Tenstorrent is seeking a Signal Integrity Engineer to join our growing team. The ideal candidate will have a wealth of exposure designing high speed interconnects, breakout design, material trade-offs and verification. A background in electrical engineering, electronics or relevant fields is required. Must love all things high speed!

This role is hybrid, based out of Santa Clara, CA or Austin, TX or Toronto, ON.

We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Who You Are

• You have a Bachelor’s degree in Electrical Engineering (or equivalent) and 5+ years working in high-speed digital design with a focus in high-speed PCB or package design at 10Gbps and above (e.g. 100GbE, GDDR6, PCIe Gen5+).
• You’re comfortable working with high-speed performance metrics such as ICR, ERL, COM, NEXT, and FEXT as well as knowledge of high-speed connector technologies, including NPO, CPO, and emerging standards.
• You are proficient with PCB ECAD tools (ideally Cadence Allegro).
• You communicate clearly (written and verbal), think critically, and love solving complex signal integrity problems.
• You’re enthusiastic about all things high speed and enjoy collaborating across teams

What We Need

• Design, extract, and simulate complex breakout structures, including end-to-end simulations and validation against physical hardware. Perform simulation and extraction of board models for both SI and PI.
• Contribute to design and sign-off with internal and external ASIC packaging teams, ODMs, and internal layout teams. Create design specifications, work with external vendors, and drive adoption of new interconnect and packaging technologies.
• Actively participate in design reviews, providing insight from your SI/PI expertise and a broader system perspective.
• Support post-silicon bring-up and help troubleshoot production and field failures related to signal and power integrity. Document design processes and provide training/knowledge sharing to other team members.

What You Will Learn

• How to work at the cutting edge of high-speed interconnects, influencing the next generation of ASIC packaging and PCB architectures.
• Deep exposure to advanced ASIC packaging flows and collaboration models with internal and external packaging teams.
• Hands-on experience with emerging high-speed connector technologies and materials, including evaluating material trade-offs for performance and manufacturability.
• Best practices for end-to-end SI/PI validation, from simulation through to lab correlation, post-silicon bring-up, and field failure analysis.

Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

About the Role:

As a Software Engineer on the ML Infrastructure team, you will collaborate closely with the Machine Learning and Product teams to build world-class machine learning inference platforms. These platforms power essential services like personalized recommendations, search, and content understanding across Tubi.

A core responsibility of this team is developing and maintaining low-latency ML model serving systems that support Deep Learning, LLM, and Search models. This involves building self-service infrastructure and critical components such as the inference engine, feature store, vector store, and experimentation engine.

You will improve the way we deploy and operate our services and even contribute to open-source projects. This role grants the architectural freedom to explore new frameworks, lead critical cross-functional projects, and transform the capabilities of our ML and Product teams.

We currently have multiple openings;

• Staff Software Engineer
• Principal Software Engineer
  • Additional Details: As a Principal Engineer on the ML Infrastructure team, you will be a technical leader and visionary, driving the evolution of our machine learning platform. You will tackle the most complex and impactful technical challenges, shaping the architecture and technology choices that enable our ML capabilities to scale and deliver exceptional user experiences. You will be a key influencer, bridging the gap between engineering and product, and a mentor to senior engineers, fostering a culture of technical excellence and continuous improvement. Your work will be used by millions of users.

Responsibilities:

• Design and build scalable, high throughput, and low latency distributed systems using Scala
• Build reusable components and services that serve various ML applications like Personalization, Search, Ads and Exploration
• Partner closely with ML engineers to understand their challenges and limitations and develop scalable solutions to address them. Proactively recommend solutions to keep our ML Inference stack state of the art.
• Take a data driven approach to identifying & optimizing latency, cost, and efficiency of our infra. Lead large scale cross functional refactorings if necessary
• Mentor other engineers on the team on system design, effective incident management, interviewing, leveraging LLMs for work, etc.
• Collaborate with ML, Product, and cross functional engineering teams to define the long term vision and architecture for ML Infrastructure at Tubi.  

Your Background:

• Experience designing and building scalable, distributed systems in any modern backend language (e.g., Scala, Java, Python, Go, C++); experience with Scala or JVM based language is a plus.
• Strong experience with AWS or an equivalent cloud platform
• Experience building online microservices at scale with low latency serving
• Experience with both SQL (e.g. Postgres) and NoSQL databases (e.g. Cassandra), message brokers (e.g. Kafka), and caches (e.g. Redis)
• Experience with containerization technologies, such as Docker or Kubernetes
• Led the response and resolution efforts for multiple major, large-scale incidents

Bonus:

• Familiarity with the machine learning infrastructure like inference engines (e.g. torschserve, triton, vLLM), vector stores (e.g. LanceDB, FAISS), feature stores (e.g. Feast), ElastiCache, model training orchestration, etc.
• Understanding of ML model training pipelines and model internals. Experience with Recommender Systems, Search, Autocomplete and Ads ML is a plus
• Previous experience with Akka, Erlang, Elixir or Go
• Proficient in data-driven analysis of complex A/B testing results

About Tubi:

Tubi is a free streaming service that entertains over 100 million monthly active users. Tubi offers the world's largest collection of Hollywood movies and TV shows, thousands of creator-led stories and hundreds of Tubi Originals made for the most passionate fans. Headquartered in San Francisco and founded in 2014, Tubi is part of Tubi Media Group, a division of Fox Corporation.

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