Senior Software Engineer, Machine Learning (Remote)

Who We Are: WellSaid Labs 

We’re creating Voice for everyone.

At WellSaid Labs, we enable creatives around the globe by putting high-tech, human parity technology into their hands, giving them the ability to add voice-over to any project and iterate with ease. Creative teams use WellSaid Lab’s Voice Studio to create compelling employee training, design unique digital experiences, and narrate audiobooks. We believe deeply in AI for Good, and that technology should be empowering, engaging, and fair to all people

Who You Are: 

The WellSaid Labs Applied Machine Learning Team works with stakeholders to identify, refine, and solve problems at the intersection of machine learning and customer needs. This team understands customer needs through quantitative and qualitative research and they work across WSL teams to understand how machine learning is utilized and how it can be improved. 

working with the ML Platform Team to prioritize model updates, training new models for deployment, and coordinating releases and educating the customer on any new capabilities. The Applied ML Team is consistently testing and reviewing any deployed models.

As a Senior Software Engineer, Machine Learning at WellSaid Labs, you will be working to regularly improve our text-to-speech service. 

How You’ll Contribute:  

As Senior Software Engineer, Machine Learning, you will work with the CTO to elevate the developer experience for our state-of-the-art Deep Learning TTS service. This includes optimizing our training pipeline, automating our delivery pipelines, 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 tooling for automating custom voice creation.
• Setting up a CI / CD pipeline.
• 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.
• Automating and monitoring our TTS deployment. You'll manage standard metrics like latency, performance, and cost. You'll also keep track of TTS metrics like loudness, cadence, and naturalness.
• Improving the scalability of our TTS deployment.
• 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.
• 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: PyTorch, 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 technical screen, as a take-home assessment 
• 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. 

WellSaid Labs is honored to be an equal opportunity workplace. We realize that by bringing together teams rich in diverse thoughts and experiences, our people, company, and customers are free to flourish. We are committed to providing equal employment opportunities regardless of race, color, national origin, religion, creed, genetic information, sex (including pregnancy, sexual orientation or gender identity), age, marital status, disability, military or veteran status; or any other protected classifications or characteristics under applicable local laws.