Dialpad is the most modern business communications company in the industry. Our products range from conferencing calling, to phone systems to contact center solutions that are all built with the end-user in mind. We allow workers to be productive from anywhere on any device and have moved all the power of an on-premise phone system or contact center to the cloud to be accessed and used by modern workers in today’s Work from Anywhere environment.
Who We Are
At Dialpad, work isn’t a place you go, it's a thing you do. We not only build products to enable the everywhere worker, but we also are everywhere workers. With offices in San Francisco, San Ramon, Austin, Raleigh, Vancouver, Waterloo, Tokyo, London and Bangalore, we truly believe in finding the best talent everywhere. We also embrace the Work from Home movement and are just as happy hiring great talent from anywhere if they choose to work from home rather than in an office.
With $120 million in funding from ICONIQ Capital, Google Ventures, Andreessen Horowitz, Scale Ventures and other top VC’s Dialpad attracts top engineers from companies like Microsoft and Google, and every member of our team plays an essential role in creating dynamic products that enable workers to be productive from anywhere.
About The Role
We're developing state-of-the-art machine learning models for automated speech recognition and natural language processing (ASR and NLP). This role will work closely with our Machine Learning and Data Engineering teams to optimize, deploy and maintain models running in real-time at large scale. We're always looking to improve -- to make the models more accurate, run faster, and utilize resources more effectively.
Do you have experience optimizing models leveraging TensorFlow, PyTorch, XGBoost, and other frameworks? Tell us about a time you needed to make something 10% faster or 20% smaller without sacrificing accuracy.
- You know your way around profilers
- You've grappled with Python, dealing with the GIL and threading models
- You have worked with CUDA, MKL, or other ML library dependencies
- You're tracking and implementing current methods to prune deep learning models or to optimize them for specific platforms
- You hate to speculate about code performance and prefer to gather data, run experiments, and really dive deep to understand the runtime and find opportunities to optimize
- You have experience with HPO methodologies and tools for various frameworks, and
- You’ve worked with virtualization stacks (Docker, Kubernetes, etc.) and cloud infrastructure
- Bachelor's degree in Computer Science or related field required. Master's degree a plus
- 3+ years of industry experience
- Demonstrated hands-on experience making things faster, cheaper and better
- Hands-on experience working with HPO and model optimization projects such as TVM or XLA
Joining our team means collaborating with people that aren’t just passionate about their work but about Argentine tango, musicals, sushi burritos, comic books - you name it. Because if you’re going to redefine the status quo, you need a group of people hungry to do more, to see more, and be more than where they started.
There is no idea too crazy and no task too small — we work together to make things we’re proud of.
Compensation & Equity
Teamwork makes the dream work. We recognize that our dedicated team members are what make us successful. That’s why we offer competitive salaries in addition to stock options.
An apple a day keeps the doctor away - and it doesn’t hurt that we offer 100% paid medical, dental, and vision plans for all employees.
We offer a monthly stipend to help cover your cell phone, home internet, and even gym membership costs.
We believe in your future as much as you do! That's why we offer a yearly stipend for continued learning and education expenses.
Bon Appetit! Enjoy catered lunches, free snacks & drinks (both healthy and unhealthy - no judgment!)
Location, Location, Location
San Francisco <> San Ramon <> Austin <> Raleigh <> Vancouver <> Kitchener <> Tokyo <> New York <> Bangalore. From coast to coast, our offices are nestled in active and growing downtown areas
Dialpad is an equal opportunity employer; we believe in creating a community of inclusion and an environment free from discrimination or harassment.