Efficient Computer is rethinking computing from the ground up to solve one of AI's biggest challenges: energy. Our Fabric architecture delivers a 10–100x improvement in energy efficiency for general-purpose computation, including AI, while supporting familiar programming languages and software frameworks—unlocking new possibilities for autonomous machines, intelligent infrastructure, wearables, and space systems. With our first processor, Electron E1, now shipping in volume and more than $97 million in Series B financing recently announced, we're accelerating customer deployments and scaling our architecture to data center performance. Join us to build the hardware and software that bring intelligence wherever it's needed and help shape the next generation of computing.
The Senior Product Manager - Software owns the strategy and direction for Efficient Computer’s developer platform - including the compiler, SDK, runtime integrations, model enablement stack, and overall developer experience. This role is critical to customer adoption and long-term ecosystem growth, translating Efficient’s hardware capabilities into a scalable, developer-ready platform that enables customers to build, optimize, and deploy applications efficiently.
Success in this role requires thinking beyond individual features and approaching the platform as a complete developer ecosystem. The Software PM is responsible for defining product direction, prioritization, customer requirements, and developer experience outcomes, while partnering closely with software engineering, silicon architecture, applications engineering, marketing, and customer-facing teams.
This is a highly cross-functional product leadership role focused on strategy, platform evolution, and business impact — not project management or sprint administration. The Software PM defines what should be built, why it matters, how success is measured, and how priorities align with customer and company goals, while engineering teams own implementation and execution.
Success looks like:
- Developers achieve production-ready applications quickly, without white-glove engineering support
- The compiler and SDK become a competitive advantage, not an adoption bottleneck
- Framework support and tooling reduce evaluation friction and accelerate customer design-ins
- Software capabilities directly influence customer wins and silicon roadmap decisions
Key Responsibilities
- Define the product roadmap for the compiler, SDK, runtime, model conversion and enablement tooling, and developer platform. Set priorities based on customer requirements, competitive positioning, and strategic platform needs.
- Lead framework and model enablement strategy across PyTorch, ONNX, ExecuTorch, LiteRT, and future runtimes, including compatibility, validation coverage, performance expectations, and support commitments.
- Drive reduction in time-to-first-working-application (TTFWA) across customer segments. Define the metric, baseline it, track it, and own the roadmap items that move it.
- Establish SDK governance: surface area, versioning, API stability commitments, and deprecation policy. Define release quality criteria, validation expectations, and backward compatibility standards.
- Drive developer confidence through reproducible benchmarking, deterministic tooling behavior, clear diagnostics, and strong documentation.
- Participate in customer engagements to understand workflow friction, deployment blockers, and framework requirements. Represent software platform strategy in technical customer discussions and ecosystem partnerships.
- Gather and prioritize developer feedback across evaluation, onboarding, optimization, and deployment phases. Maintain structured mechanisms to feed this directly into roadmap decisions.
- Partner with Applications Engineering to define the software platform capabilities necessary for production-quality reference applications and customer evaluation flows, including AI inference, vision, audio, and sensor-processing pipelines.
- Define requirements for profiling, debugging, and performance analysis workflows that allow developers to understand and optimize application behavior on Efficient hardware.
- Balance long-term platform investments against near-term customer enablement and revenue-driving requirements. Understand when the right call is shipping a polished narrow capability vs. a rough broad one.
- Influence silicon decisions based on software needs and constraints. Partner with the Hardware PM and architecture team when compiler or runtime requirements have silicon implications.
- Establish and own developer success metrics and developer workflow metrics and diagnostics: build success rates, TTFWA, workflow completion rate, and friction points.
- Define and own the SDK release cadence, packaging, distribution, and support lifecycle.
Required Qualifications
- 7+ years of product management experience for developer-facing software platforms - SDKs, compilers, runtimes, APIs, ML tooling, or embedded developer ecosystems
- Experience shipping tools and platforms used directly by external developers, including operating through the customer-zero phase
- Demonstrated ownership of developer adoption, onboarding success, workflow completion, or related developer productivity metrics
- Strong understanding of modern ML inference and deployment pipelines (PyTorch, ONNX, ExecuTorch, LiteRT (formerly TensorFlow Lite), TensorRT, or equivalent)
- Experience translating customer workflows and technical constraints into actionable product requirements that engineering can build from without ambiguity
- Familiarity with software performance tradeoffs involving memory, latency, throughput, power, and hardware utilization
- Ability to work effectively with compiler, runtime, systems software, and silicon architecture teams and to influence without authority across all of them
- Ability to establish credibility with highly technical developers, compiler engineers, and ML practitioners through clear thinking, technical depth, and strong customer empathy.
Preferred Qualifications
- Experience with compiler toolchains, IRs, and deployment flows (LLVM, MLIR, TOSA, XLA, or equivalent)
- Experience with embedded AI deployment pipelines and edge inference workflows
- Experience at a semiconductor or AI hardware company building developer tools for a novel architecture
- Familiarity with embedded software ecosystems (FreeRTOS, CMSIS-NN, MCU SDK patterns) and Linux-based embedded development environments and cross-compilation workflows
- Experience with performance profiling tools, compiler traces, and benchmark-driven optimization workflows
- Experience with benchmarking methodologies (MLPerf or equivalent) - including designing, running, and publishing credible results
- Experience operating in early-stage environments with incomplete requirements and rapidly evolving architectures
- Experience in startup environments with hybrid PM + DevRel responsibilities
We offer a competitive base salary for this role, generally ranging from $160,000 to $240,000, plus a 10% annual bonus, meaningful equity, and comprehensive benefits. Final compensation will depend on experience, level, and location, with flexibility for the right candidate.
Why Join Efficient?
Build what's next. At Efficient, you'll tackle big challenges with room to take ownership and make an impact. We back you with competitive pay, equity, a 401(k) match, company-paid benefits, paid parental leave, and flexibility—plus opportunities to grow your skills and career as we scale.
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