About the role:

We're looking for a Senior Researcher to join our Research team. At AssemblyAI, our core competencies include creating best-in-class AI models and deploying them in production. The successful candidate will conduct applied research in Speech and Natural Language Processing (NLP) in a collaborative team environment. Key responsibilities include writing training code for large-scale models with billions of parameters, rigorously evaluating these models, conducting extensive experiments for identifying successful training recipes, and working closely with engineers for data creation, data filtering, and model deployment. 

The ideal candidate will have a strong background in research and engineering using deep learning and a passion for writing high-quality code. They should possess excellent problem-solving skills, a deep scientific acumen gained through years of hands-on deep learning experiences, and the ability to contribute to breakthrough research projects that meet evolving market demands.

What You’ll Do:

• Write training code for large-scale models and conduct experiments to develop state-of-the-art models for Speech AI tasks, including multi-modal LLMs, ASR, speaker recognition, and more.
• Stay current with the latest AI research and share relevant insights across the company.
• Collaborate with the technology leadership team to define the scope of research projects, prioritize and deprioritize tasks based on product roadmaps and timelines, and take ownership of their execution.
• Work closely with the engineering team to deploy new models into production and continuously improve them.
• Partner with the data infrastructure team to enhance data quality and optimize the data processing pipeline.
• Engage with research communities through activities such as publishing papers or participating in conferences.

What You’ll Need:

• 2+ years of professional hands-on experience in deep learning research & development. 
• Demonstrated experience in all aspects of deep learning model development, including data acquisition and processing, implementation, model training, experimental analysis, and writing inference and evaluation code as an individual contributor. 
• Experience with training production-grade, large Transformer models on distributed systems. 
• Strong Python programming skills. 
• Appetite for writing high-quality, well-designed, and extensible code.
• Strong technical and analytical skills for generating new ideas, implementing novel techniques, analyzing experimental results, identifying inefficiencies, and refining the ideas of others through discussion, identifying and addressing problems, as well as reviewing and improving the code of peers.
• Strong written and verbal communication skills for technical matters. 

Nice to Have:

• Hands-on experience with JAX/TPUs and distributed training. 
• Excellent knowledge of GPU and TPU hardware. 
• Expertise in writing high performance CPU/GPU/TPU code. 
• Track record of publications in deep learning or its applications at top-tier conferences. 

You may be a great fit if you are:

• Highly self-motivated and keen to have real-world impact. 
• Detail-oriented, analytical, and creative problem solver. 
• Meticulous in all aspects (code, data, modeling, ...). 
• Able to work effectively in a team-oriented, collaborative environment. 

Location Requirements:

At this time, we are only able to hire for this role in the USA, Canada, UK, Germany and Switzerland.

Pay Transparency:

AssemblyAI strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on paying competitively for our size, stage and industry, and are one part of many compensation, benefits and other reward opportunities we provide.

There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range.

Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates.

Salary range: $185K - $265K