Senior Software Engineer, Machine Learning

As Senior Software Engineer, Machine Learning, you will work on the ML Platform Team with the CTO to elevate our machine learning platform and extend our state-of-the-art text-to-speech models. This includes optimizing our training pipeline, automating our data processing, and rewriting abstraction layers.

In your day-today, you’ll work on:

• Iteratively and incrementally improving the ease of use, reliability, and performance of our TTS service.
• Building automated training and data processing services.
• Developing data structures for loading, processing, and validating 1000s of hours of text and speech data.
• Improving the performance and the scalability of our machine learning training pipeline by integrating tools like DeepSpeed, PyTorch AMP, PyTorch JIT, and PyTorch Profiler.
• Being mindful and conscientious of AI ethics and the social impact of the work you do at WellSaid Labs.
• Open-source reusable libraries and tooling.

What We’re Looking For

To thrive in this role, you ideally have experience with and a solid understanding of ML concepts and best practices, experience with deep learning frameworks (e.g., PyTorch, Tensorflow, etc.), and  an understanding of the key elements to a good developer experience. Ideally, you also have some combination of the following:

• Experience in iteratively and incrementally developing a mature data-driven web service.
• 2 years experience using Pytorch professionally.
• Great attention to detail.
• Experience automating delivery pipelines and integrating continuous monitoring.
• Attention to creating modular, secure, and well-tested code.
• Experience building reusable tools to increase workflow efficiencies.
• A background using data structures and algorithms to process large amounts of data.
• Experience implementing automated model training and data processing.
• Experience implementing various tooling for speed up training and modeling.
• (Bonus) Has implemented lower level kernels and mixed precision.
• (Bonus) Experience with our tech stack which includes: C++, Python, CUDA, Docker, Google Kubernetes Engine.
• (Bonus) Experience with web technologies like HTML, CSS, React, Node.
• (Bonus) Experience profiling and optimizing deep neural network performance.

To join our team you must also:

• Be a U.S. Citizen or Permanent Resident
• pass a pre-employment background check

What We Offer

WSL is proud to support an inclusive work environment that emphasizes each team member’s personal and professional growth. Our team is fully distributed throughout the U.S., and we support flexible schedules – work where and when you work best. You’ll have teammates just a Slack message or video call away if you ever need help solving an exciting challenge, or even if you just have a funny story to tell.

Other perks and benefits:

• Competitive salary and stock options
• Full medical, dental, and vision insurance
• Matching 401(k) plan
• Generous vacation policy/paid time off
• Parental leave
• Learning & development stipend
• Home office stipend

As a startup, we strive to be externally competitive with companies at a similar size and stage, and internally fair in our pay practices. The hiring salary range for this role is $155,000 – $175,000  and represents the target offer range given the scope and experience expectations for this role.

What to Expect From Us

We strongly encourage you to apply! If we feel your skills, experience, and values match, we’ll reach out about meeting with the team.

During the interview stage, you can expect:

• An introductory interview with the hiring manager (50 minutes); if there’s a match we’ll schedule an interview loop with the team.
• A take-home assessment which involves implementing small suggested improvements from research papers in PyTorch
• An Interview loop with 3-4 interviews (1 hour each) with the team members you will be potentially working with

All interviews will be remote via Google Meets; we are happy to make accommodations you might need to feel comfortable and set up for success in our process.