience in leading impactful ML initiatives and collaborating effectively across teams.
Design and build scalable training and inference systems for LLMs, Multimodal LLMs, and other media ML models.
Optimize end-to-end training processes including data pipelines, distributed training strategies, and mixed precision techniques.
Enhance inference performance through KV cache design, batching, quantization, and long-context handling.
Scale model training and inference into robust systems integrated seamlessly with Netflix workflows.
Drive initiatives to improve scalability, latency, and reliability of ML systems as a technical thought leader.
Mentor and elevate other engineers and scientists in large-scale ML system development and performance engineering.
What we're looking for
Extensive experience in ML engineering for large, production-grade systems using LLMs and multimodal models.
Deep hands-on expertise in optimizing training efficiency through data pipelines and distributed strategies.
Strong skills in inference optimization including KV cache design, batching, scheduling, and quantization.
Proficient with PyTorch and solid software engineering practices like testing and observability.
Proven leadership in defining and executing impactful ML roadmaps with stakeholders.
Exceptional communication and collaboration abilities; comfortable with ambiguity and high ownership.
Market check
Salary context
This
$466,000–$750,000
range sits above
100%
of similar postings on FindRole.
Peer median band
$161,700–$241,500
Median floor and ceiling across peers.
Typical midpoint (25–75%)
$169,213–$246,150
Middle half of comparable postings.
Based on 240 comparable postings.*
* 240 is the maximum number of comparable postings sampled.
Employer
About Netflix
Netflix is the world''s leading streaming entertainment service, offering a vast library of TV series, films, documentaries, and original content to subscribers in over 190 countries. Industry: Streaming Entertainment & Media
Netflix currently has
91 open roles
on FindRole.
Listed pay typically runs
$388,000–$610,000
across 87 roles with salary data.
Python
TensorFlow
PyTorch
scikit-learn
MATLAB
C++
signal processing
wireless communication
MIMO
OFDM
SDRs
GPU acceleration
embedded machine learning
real-time systems
adaptive modulation
beamforming
cognitive radio techniques
3GPP
IEEE 802.11/15
military waveforms