Member of Design Staff — Conversation Design (Voice + Chat) (MDS‑CXD) — Mumbai/Pune/Kharagpur (Onsite Only) Words are the interface. Trust is the outcome. Make negotiation, scheduling, and money flows feel effortless—and always legible. Why this role exists Kai and Nav must sound competent, kind, and clear—especially when handling consent, money, or mistakes. Your craft turns complex systems into conversations people understand and control. What you’ll do Design conversation patterns for negotiation, scheduling, bookings, bill‑pay, and follow‑ups , including error/repair. Create tone systems and microcopy that make consent, privacy, and approvals unmistakably clear. Script voice call flows (fee waivers, refunds, appointment changes) with objections and recovery paths . Build a library of prompts/tool utterances with measurable intent boundaries; partner with Applied Science on evals. Run usability tests; ship rubrics for task success, clarity, and satisfaction ; instrument analytics. 30 / 60 / 90 outcomes 30 days : Pattern library v1; tone system; consent/approval microcopy; baseline clarity scores from pilot users. 60 days : Negotiation scripts (telecom fee waiver, utility bill credit, airline fee); +15% task success vs baseline; call flow recordings reviewed weekly. 90 days : +25% task success and –30% error‑recovery time on golden set; clarity/NPS improvements documented; CXD gates in CI. Signals we’re looking for Shipped conversational UX at scale (voice/call + chat). Proof that your words moved metrics (success, CSAT, AHT). Comfort with consent, privacy, and money‑related microcopy. Clear portfolio; crisp writing. The stack you’ll touch Figma, call flow tools, prompt templates (YAML/JSON), analytics dashboards, usability testing suites, CallKit review workflows. How we work Campus pilots, weekly ships, privacy by architecture, written decisions, tiny senior team. Compensation ₹0.8L – ₹1.2L per month + meaningful equity . Board‑approved bands; refreshers tied to shipped impact. Apply Email talent@hushh.ai with the subject “MDS‑CXD — Fulltime/Internship (pick-one)” . Include links and five bullets on flows you improved and how you measured clarity and success in the real world with clear examples and Github repo references with the best project contributions you've completed so far in your personal and professional life / portfolio. Please note we are a small team with minimal overhead so please be patient with our responses as we have received over 100,000 applications for every job we open. We will prioritize candidates with completed applications and the best projects that showcase their open-source and community work along with their individual contributions.
Member of Technical Staff (MTS) — On‑Device ML (MTS‑EDGE) — Kharagpur/Pune/Bombay (On-site Lab=Garage Work from Office Only) Put intelligence where it earns trust: on the device, by default. If you get a thrill from shaving milliseconds, shrinking models, and making voice feel instant without shipping data to strangers, this is your stage. Why this role exists Kai and Nav are only as trusted as their privacy and responsiveness. On‑device inference gives us both. Your work delivers real‑time speech, local understanding, and smooth synthesis with battery and memory budgets that respect the user—and the product. What you’ll do Quantize, distill, and compile models (VAD/ASR/NLU/TTS/Small‑LLMs) for CoreML/Metal with streaming pipelines. Build offline fallbacks and clever on‑device first, cloud‑when‑necessary routing with clear consent gates. Instrument latency, accuracy, power, memory, and binary size; land targets and keep them there. Partner with iOS to ship low‑friction voice UX (barge‑in, barge‑out, interruption repair). Collaborate with Orchestration to design tool contracts that exploit edge capabilities (wake‑words, local context, cache). Maintain a reproducible toolchain (PyTorch → ONNX → CoreML) with deterministic builds and golden benchmarks. 30 / 60 / 90 outcomes 30 days : Baseline ASR+TTS pipeline running locally with streaming; p95 end‑to‑end voice turnaround 85% task‑success on the on‑device golden set; stable MOS for TTS; memory <300 MB at p95; <3% battery per 10‑minute assisted session. Signals we’re looking for You’ve shipped CoreML/Metal inference with real‑time audio and can show profiling traces. You’ve done quantization (INT8/INT4), distillation, or sparsity and can explain the trade‑offs. Comfort across Swift/C++ bridging, AVAudioEngine, and low‑latency I/O. Taste for graceful degradation and offline safety. The stack you’ll touch CoreML, Metal, Accelerate, AVAudioEngine, Swift/C++, PyTorch, ONNX, Python toolchains, Instruments, power/thermal profilers. How we work Campus pilots, weekly ships, privacy by architecture, ruthless measurement, written decisions, small senior team. Compensation ₹1.0L – ₹1.5L per month + meaningful equity . Board‑approved bands; refreshers tied to shipped impact. Apply Email talent@hushh.ai with subject “MTS‑EDGE — Full-time / Internship” Include code links and five bullets on how you beat a latency/accuracy/power target in the real world with clear examples and Github repo references with the best project contributions you've completed so far in your personal and professional life / portfolio. Please note we are a small team with minimal overhead so please be patient with our responses as we have received over 100,000 applications for every job we open. We will prioritize candidates with completed applications and the best projects that showcase their open-source and community work along with their individual contributions.