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Browse remote TensorFlow positions — production ML pipelines, Keras model development, TFX workflows, and mobile/edge AI with TFLite.
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Imaging based phenotyping of in-vitro biology is at the heart of insitro's efforts to accelerate drug development. At insitro, we use machine learning...
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Posted 3 weeks ago
Senior/Staff System Research Engineer – LLM Inference Optimization
Snowflake
US-WA-Bellevue
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are en...
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Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows,...
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Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows,...
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Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI resear...
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At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are en...
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Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training...
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Posted 3 weeks ago
Member of Technical Staff - Quantitative Research
Udio
New York City (Remote possible for exceptional candidates)
Udio builds extraordinary AI experiences to empower musical artists and super fans. Pairing best-in-class AI models with groundbreaking partnerships a...
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Posted 3 weeks ago
Fullstack Software Engineer - Core
Dataiku
France, Remote; Germany, Remote; Netherlands, Remote; Spain, Remote; United Kingdom, Remote
Dataiku is the Platform for AI Success, the enterprise orchestration layer for building, deploying, and governing AI. In a single environment, teams d...
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WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we'...
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Role guide
What to expect in remote TensorFlow jobs
TensorFlow remains the preferred framework for enterprise ML deployments, structured pipelines via TFX, and mobile/edge applications via TFLite. Remote TensorFlow jobs typically require production engineering depth — model serving, pipeline orchestration, and cross-platform deployment experience.
What you'll work on
- Build production ML pipelines with TFX for enterprise data processing
- Deploy models to mobile or edge devices using TFLite
- Develop and maintain Keras model architectures for classification or regression tasks
- Serve ML models at scale with TensorFlow Serving or Vertex AI
What companies look for
- Experience with Keras functional and subclassing APIs
- Knowledge of TFX components and production pipeline orchestration
- TF2 eager execution and SavedModel deployment expertise
Frequently asked questions
Are TensorFlow jobs still available remotely?
Yes. TensorFlow is still widely used in enterprise AI, healthcare, and edge computing. Many large organisations have standardised on TF for its mature deployment tooling — particularly TFX and TFLite.
What is the typical stack for remote TensorFlow roles?
TF2 + Keras for modelling, TFX for pipeline orchestration, TensorFlow Serving or Vertex AI for deployment. Docker and Kubernetes are common for infrastructure. Some roles also involve TFLite for mobile deployment.
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