2 meilleures offres (backend engineer (python)) (à pourvoir)

Technical Lead – Physical Design (RTL to GDSII)
Synthara AG —Zürich, ZH
- Python
Staff / Principal Machine Learning Engineer, Serving - Switzerland
Inworld AI —Suisse
- 100%
- Télétravail
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- Anglais
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il y a 1 jour

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Technical Lead – Physical Design (RTL to GDSII)

Synthara AG
Zürich, ZH

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Détails de l'emploi

Qualifications

Git
Python

Description complète du poste

Role

Location: Zürich, Switzerland
Seniority: 10+ years (ASIC implementation; 2+ tapeouts as owner)

Own the end-to-end RTL-to-GDSII implementation for complex IP/SoC subsystems and build the backend team that scales it. You’ll define the methodology, constraints, and quality metrics that the team shall adhere to. The team you lead will be responsible for synthesis, floor planning, P&R, clock tree synthesis, multi-corner STA, design for testability, and ECOs to achieve sign-off. You and your team will collaborate tightly not only with our RTL/digital team but also with our full-custom and full-custom layout team, integrating our full-custom design blocks into a digital-on-top mixed ASIC design. This is a hands-on technical leadership role, where you will not only set the flow and lead the team, but also personally de-risk and own the most challenging aspects of the design.

What you’ll do

Methodology: Define and maintain a modern RTL-to-GDS flow, including constraint strategy, libraries/PDKs, UPF/CPF, and sign-off checks.
Implementation: Run synthesis, floorplan, partitioning, P&R, CTS, routing, extraction, and closure.
PPA & quality: Create predictable PPA targets and tracking, lead timing/power ECOs; correlate pre/post-layout timing
Integration: Integrate custom macros, SRAMs, and I/O, manage clocking strategy, CDC, and hierarchical/hard-macro integration with LEF.
Low power: Own power intent (UPF/CPF), isolation/retention strategies, level shifting, and power-aware STA/simulation.
DFT & test hooks: Partner with DFT on scan/MBIST insertion and test timing; ensure routes and constraints don’t compromise test coverage or bring-up.
Automation & CI: Industrialize the flow with Tcl/Python automation, reproducible configurations, metrics dashboards, and CI/CD for nightly builds and regression testing.
Team: Recruit and performance-develop a 5+ engineer group, set sign-off standards, and ideally establish a flow-based build ensuring repeatability.
Foundry interface: Engage with foundries on PDK updates, waiver handling, antenna/density rules, and reliability guidance; maintain the flow of information.

Outcomes (first 18 months)

Tapeout of one or more blocks/subsystems with MCMM (Multi Corner Multi Mode) timing, closed, clean DRC/LVS, and signed-off IR/EM.
A documented, automated PD flow adopted across projects, with measurable cycle-time and PPA improvements.
A staffed and functioning backend team with clear ownership areas (timing, power/IR, integration, sign-off) and reliable execution metrics.
Golden constraints and library strategy (views, corners, derates) with proven correlation (synth – P&R – sign-off) and predictable ECO closure.

Requirements

10+ years in ASIC physical design; 2+ successful tapeouts as block/subsystem owner from synthesis to sign-off.
Deep expertise in one complete tool chain (Synopsys or Cadence)
Hands-on experience in power-optimization techniques, including glitch reduction and activity-based power correlation (VCD/SAIF).
Strong MCMM STA and timing-closure experience
Experience with grid planning, IR/EM analysis, and fixes. Proven floorplanning/partitioning and hierarchical integration (hard-macros, abstracts/LEF, feedthroughs, blockage strategy).
UPF/CPF know-how for multi-voltage, power-gated designs, including isolation/retention and power-aware STA and sim.
Scripting for automation (Tcl, Python) and version control (Git, Perforce, or similar)
Ability to work and lead the activities independently and assume responsibility for major decisions

Nice to have

DFT exposure (scan planning, test timing, MBIST integration) and formal equivalence workflows.
Package/board co-design awareness (bump/rail planning, SSO/PI, thermal assumptions).
7 nm FinFET) with multi-patterning/EUV constraints and variability considerations.
Familiarity with sign-off for safety-/quality-critical markets (automotive-style reliability targets, waiver governance, documentation rigor).

Apply

Send your CV and a short note (2–3 paragraphs on a design you owned, your toughest bug & how you solved it, an intro on what you like to do and how you see yourself as an engineer)

Interview flow (indicative)

30-min intro with HR (role/context)

First Technical deep dive

Second Technical Deep Dive

(Optional) Third Technical Deep Dive

Systems/product conversation with management

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backend engineer (python) emplois

Technical Lead – Physical Design (RTL to GDSII)

Staff / Principal Machine Learning Engineer, Serving - Switzerland