7 machine learning platform engineer jobs at 5 companies in Stanton, CA

3w
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Machine Learning Platform Engineer
San Francisco or New York City or Los Angeles or Seattle
$245k-$345k/yr HybridFull Time
Whatnot
Whatnot: Social marketplace for buying and selling via live streams
4+ YOE4+ years building ML systems, 3+ years engineering production systems, 1+ year Python, experience with distributed training/inference, databases, monitoring, and cloud services.
Python, PostgreSQL, DynamoDB, Elasticsearch, Redis, DataDog, Grafana, AWS Sagemaker, Lambda, Kinesis, S3, EC2, EKS, ECS, Apache Kafka, Flink
2w
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Sr Machine Learning Engineer
Seattle or Santa Monica or Glendale or San Francisco
$149k-$199k/yr HybridFull Time
The Walt Disney Company
The Walt Disney CompanyNYSE: DIS: Produces movies, operates theme parks, and provides streaming services.
5+ YOE5+ years software/ML engineering experience, BS/MS in CS or equivalent, strong Java skill, experience with large-scale ML/DL platforms and LLM tools, good communication and problem-solving.
Java, scikit-learn, Spark MLLib, PyTorch, AWS Bedrock, Azure Cognitive Services, Vertex AI, LangGraph, Crew AI, strands sdk, vector databases, SpringBoot, DynamoDB, Redis, ValKey, MemCache, Apache Kafka, Kinesis, AWS, Terraform, Docker, Kubernetes
1mo
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Staff Machine Learning Engineer - Game Tech Group, ML Platform
Los Angeles, California, United States
$229k-$320k/yr OnsiteFull Time
Riot Games
Riot Games: Developing and publishing competitive multiplayer video games.
6+ YOE6+ years engineering experience with ML/AI or platform teams; experience with inference platforms (KServe), Feast, Milvus, inference serving frameworks (NVIDIA Triton, TorchServe), GPU orchestration, CI/CD, Terraform, and distributed services.
KServe, Feast, Milvus, NVIDIA Triton, Dynamo, TorchServe, CI/CD, Terraform
5d
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Sr Machine Learning Engineer
Seattle or Santa Monica or Glendale or San Francisco
$149k-$199k/yr HybridFull Time
The Walt Disney Company
The Walt Disney CompanyNYSE: DIS: Produces media content and operates global theme parks.
5+ YOE5+ years ML-focused software engineering experience, proficiency with Java and large-scale ML platforms, experience with ML frameworks and LLMs, strong communication and problem-solving skills.
Java, scikit-learn, Spark MLLib, PyTorch, AWS Bedrock, Azure Cognitive Services, Vertex AI, LangGraph, Crew AI, strands sdk, SpringBoot, DynamoDB, Redis, ValKey, MemCache, Apache Kafka, Kinesis, AWS, Terraform, Docker, Kubernetes
2mo
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Machine Learning Engineer 5 - Decisioning & Optimization
New York or Los Angeles or Los Gatos or Seattle
$466k-$750k/yr OnsiteFull Time
Netflix
NetflixNASDAQ: NFLX: Global video streaming and media production service.
7+ YOE7+ years software engineering; 3+ years ML infrastructure, model serving, or ML platform experience in ads/real-time decisioning; real-time model serving with sub-20ms latency; proficiency in Java, Python, or Scala; experience with ML serving frameworks and real-time feature pipelines; strong model monitoring and production readiness.
Java, Python, Scala, ML serving frameworks, feature stores, model registries
2mo
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Senior Principal Machine Learning Engineer, Ad Platforms
Seattle or Santa Monica
$229k-$321k/yr HybridFull Time
The Walt Disney Company
The Walt Disney CompanyNYSE: DIS: Produces media content and operates global theme parks.
12+ YOEBS or MS in Computer Science/Engineering; 12+ years software engineering; strong ML/AI expertise; experience with ML frameworks and ad tech; open AI models and tuning; leadership/mentoring capabilities.
TensorFlow, PyTorch, Hugging Face, Python, Java, SQL, TensorRT, ONNX, DeepSpeed
3w
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Principal Software Engineer, Machine Learning Infrastructure
Palo Alto or Seattle or Los Angeles or New York or Bellevue
$235k-$414k/yr OnsiteFull Time
Snap
SnapNYSE: SNAP: Develops social media applications and augmented reality technology.
10+ YOE10+ years software development experience, technical leadership, distributed systems and ML inference platform expertise, strong software design and debugging skills, ability to operate highly-available systems at scale.
Tensorflow, PyTorch, Kubernetes, GPU, LLM inference, RPC