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Put your name on a generational chip.

Hiring those moving at speed, building the lowest-power edge compute chip. High ownership, meaningful equity, no silos. No assholes.

Engineering Unpaid . Part-time
Pre-funding at this stage — this is not a paid position.

Define and drive the architecture of Biio's core compute engines — from ISA definitions and programming models through memory hierarchies and on-chip interconnects. Lead the overall chip architecture and tape-out program, own foundry and EDA relationships, and be the driving force behind the computational heart of our products, ensuring every cycle counts and every watt is well spent.

Your challenges
  • Define and own compute engine architecture specifications, balancing performance, flexibility, power, area, and design complexity
  • Lead architectural exploration from early concept through to specification, coordinating across modelling, implementation, verification, and physical design teams
  • Specify execution units, memory hierarchy, instruction sets, and data flow — making principled trade-offs at every level
  • Build and maintain performance models and simulators to guide architectural decisions with data
  • Manage foundry and EDA relationships; prepare and evaluate end-to-end SoC designs for tapeout
  • Evaluate emerging techniques — compact number formats, novel compute paradigms, advanced packaging — to inform the roadmap
  • Act as a technical mentor, raising the bar for rigour in performance analysis and architectural documentation across the team
Your profile
  • Startup experience, or experience from one of the top organisations
  • Degree in Electronic Engineering, Computer Science, Mathematics, Physics, or similar
  • 10+ years of industry experience in processor or ASIC architecture, with at least 3 full tapeout cycles to your name
  • Deep understanding of compute engine and processor architecture, including matrix/vector-centric floating-point arithmetic and memory hierarchies
  • Strong grasp of RTL design flows and physical design constraints, and how they feed back into architectural choices
  • Experience taking designs from early exploration through to tapeout and post-silicon performance characterization
  • Background in AI acceleration, vector/matrix compute, or domain-specific processor design is highly desirable
  • Excellent communicator who can bridge architectural depth with system- and product-level context
Apply — attach your CV →
Pre-funding at this stage — this is not a paid position.

Work directly with the founders as a force multiplier — owning whatever needs owning to help a 10-person team move at the speed of a much larger one. One week that's fundraising support and investor materials, the next it's operations, hiring pipeline, customer research, or standing up an internal process from scratch. A high-trust, high-ambiguity role for someone who wants to see how a deep-tech company is built from the ground up.

Your challenges
  • Be the founders' right hand — take ambiguous problems off their plate and drive them to done
  • Support fundraising: investor research, data-room prep, deck iteration, and follow-ups
  • Run operations and internal processes — set up the systems a growing team needs before it needs them
  • Own the hiring pipeline end-to-end: sourcing, scheduling, candidate communication, and keeping the process moving
  • Dig into customer and market research to sharpen positioning and go-to-market
  • Jump into whatever is on fire that week — no task too big or too small
Your profile
  • Startup experience, or experience from one of the top organisations
  • Exceptional generalist — organised, resourceful, and comfortable with ambiguity
  • Bias for action: makes 80% decisions quickly and iterates
  • Strong written and verbal communication; can represent the company to investors and customers
  • No ego — will write docs, join customer calls, and do whatever the team needs
  • Genuine interest in deep tech, hardware, or edge AI is a strong plus
Apply — attach your CV →
Pre-funding at this stage — this is not a paid position.

Design the architecture and micro-architecture of an ultra-low-power ASIC on modern process technologies (≤ 28nm). Write SystemVerilog and code new tests to validate the design, do logic design and validation of custom IP, evaluate and integrate IP such as RISC-V, and prepare the end-to-end SoC design for silicon tapeout.

Your challenges
  • Design and implement low-power techniques for RISC-V cores (clock gating, power gating, DVFS, multi-Vt, etc.)
  • Implementation on FPGA
  • Work across architecture, RTL, and physical design teams to integrate low-power features
  • Perform power analysis, estimation, and optimization at block and system level
  • Bring-up, debug, and test of the developed solutions on hardware
  • You are passionate about low-power processor design and architecture
Your profile
  • Startup experience, or experience from one of the top organisations
  • Degree in a technical subject — electronic engineering, computer science, mathematics, physics, or similar
  • 5+ years of industry experience in low-power digital design, with focus on RISC-V or similar CPU architectures
  • Solid knowledge of RTL design (SystemVerilog or Verilog) and power-aware simulation
  • Experience with ultra-low-power designs
  • Understanding of the RISC-V ISA and RISC-V power
Apply — attach your CV →
Pre-funding at this stage — this is not a paid position.

Develop the machine learning compiler stack for Biio's AI acceleration hardware. Enable industry-leading performance of the latest AI models on Biio's accelerators, working with hardware and ML engineers in a highly collaborative hardware-software co-design methodology — directly shaping how intelligence runs at the edge.

Your challenges
  • Build and optimize the end-to-end ML compiler stack targeting Biio's custom AI accelerators
  • Map state-of-the-art neural network models onto novel compute architectures with maximum efficiency
  • Develop and maintain compiler infrastructure using industry-standard technologies such as MLIR, LLVM, or TVM
  • Drive performance analysis, profiling, and bottleneck resolution across the full software-hardware stack
  • Work closely with hardware and architecture teams to feed software requirements back into silicon decisions
  • You are passionate about the intersection of compiler technology, AI, and energy-efficient hardware
Your profile
  • Startup experience, or experience from one of the top organisations
  • Degree in Computer Science, Electronic Engineering, Mathematics, Physics, or similar
  • 3+ years of industry experience in compiler development, with focus on ML or hardware-targeting compilers
  • Solid knowledge of C/C++ and hands-on experience with compiler frameworks such as LLVM
  • Experience with machine learning compiler infrastructure (MLIR/IREE, TVM, or similar)
  • Familiarity with polyhedral compilation techniques is a plus
  • Creative and innovative mindset, with a willingness to take ownership in a fast-paced environment
Apply — attach your CV →
Pre-funding at this stage — this is not a paid position.

Own the AI layer on both sides of Biio's operation: automate and accelerate the internal engineering workflows that let a 10-person team move at the speed of a much larger one, and build the model deployment pipelines that get neural networks running efficiently on Biio silicon. A dual-charter role — half productivity multiplier for the company, half technical contributor to the core product.

Your challenges
  • Design and deploy internal AI workflows that eliminate repetitive overhead across engineering, documentation, simulation analysis, and customer communication — if a task is repeatable, it should be automated
  • Build and maintain the end-to-end model deployment pipeline from PyTorch/ONNX through quantization, compression, and execution on Biio's edge AI architecture
  • Work directly with the compiler and ASIC teams to validate model accuracy and power behaviour through the full INT4/INT8/INT16 quantization flow
  • Develop tooling that makes it faster for OEM customers to evaluate Biio silicon — reducing the friction between a trained model and running inference on-device
  • Identify and implement LLM-assisted workflows for code review, design documentation, test generation, and simulation result analysis
  • Stay close to the bleeding edge of AI tooling — evaluate new models, agents, and frameworks with a ruthless focus on what actually saves time or ships faster
Your profile
  • Startup experience, or experience from one of the top organisations
  • Degree in Computer Science, Electrical Engineering, or a related field
  • 3+ years working across ML model deployment and/or AI-powered automation workflows
  • Hands-on experience with model optimisation techniques: quantization, pruning, knowledge distillation, ONNX export
  • Comfortable working across the stack — from Python scripting and CI/CD pipelines to understanding the hardware constraints that shape deployment decisions
  • Experience building with LLM APIs, agent frameworks, or workflow automation tools (LangChain, n8n, or similar)
  • A mindset that treats internal tooling as a product: if it isn't used, it doesn't count
  • Familiarity with edge inference runtimes (TFLite, ONNX Runtime, or similar) is a strong plus
Apply — attach your CV →
Internships Unpaid · Part-time
Pre-funding at this stage — this is not a paid position.

Work alongside our ASIC team on the physical implementation of an ultra-low-power chip on modern process technologies (≤ 28nm) — taking RTL through to a tapeout-ready layout. A hands-on internship for someone eager to learn the back-end flow on real silicon. Location-flexible.

What you'll do
  • Support the physical design flow — floorplanning, placement, clock tree synthesis, and routing (place-and-route)
  • Help run and analyse static timing analysis (STA) and close timing across corners
  • Assist with power, area, and congestion optimization at block and top level
  • Run physical verification checks (DRC / LVS) and help resolve violations
  • Contribute to the end-to-end SoC design as it's prepared for silicon tapeout
  • Learn low-power implementation techniques — clock gating, power gating, multi-Vt
Your profile
  • Working toward a degree in electronic engineering, computer science, or a related technical field
  • Familiarity with digital design fundamentals and the ASIC back-end flow
  • Exposure to EDA tools for place-and-route or timing analysis (e.g. Cadence, Synopsys) is a plus
  • The right skills and attitude — bias for action, no ego, intrinsic drive
Apply — attach your CV →
Pre-funding at this stage — this is not a paid position.

Support our ASIC engineers on the design architecture and micro-architecture of an ultra-low-power ASIC on modern process technologies (≤ 28nm). A hands-on internship for someone with the right skills and attitude, working on our proof of concept. Location-flexible — a chance to work on real silicon.

What you'll do
  • Support ASIC engineers with design architecture and micro-architecture of an ultra-low-power ASIC on modern process nodes (≤ 28nm)
  • Write SystemVerilog and code new tests to validate the design
  • Logic design and validation of custom IP
  • Evaluate and integrate IP such as RISC-V
  • Prepare and evaluate the end-to-end SoC design for silicon tapeout
  • Design and implement low-power techniques for RISC-V cores (clock gating, power gating, DVFS, multi-Vt, etc.)
Your profile
  • Working toward a degree in electronic engineering, computer science, or a related technical field
  • Familiarity with SystemVerilog/Verilog and digital design fundamentals
  • Exposure to RISC-V, FPGA prototyping, or low-power techniques is a plus
  • The right skills and attitude — bias for action, no ego, intrinsic drive
Apply — attach your CV →

Don't see your role but think you'd move the needle? We hire to solve a gap — make the case. careers@biio.ai