Senior Research Engineer, AI/ML

2 Days ago • 5-8 Years • Research & Development • Artificial Intelligence

Job Summary

Job Description

As a Senior Research Engineer at Fitbit (a Google company), you'll contribute to the development of cutting-edge AI/ML solutions for their health and fitness products. Responsibilities include designing, implementing, and testing machine learning models, collaborating with stakeholders, contributing to documentation, and troubleshooting system issues. You'll work with frameworks like TensorFlow, PyTorch, or Jax, focusing on model pretraining, fine-tuning, evaluation, and optimization. The role requires experience in software development, testing, and design, along with a strong understanding of data structures and algorithms. The ideal candidate will have a Master's or PhD in a relevant field and experience publishing research in machine learning journals.
Must have:
  • 5+ years experience with data structures and algorithms
  • 3+ years software product testing and launch experience
  • Experience with ML model training, evaluation, and optimization
  • Proficiency in TensorFlow, PyTorch, or Jax
  • Software design and architecture experience
Good to have:
  • Master's or PhD in CS or related field
  • Publications in machine learning journals
  • Experience with Python and C++

Job Details

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 5 years of experience with data structures or algorithms and software development in one or more programming languages.
  • 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  • Experience with machine learning model pretraining, fine-tuning, evaluation, and optimization methodologies.
  • Experience in using common machine learning frameworks such as Tensorflow, PyTorch or Jax.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical field.
  • Experience publishing in high-quality machine learning journals.
  • Experience in Python and C++.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions. Fitbit’s wide range of innovative products, including smartwatches, trackers, and a smart scale, help people lead healthier, more active lives by empowering them with data, inspiration, and guidance to reach their health and fitness goals. Coupled with our leading software and Fitbit Premium, our immersive platform experience delivers personalized experiences, insights, and guidance to support our users’ health and wellness. Fitbit’s mission has always been to help make everyone in the world healthier and now, as part of Google we’ll be able to make health even more accessible to everyone.

Responsibilities

  • Write and test product or system development code.
  • Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency,)
  • Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
  • Design and implement solutions in one or more specialized machine learning areas, leverage or build machine learning infrastructure, and manage machine learning project life-cycle.
  • Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.

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