Technical Lead Manager, Applied AI

Reposted Yesterday
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Singapore, SGP
In-Office
Senior level
Artificial Intelligence
The Role
Lead an engineering team to design, build, and deploy scalable generative-AI applications. Translate research into products, optimize ML infrastructure, mentor engineers, and drive 0-to-1 product development with partners and PMs.
Summary Generated by Built In
Job Description

We are seeking a Technical Lead Manager (TLM) to lead the development and deployment of novel applications, leveraging Google’s generative AI models. This role focuses on rapidly developing new features, and working across partner teams to deliver solutions, and maximize impact for Google & top Google customers. You will be instrumental in translating cutting-edge AI research into real-world products, and demonstrating the capabilities of latest generation models. We are looking for a TLM with a strong track record of building and shipping software, and leading engineering teams, ideally with some experience in early-stage environments, where you may have contributed to scaling products from initial concept to production. The ideal candidate will be motivated by the opportunity to drive product & business impact, and develop strong relationships with research teams.

This role requires a strong software engineering foundation, a passion for building and iterating on software products, and proven leadership skills. We are looking for a TLM who thrives in fast-paced environments, and has the proven ability to deliver high-quality code & guide a team to success. Experience in end-to-end development is essential, as is the ability to mentor and develop junior engineers. We particularly value experience in early-stage or startup environments, where managers take ownership and drive product development from the ground up.

Job responsibilities
  • Lead a team in the design and development of scalable software applications leveraging generative AI models.
  • Guide the team in rapidly developing new features and iterating based on evaluation results.
  • Collaborate with researchers and product managers to translate research advancements into tangible product features.
  • Oversee the optimization of software performance and ensure the reliability of deployed applications.
  • Champion the development of best practices for building and deploying generative AI applications.
  • Lead the architecture and development of new products & features from 0 to 1.
  • Mentor and develop team members, fostering a collaborative and high-performing environment.
  • Partner with PM team to qualify & size new project opportunities.

Minimum qualifications:

  • A bachelor degree in computer science, electrical engineering or equivalent experience.
  • 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
  • 5 years of experience in minimum of one ML field (eg. media generation, reinforcement learning, infrastructure etc.)
  • 7+ years of experience leading technical projects and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning), including at least 5 years of experience in a people leadership role overseeing and guiding technical teams.

Preferred qualifications:

  • Experience with generative AI models and applications.
  • Contributions to open-source projects.
  • Experience with front-end development.
  • Proven experience in rapidly developing and shipping software products in a fast-paced, customer-facing startup-like environment, demonstrating adaptability to changing priorities.
  • Experience evaluating model performance, analyzing results, and implementing improvements.
  • Experience with cloud computing platforms and infrastructure (e.g., Google Cloud Platform, AWS, Azure).
  • Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Hugging Face, etc.

Skills Required

  • Bachelor's degree in computer science, electrical engineering, or equivalent experience.
  • 8 years of software development experience in one or more languages (Python, C, C++, Java, JavaScript).
  • 5 years of experience in at least one ML field (e.g., media generation, reinforcement learning, infrastructure).
  • 7+ years leading technical projects and optimizing ML infrastructure (model deployment, evaluation, data processing, debugging, fine-tuning).
  • At least 5 years of people leadership overseeing and guiding technical teams.
  • Proven experience building and shipping production software and end-to-end development.
  • Ability to mentor and develop junior engineers.
  • Experience with generative AI models and applications.
  • Contributions to open-source projects.
  • Experience with front-end development.
  • Proven experience rapidly developing and shipping software in fast-paced, customer-facing startup-like environments.
  • Experience evaluating model performance and implementing improvements.
  • Experience with cloud computing platforms and infrastructure (Google Cloud Platform, AWS, Azure).
  • Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Hugging Face.
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The Company
1,218 Employees
Year Founded: 2010

What We Do

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. Our long term aim is to solve intelligence, developing more general and capable problem-solving systems, known as artificial general intelligence (AGI). Guided by safety and ethics, this invention could help society find answers to some of the world’s most pressing and fundamental scientific challenges. We have a track record of breakthroughs in fundamental AI research, published in journals like Nature, Science, and more.Our programs have learned to diagnose eye diseases as effectively as the world’s top doctors, to save 30% of the energy used to keep data centres cool, and to predict the complex 3D shapes of proteins - which could one day transform how drugs are invented.

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