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Remote Tensorflow Developer Jobs in Los Angeles, CA

Mantari

Software Engineer

Torrance, CA · On-site +1

Deep fluency with at least one modern deep learning framework (JAX, PyTorch, TensorFlow, etc ... Strong grasp of modern DevOps: code reviews, CI/CD pipelines, observability, and containerization ...

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Remote Tensorflow Developer information

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How much do remote tensorflow developer jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for remote tensorflow developer in Los Angeles, CA is $56.93, according to ZipRecruiter salary data. Most workers in this role earn between $43.51 and $69.66 per hour, depending on experience, location, and employer.

What is a remote Tensorflow developer?

A Remote TensorFlow Developer job involves designing, implementing, and optimizing machine learning models using TensorFlow while working from a remote location. Developers in this role typically collaborate with data scientists, engineers, and product teams to build AI-driven applications and improve model performance. Responsibilities may include data preprocessing, model training, deployment, and fine-tuning for scalability and efficiency. Strong knowledge of deep learning, neural networks, and cloud platforms is often required.

What are the key skills and qualifications needed to thrive as a remote Tensorflow developer, and why are they important?

To thrive as a Remote Tensorflow Developer, you need deep knowledge of machine learning concepts, strong proficiency in Python programming, and hands-on experience with Tensorflow framework. Experience with cloud platforms (such as AWS, GCP, or Azure), model deployment, and relevant Tensorflow Developer certification are highly valuable. Excellent problem-solving abilities, self-motivation, and effective remote communication skills help developers stand out. These qualities are crucial for building robust machine learning solutions, efficiently collaborating with distributed teams, and delivering high-impact results in a remote setting.

What are some typical challenges faced by remote Tensorflow developers, and how are these addressed?

Remote Tensorflow Developers often face challenges such as collaborating across different time zones, managing large datasets, and keeping up with rapidly changing machine learning technologies. These challenges are typically addressed through robust communication tools (like Slack or Zoom), using version control systems for code collaboration, and adopting efficient cloud-based workflows for data and model sharing. Teams may also conduct regular virtual stand-ups and knowledge-sharing sessions to stay aligned on projects and share learnings. Engaging in continuous learning and attending online workshops or conferences also helps remote developers stay updated and effective in their roles.

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Remote Tensorflow Developer jobs near you

Software Engineer

Mantari

Torrance, CA • On-site, Remote

Full-time

Re-posted 20 days ago

Job description

Description

Own the guts of our modeling engine, everything between raw sensor data and a lightning-fast forecast API:

  • Build and optimize CUDA kernels, JAX/PyTorch ops, and distributed training loops for physics-aware transformer models
  • Stand up reproducible, containerized pipelines (Ray, Kubernetes, Slurm, or similar) that scale from a single GPU to multi-region GPU clusters in the cloud
  • Automate data ingest and feature engineering from our growing sensor network (satellite, buoy, radar, etc.)
  • Translate novel research prototypes into production-grade code

You'll work closely with Mantari's Head of Weather and AI modeling teams to operationalize next-generation forecast systems, bringing meteorological science and modern ML together at planetary scale.

Requirements
  • Degree in Atmospheric Science, Computer Science, or related engineering / physical sciences field
  • 5+ years writing high-performance Python/C++/Rust for GPU workloads
  • Real-world experience designing and building cloud-native applications and infrastructure (GCP, AWS, or Azure)
  • Deep fluency with at least one modern deep learning framework (JAX, PyTorch, TensorFlow, etc.)
  • Proven track record shipping distributed training or inference systems at scale (100+ GPUs)
  • Comfortable profiling kernels, diagnosing memory bottlenecks, and reading compiler logs when needed
  • Strong grasp of modern DevOps: code reviews, CI/CD pipelines, observability, and containerization
Bonus Qualifications
  • Experience with numerical weather prediction, remote-sensing data, or geospatial intelligence
  • Background in physics-informed ML, simulation modeling, or data assimilation
  • Contributions to open-source ML or scientific computing frameworks
How We Work
  • Small, senior team; high autonomy, high expectations.
  • Collaborate closely with the founding team and SMEs to push the boundaries of observation-driven AI-native weather forecasting, and turn weather into an advantage, not a roadblock.
  • LA HQ required.
  • Equity upside commensurate with being one of the first core team members. Competitive salary, full benefits, and hardware budget.

Apply