DeepMind

Senior Production Engineer, Enterprise Engineering

Mountain View, CA US
USD 142k - 219k
Machine Learning Swift Streaming
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Description

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

Snapshot

We are seeking an experienced Production Engineer to lead and drive technology projects in our workplace. The Enterprise Engineering team design, develop and support world class infrastructure to accelerate our research progress. We are always looking to embrace cutting-edge technologies to provide the tools our research teams require to change the world!

About us

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

The role

This is a unique role that offers a diverse workload from systems design and continual improvement to low level support of the entire signal chain, from acquisition all the way through to Internet distribution.

Reporting to the Head of Enterprise Engineering, you will help define and drive user requirements, be responsible for following design guidelines, owning technical design and acting as a point of technical escalation for global event studios.

Just as we have ambitious research goals, we have ambitious goals for our production systems, we are embracing cutting edge IP video and audio technologies to provide the tools our research teams require to change the world.

Key responsibilities

  • Drive operational excellence: Ensure high availability and optimal performance across all research facilities. You'll champion proactive monitoring, preventative maintenance, and rapid incident response, minimizing downtime and maximizing system performance.
  • Own the detailed technical design of critical infrastructure, translating the organisation’s needs into robust and scalable solutions.
  • Act as the escalation point for critical system issues, troubleshooting complex problems and collaborating with vendors to drive swift resolutions.
  • Proactively identify emerging technologies and collaborate with vendors (including production equipment manufacturers) to implement solutions that anticipate and meet the future needs of our research teams.
  • Managing site upgrades to ensure operational stability
  • Partner with research teams on an ad hoc basis to understand their unique needs and provide tailored support
  • Ensure facility documentation is up to date and correct
  • Lead research projects, managing suppliers, integrators and budgets
  • Establish the feasibility of any minor developments including the production of costing, effort, and timescales for management approval
  • Act as EIC (Engineer In Charge) for high profile moments

About you

We are a team of domain specialists, and we are looking for a candidate with deep Infrastructure Engineering experience. You should have a solid understanding of networking technology to inform troubleshooting, maintenance and planning and will partner closely with network engineers within the team.
In order to set you up for success as an Infrastructure Engineer at Google DeepMind, we look for the following skills and experience:

Technical Expertise:

  • You're an expert in IP video and audio technologies (including 2022-6/7, ST2110, Dante, AES67), with a deep understanding of baseband video standards and analog audio.
  • You have a strong grasp of IP networking (IGMP, DNS, DHCP, routing, L2 encryption) and are adept at troubleshooting network behavior using packet capture and inspection tools.
  • Ideally, you have experience with broadcast systems like EVS IPDirector, Ross production switchers, Evertz Routing & Glue, and contribution encoders. Familiarity with digital video codecs and internet streaming is a plus!

Problem-Solving and Communication:

  • You possess a keen eye for detail and a logical approach to troubleshooting, enabling you to calmly and effectively resolve complex technical challenges.
  • You're an excellent communicator, capable of explaining intricate technical concepts to both technical and non-technical audiences.

Teamwork and Initiative:

  • You thrive in a collaborative environment and are comfortable working with individuals at all levels of the organization.
  • You're a proactive problem solver who takes initiative to identify and address technology gaps, collaborating with equipment manufacturers to find the best solutions.

Passion for Innovation:

  • You're excited to push the boundaries of broadcast technology, constantly seeking ways to improve our infrastructure and empower our researchers.
  • Experience with AutoCAD for managing technical facility documentation is a plus.\

The US base salary range for this full-time position is between $142,000 - $219,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

Note: In the event your application is successful and an offer of employment is made to you, any offer of employment will be conditional on the results of a background check, performed by a third party acting on our behalf. For more information on how we handle your data, please see our Applicant and Candidate Privacy Policy.

DeepMind
DeepMind
Artificial Intelligence (AI) Business Development Machine Learning

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