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Efficient Computer

Energy-efficient processors for edge IoT computing

Senior Product Manager - Software

Technical Product ManagementConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • At least 7 years of product management experience for developer-facing software platforms such as SDKs, compilers, runtimes, APIs, machine-learning 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 machine-learning inference and deployment pipelines such as PyTorch, ONNX, ExecuTorch, LiteRT, TensorRT, or equivalent.
  • Experience translating customer workflows and technical constraints into actionable product requirements that engineering teams can implement 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 influence across them without authority.
  • Ability to establish credibility with technical developers, compiler engineers, and machine-learning practitioners through clear thinking, technical depth, and customer empathy.

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); define the metric, establish a baseline, track it, and own roadmap items that improve it.
  • Establish SDK governance, including 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, and maintain structured mechanisms to feed it into roadmap decisions.
  • Partner with Applications Engineering to define software platform capabilities 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 help developers understand and optimize application behavior on Efficient hardware.
  • Balance long-term platform investments against near-term customer enablement and revenue-driving requirements, and decide when to ship a polished narrow capability versus 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 and workflow metrics and diagnostics, including build success rates, TTFWA, workflow completion rate, and friction points.
  • Define and own the SDK release cadence, packaging, distribution, and support lifecycle.

Desired Qualifications

  • Experience with compiler toolchains, intermediate representations (IRs), and deployment flows such as 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 such as FreeRTOS, CMSIS-NN, and microcontroller SDK patterns, as well as 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 such as MLPerf, 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 product-management and developer-relations responsibilities.

About the Company

Efficient Computer

Energy-efficient processors for edge IoT computing

Efficient Computer makes energy-efficient programmable processors for IoT edge devices and sells a compatible software toolchain that fits existing embedded languages and AI/ML workflows. These processors run local computations at the edge, reducing the need to send data over wireless links, which saves power and enables real-time processing and data compression. Its strength comes from combining hardware with a developer-friendly ecosystem rather than relying on general-purpose chips, helping deployments last longer in places without wired power. Its goal is to enable widespread, cost-effective edge deployments by dramatically lowering energy use and total cost of ownership for IoT networks.

Company size
51-200
Company stage
Series B
Total funding
$173M
Headquarters
Pittsburgh, PA
Founded
2022

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