Splice

Senior Machine Learning Engineer - Generative Models (Remote)

Remote US
USD 165k - 206k
Machine Learning Deep Learning GCP Python TensorFlow PyTorch Azure Docker Git AWS Kubernetes Unity C++
Search for More Jobs Talk to a recruiter now 💪
Description

WHO WE ARE:  

We are a producers playground, delivering music creators the tools they need to bring their ideas to life. With a massive, industry-leading catalog of licensed samples, paired with powerful AI, and access to affordable plugins and DAWs, Splice kicks sound discovery, inspiration, and creative output into overdrive. 

HOW WE WORK:  

At Splice, DISCO is a rallying cry for collaboration, accountability and unity within our organization; Direct, Inclusive, Splice Together, Creator Centric and Optimistic. Our shared success depends on our ability to support one another, work well together and communicate directly. By embracing flexibility and a unified approach, we can navigate anything that’s thrown at us. 

Splice embraces a culture of remote work. You’ll see your colleagues showing up from across the US and the UK. In order to keep us working well as a team, we have regular communication, including Town Halls, departmental All Hands and get-togethers.

When you join Splice, you join a network of colleagues, peers, and collaborators. Are you ready?

JOB TITLE: Senior Machine Learning Engineer

LOCATION: Remote / NY

TEAM INFORMATION:

The Splice AI & Audio Science team is dedicated to pushing the boundaries of artificial intelligence applied to audio data, with the mission to empower music creators everywhere. Being musicians ourselves, we are deeply committed to the use of AI in a creator-centric, ethical and responsible way. Our team consists of passionate and creative individuals who thrive in a collaborative, innovative, and fast-paced environment.

WHAT YOU WILL DO:

  • Design, adapt and optimize cutting-edge model architectures for generative audio/music applications, leveraging state-of-the-art deep learning techniques for audio/music synthesis.
  • Collaborate with other Applied Researchers and Machine Learning Engineers to design, train, fine-tune, and deploy scalable models to production.
  • Explore and implement core building blocks in generative models, such as general Variational Autoencoders (VAEs), Neural Audio Codecs (RVQ / VAE), GANs, Diffusion Models, and Transformer-based architectures.
  • Contribute to integrating machine learning models into Splice’s products, delivering new and creative experiences for music creators.
  • Performance Benchmarking and Evaluation**:** design and run experiments to benchmark the accuracy, quality and performance of trained models.
  • Stay current with the latest advancements in machine learning applied to generative models in the audio domain, incorporating and sharing relevant insights into the applied research process.
  • Documentation and Knowledge Sharing**:** document experiments, best practices, and lessons learned to facilitate knowledge sharing and maintain reproducibility. Provide technical guidance and training to team members on model training, evaluation, deployment and optimization techniques.

JOB REQUIREMENTS:

  • Master's or PhD degree in Electrical Engineering, Computer Science or related Engineering discipline.
  • Proven ability and track record designing, training, evaluating and deploying machine learning models in production environments, powering real applications.
  • 2+ years of hands-on experience with generative models architectures in the audio, image or language domains. Specific experience with Latent Diffusion Models and Transformer-based architectures is a must.
  • Proficiency in Python, C/C++, or CUDA. Strong proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch).
  • Hands-on experience with cloud services (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
  • Comfortable with software development best practices and version control systems (e.g., Git).

NICE TO HAVES:

  • Familiarity with audio signal processing, music information retrieval (MIR), or audio synthesis techniques is a strong plus.
  • Background or knowledge in music production.

 

The national pay range for this role is $165,000 - $206,000. Individual compensation will be commensurate with the candidate's experience.

Splice is an Equal Opportunity Employer 
Splice provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Splice
Splice
Machine Learning Media and Entertainment Music Software

0 applies

3 views

There are more than 50,000 engineering jobs:

Subscribe to membership and unlock all jobs

Engineering Jobs

60,000+ jobs from 4,500+ well-funded companies

Updated Daily

New jobs are added every day as companies post them

Refined Search

Use filters like skill, location, etc to narrow results

Become a member

🥳🥳🥳 401 happy customers and counting...

Overall, over 80% of customers chose to renew their subscriptions after the initial sign-up.

To try it out

For active job seekers

For those who are passive looking

Cancel anytime

Frequently Asked Questions

  • We prioritize job seekers as our customers, unlike bigger job sites, by charging a small fee to provide them with curated access to the best companies and up-to-date jobs. This focus allows us to deliver a more personalized and effective job search experience.
  • We've got about 70,000 jobs from 5,000 vetted companies. No fake or sleazy jobs here!
  • We aggregate jobs from 5,000+ companies' career pages, so you can be sure that you're getting the most up-to-date and relevant jobs.
  • We're the only job board *for* software engineers, *by* software engineers… in case you needed a reminder! We add thousands of new jobs daily and offer powerful search filters just for you. 🛠️
  • Every single hour! We add 2,000-3,000 new jobs daily, so you'll always have fresh opportunities. 🚀
  • Typically, job searches take 3-6 months. EchoJobs helps you spend more time applying and less time hunting. 🎯
  • Check daily! We're always updating with new jobs. Set up job alerts for even quicker access. 📅

What Fellow Engineers Say