Senior Product Manager - Software

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

Pay and benefits

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.