Research Software Engineer, Google Research

MINIMUM QUALIFICATIONS:

* Bachelor’s degree or equivalent practical experience.

* 2 years of experience with software development in one or more programming

languages, or 1 year of experience with an advanced degree.

* Experience in machine learning research, or quantitative research in fields

such as mathematics, physical sciences, engineering, or economics.

* Experience with machine learning frameworks (e.g., JAX or PyTorch).

PREFERRED QUALIFICATIONS:

* Master's degree or PhD in Computer Science or related technical fields.

* Publication in journals or conferences in machine learning or quantitative

fields such as mathematics, physical sciences, engineering, or economics.

* Experience with sequence modeling, machine translation, speech/audio

processing, diffusion language models, or reinforcement learning.

* Experience in building, scaling, and optimizing complex machine learning

systems.

* Contribution to major open-source projects related to machine learning such

as JAX, PyTorch, HuggingFace Transformers, Kaldi K2, ESPNet.

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.

Our team is pioneering new ways to interact with audio by building the next

generation of foundational audio models. In this role, your mission is to

deliver quality across practical audio tasks while achieving ultra-low latency

and extreme cost-effectiveness as we are fundamentally rethinking the stack,

focusing on novel sequence modeling architectures, new training methods, and

advanced inference algorithms. You will innovate at the foundational level as

our work has the potential to expand across other modalities. You will as a

tightly knit, milestone-oriented team within Google Research that relies on

close collaboration to push the boundaries of machine learning and turn

ambitious research into reality.

Google Research addresses challenges that define the technology of today and

tomorrow. From conducting fundamental research to influencing product

development, our research teams have the opportunity to impact technology used

by billions of people every day.

Our teams aspire to make discoveries that impact everyone, and core to our

approach is sharing our research and tools to fuel progress in the field -- we

publish regularly in academic journals, release projects as open source, and

apply research to Google products.Individual pay is determined by factors

including job-related skills, experience, and relevant education or training.

US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google

[https://www.google.com/about/careers/applications/benefits/].

RESPONSIBILITIES:

* Design, implement, and rigorously test novel modeling and algorithmic

improvements for foundational audio models.

* Solve complex, open-ended challenges in audio understanding architectures,

sequence modeling, and fast inference.

* Write product or system development code to integrate and evaluate audio

capabilities across the ecosystem.

* Participate in or lead design reviews with peers and stakeholders to decide

amongst available technologies.

* Triage product or system issues and debug, track, and resolve them by

analyzing the sources of issues and their impact on service operations and

quality.