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AI Systems, Training

Unconventional AI - Palo Alto, CA I US Remote

Posted Apr 15, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
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Relocation assistance
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Childcare support
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Learning budget
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Verification
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Salary
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401(k) match
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Market context

U.S. role benchmark (BLS OEWS)
$116,543 U.S. median for this role
Projected growth (BLS Employment Projections)
+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function
Engineering From the posting source checked Jun 20, 2026
Seniority
Mid From the posting source checked Jun 20, 2026
Work mode
Remote From the posting source checked Jun 20, 2026
In-office days
0 days From the posting source checked Jun 20, 2026

Schedule

Shift type
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Weekend work
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Application

Cover letter
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Assessment
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Deadline
Not stated

Where they hire

State eligibility is not yet verified.

About this role

AI Systems, Training Palo Alto, CA I US Remote About Unconventional Since 2022, AI has entered the mainstream, reshaping entire industries from education and software development to fundamental consumer behaviors. This revolution has created an unprecedented demand for computation - a demand that is now fundamentally limited by energy, not just in the datacenter, but at a global scale. At Unconventional, our mission is to solve this. We are rethinking computing from the ground up to build a new foundation for AI that is 1000x more efficient. We're doing this by exploiting the rich physics of semiconductors, mapping neural networks directly to the device physics rather than relying on layers of inefficient abstraction. The Role You will be a key contributor to our training ecosystem. Your goal is to build the next-generation ML model training platform tailored for a world where compute is no longer constrained by the digital abstraction. You will co-design and implement training systems alongside novel AI models and hardware platforms that push the boundaries of physics-based compute. What You'll Do - The Model Architectures: Build and maintain highly optimized, model-specific training stacks specifically tuned for state-of-the-art generative vision, language, and world models. - The Training Infrastructure: Design and scale multi-node distributed training systems, implementing elastic sharding and robust data streaming pipelines for fast, large-scale iteration. Implement and robust model checkpointing and recovery mechanisms. - Optimization & Benchmarking: Develop and optimize kernels using low-level programming models like CUDA andTriton. Design rigorous benchmarking suites to track Model Flops

Read the full description at unconv.ai. FewerJobs shows a preview and links to the original posting.

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