Senior Product Manager - Software

Job Title

Senior Product Manager - Software

Role Summary

The Senior Product Manager - Software owns strategy and direction for the developer platform: compiler, SDK, runtimes, model enablement, and developer experience. The role translates hardware capabilities into a developer-ready platform that drives customer adoption and ecosystem growth.

This is a cross-functional product leadership role focused on platform strategy, prioritization, and business impact rather than project execution.

Experience Level

Senior — requires significant product management experience; the posting requests 7+ years of product management for developer-facing software platforms.

Responsibilities

Own product direction, developer experience outcomes, and metrics that drive adoption and platform growth.

• Define roadmap and priorities for compiler, SDK, runtime integrations, model conversion/enablement tooling, and developer platform.
• Lead framework and model enablement strategy (PyTorch, ONNX, ExecuTorch, LiteRT, etc.) including compatibility, validation, and performance targets.
• Reduce time-to-first-working-application (TTFWA): define the metric, baseline it, track progress, and own roadmap items that improve it.
• Establish SDK governance: API surface, versioning, stability commitments, deprecation policy, release quality, and backward compatibility standards.
• Drive developer confidence via reproducible benchmarks, deterministic tooling, diagnostics, and clear documentation.
• Engage with customers to identify workflow friction, deployment blockers, and requirements; represent platform strategy in technical discussions.
• Partner with Applications Engineering and architecture teams to define capabilities for reference applications and production evaluation flows.
• Define profiling, debugging, and performance-analysis requirements to enable developers to optimize on Efficient hardware.
• Balance long-term platform investments against near-term customer enablement and revenue-driving needs; influence silicon decisions when required.
• Define and own developer success metrics and SDK release cadence, packaging, distribution, and support lifecycle.

Requirements

Must-have product and technical skills required for this role, followed by preferred qualifications.

• Must-have: 7+ years product management experience for developer-facing platforms (SDKs, compilers, runtimes, ML tooling, or embedded ecosystems).
• Must-have: Experience shipping tools/platforms used by external developers and driving developer adoption, onboarding, and workflow completion metrics.
• Must-have: Strong understanding of ML inference and deployment pipelines (PyTorch, ONNX, LiteRT/ExecuTorch, TensorRT or equivalent).
• Must-have: Ability to translate customer workflows and technical constraints into clear, actionable requirements for engineering.
• Must-have: Familiarity with software performance tradeoffs (memory, latency, throughput, power, hardware utilization) and with working alongside compiler/runtime and silicon architecture teams.
• Must-have: Ability to establish credibility with technical developers, compiler engineers, and ML practitioners through technical depth and customer empathy.
• Nice-to-have: Experience with compiler toolchains and IRs (LLVM, MLIR, TOSA, XLA) and deployment flows.
• Nice-to-have: Experience with embedded AI, edge inference, embedded software ecosystems (FreeRTOS, CMSIS-NN), Linux-based embedded development, and cross-compilation workflows.
• Nice-to-have: Experience with profiling tools, compiler traces, benchmark-driven optimization, and benchmarking methodologies (MLPerf or equivalent).
• Nice-to-have: Semiconductor or AI hardware company experience, and experience operating in early-stage or startup environments with hybrid PM + DevRel responsibilities.

Education Requirements

Not specified.

About the Company

Company: Efficient Computer

Headquarters: Austin, TX, USA

Developer of ultra-low-power general-purpose processors using patented technology that can consume up to 100x less energy than comparable ultra-low-power processors. Their programmable platform supports standard high-level languages and AI/ML frameworks to enable long-lived, battery-powered edge devices and energy-efficient SoCs for IoT and edge AI applications.