---
title: 'Member of Technical Staff - AI Training Platform at Unconventional, Inc.'
canonical: 'https://feeny.ai/job/member-of-technical-staff-ai-training-platform-unconventional-inc-mountain-view-d1g7x3es47d9'
type: 'job'
last_seen: '2026-09-08'
---

# Member of Technical Staff - AI Training Platform at Unconventional, Inc.

- **Company:** Unconventional, Inc.
- **Location:** Mountain View, CA / Seattle, WA
- **Posted:** 2026-09-02
- **Last confirmed live:** 2026-09-08
- **Apply:** https://unconv.ai/careers/?gh_jid=4393750009

## Job description

## 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

As a Member of Technical Staff, AI Training Platform, you will be a core contributor to the infrastructure that powers our model training ecosystem. You will build and scale the end-to-end tooling required to train, evaluate, and benchmark models. Your work will directly accelerate researchers' ability to map neural networks to novel hardware and push the boundaries of physics-based compute.

## Responsibilities

- Training Infrastructure: Architect, scale, and maintain the core AI/ML/RL training platform and 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.
- Framework Development: Maintain and expand our proprietary training framework, ensuring it provides a robust and flexible foundation for all internal model training.
- Optimization & Benchmarking: Develop and optimize kernels using low-level programming models like CUDA and Triton. Design rigorous benchmarking suites to track Model Flops Utilization (MFU), memory bandwidth, and convergence stability.
- Hardware Evaluation Tooling: Build and iterate on tooling to enable rapid, high-level evaluation of novel hardware ideas against benchmarks.
- Cross-Functional Collaboration: Act as a translator, discussing algorithmic trade-offs with theorists and converting model requirements into concrete specifications for infrastructure and hardware engineering teams.
- Optimization & ML Hillclimbing: Design systems to track and visualize quality-vs-efficiency Pareto frontiers, enabling researchers to optimize models for both performance and energy consumption.

## Minimum Qualifications

- Education: BS in Computer Science, Physics, Electrical Engineering, or Applied Math.
- Experience: 5+ years of experience in AI/ML engineering. Veteran of the modern ML software stack. Demonstrated ability to map state-of-the-art AI model architectures (e.g., transformers, Mixture of Experts, diffusion models) to system performance implication.  Deep expertise in how models are partitioned across a cluster, with a mastery of communication primitives, and parallelism strategies.
- Software Development: Strong programming skills in Python or C++. Proven track record of implementing, debugging, and maintaining production-grade training frameworks—such as Megatron-LM, DeepSpeed, Ray, PyTorch Lightning—turning raw compute into a reliable model-building factory.

## Preferred Qualifications

- MS/PhD or equivalent research/project experience in AI/ML or high-performance computing, with publications
- Experience in training, post-training large-scale LLMs and generative models.
- Experience in one or more of the following technologies: Kubernetes, GPU kernels and performance tuning, LLM inference, CUDA, Triton, NCCL, vLLM, SGLang, VeRL, TRL.

Why Join Us?

- The Mission: Redefine computing for the next 50 years by solving the fundamental energy limitation of AI at a global scale.
- The Impact: Shape the company's future as a foundational team member. Enjoy massive ownership and an outsized opportunity to drive change.
- The Challenge: Dive into deeply complex, intellectually stimulating, and unsolved problems at the cutting edge of multiple, converging fields—you will be defining the future of AI compute.
- The Perks: A comprehensive package including competitive salary, significant equity, best-in-class health benefits, 401k matching, truly unlimited PTO, and complimentary meals when working from our Palo Alto office.

## About Unconventional, Inc.

## Company Overview
- **One-liner**: Unconventional AI is rethinking the foundations of a computer to optimize energy efficiency for AI by building analog chips that run neural networks directly on physics rather than simulating digital logic.
- **Entity Type**: Private (Seed stage – raised $475M seed round)
- **Headquarters**: San Diego, California, United States (also has an office in San Francisco)
- **Founded**: Not explicitly stated; assumed ~2024/2025 based on funding announcement in December 2025
- **Founders**: Naveen Rao (CEO), Michael Carbin (co-founder), Sara Achour (co-founder), Meelan Lee (engineering leader)

## Core Business
- Primary industry/industries: Hardware design for artificial intelligence, analog computing, energy-efficient semiconductors
- Target customers: AI labs, hyperscalers, and enterprises that train and deploy large neural networks (B2B/Enterprise)
- Mission or purpose statement: *“Bringing biology-scale efficiency to artificial intelligence”* – building the right isomorphism for intelligence to unlock efficiency gains far beyond digital simulation

## Products & Services
- **Unconventional AI Chip Platform (in development)**: A novel analog/mixed-signal chip designed specifically for probabilistic AI workloads. The chip stores exact probability distributions in the physical substrate (silicon) rather than using numerical approximations, potentially achieving ~1,000x lower power consumption than digital computers. It is a **Hardware** product, supported by extreme codesign of algorithms and software.

## Market Standing
- **Valuation/Market Cap**: $4.5 billion (as of December 2025 – seed round valuation)
- **Key Metric**: Total Funding $475 million (seed round, December 2025)
- **Notable Investors/Partners**: Lightspeed Venture Partners (co-lead), Andreessen Horowitz (co-lead), Sequoia, Lux Capital, DCVC, Future Ventures, Jeff Bezos (individual), and others. CEO Naveen Rao personally invested $10 million.
- **Growth Signals**: 
  - Named to 2026 CB Insights AI 100 list
  - Headcount of 23 employees with +10.8% monthly growth
  - Monthly website traffic 27,433 (+21.7% growth)
  - Highly active on LinkedIn with 9,516 followers and frequent technical blog posts
  - Launched the “Unconventional Grant” program – $500,000 in funding for bold research ideas in AI compute

## Competitive Advantages
- **First-principles approach**: Rejects digital abstraction for analog/physics-based computation, achieving orders-of-magnitude energy efficiency improvements that conventional GPU architectures cannot match.
- **Extreme codesign**: Hardware, software, algorithms, and models are co-optimized from day one, not adapted from legacy computing paradigms.
- **World-class team**: CEO Naveen Rao (prior exits: Nervana→Intel, Mosaic→Databricks) plus co-founders with deep expertise in AI systems, analog circuits, computing theory, and neuroscience.
- **Massive financial backing**: $475M seed round at a $4.5B valuation provides a long runway for ambitious R&D.

## Strategic Focus
- **Near-term priorities**: Design and tape-out of analog AI chips; recruit top interdisciplinary talent across hardware, software, algorithms, and neuroscience.
- **Long-term direction**: Achieve “biology-scale” energy efficiency (on the order of 20W for human-level intelligence) and scale to meet projected global AI compute demand that could outstrip energy supply within 3–4 years.
- **Research investment**: Active grant program and open collaboration with academic/unconventional thinkers.

## Why Work Here
- **Culture**: Deeply interdisciplinary, first-principles culture that challenges assumptions – described as “endlessly curious, comfortable with discomfort, and drawn to the edge of chaos.”
- **Growth opportunity**: Very early-stage (only 23 employees) with massive ambition; employees can shape foundational technology from the ground up.
- **Remote/Hybrid**: Two offices (San Diego HQ and San Francisco); likely hybrid or on-site given hardware work, but not explicitly stated.
- **Perks & environment**: Small team, high ownership, access to top investors and mentors, and the chance to solve one of AI’s most critical bottlenecks (energy).
- **Talent sources**: Employees come from Databricks, MIT, Cohere, and other top AI/tech organizations – strong peer group.

## Sources
1. [unconv.ai](https://unconv.ai/)
2. [unconv.ai/careers](https://unconv.ai/careers/)
3. [unconv.ai/blog](https://unconv.ai/blog/introducing-unconventional-ai/)
4. [linkedin.com](https://www.linkedin.com/company/unconvai)
5. [a16z.com](https://a16z.com/announcement/investing-in-unconventional/)

## Other roles at Unconventional, Inc.

- [Finance Manager, Accounting & FP&A](https://feeny.ai/job/finance-manager-accounting-fp-a-unconventional-inc-mountain-view-s7qznaybwxbd) — Mountain View, CA
- [Member of Technical Staff - Development Experience](https://feeny.ai/job/member-of-technical-staff-development-experience-unconventional-inc-mountain-sb1ydxb6g5rk) — Mountain View, CA / Seattle, WA
- [Member of Technical Staff - Agentic Applications](https://feeny.ai/job/member-of-technical-staff-agentic-applications-unconventional-inc-mountain-view-d5s7z32mqy23) — Mountain View, CA / Seattle, WA
- [AI Systems, Model Optimization](https://feeny.ai/job/ai-systems-model-optimization-unconventional-inc-mountain-view-ca-i-bhb7nvk4vwfb) — Mountain View CA I, United States
- [AI Theory & Systems, Algorithms & Models](https://feeny.ai/job/ai-theory-systems-algorithms-models-unconventional-inc-mountain-view-f0vwf70pgvkv) — Mountain View, CA
- [AI Silicon, Silicon Validation Engineer](https://feeny.ai/job/ai-silicon-silicon-validation-engineer-unconventional-inc-mountain-view-bnzvp2npndhw) — Mountain View, CA
- [AI Silicon, Junior Digital Design Engineer](https://feeny.ai/job/ai-silicon-junior-digital-design-engineer-unconventional-inc-mountain-view-sz9k072xz7hm) — Mountain View, CA
- [AI Silicon, Digital Design Engineer](https://feeny.ai/job/ai-silicon-digital-design-engineer-unconventional-inc-mountain-view-7nbkzmsh4caz) — Mountain View, CA
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