Senior Research Engineer

About AssemblyAI

At AssemblyAI, we’re creating a leading Applied AI company by building powerful models to transcribe and understand audio data, exposed through a straightforward web API. 

Progress in AI is moving at an unprecedented pace–we keep our pulse on the latest developments and breakthroughs in AI research and use these advances to inform our production-ready AI models. Our Automatic Speech Recognition (ASR) models already outperform companies like Google, AWS, and Microsoft (see our research page linked below) - which is why hundreds of companies and thousands of developers are using our API to transcribe and understand millions of videos, podcasts, phone calls, and Zoom meetings every day.

We’ve raised funding by leading investors including Accel, Insight Partners, Y Combinator’s AI Fund, Patrick and John Collision, Nat Friedman, and Daniel Gross. As part of a huge and emerging market, AssemblyAI is well on its way to becoming the leader in applied AI.

Join our world-class, remote team and help us build an iconic AI company!

About the role:

We are looking for a Senior Research Engineer to join our Research team. The core competencies of AssemblyAI include building best-in-class AI models, writing optimized inference code, and creating infrastructure to support deep learning work. This role involves both research engineering and applied research in Speech and Natural Language Processing (NLP) within a collaborative team environment. Specific responsibilities include enabling cutting-edge performance of our training software stack on large TPU clusters, writing code for state-of-the-art model training, and optimizing code for both training and inference. The ideal candidate will have a strong background in research engineering, deep learning using JAX, and experience writing high-quality code. With a fine-grained understanding of deep learning fundamentals, training hardware, and distributed systems, this person will contribute to all research projects, alongside the specific ones assigned to them.

What You’ll Do:

• Train large-scale Speech AI models, including speech-focused multi-modal LLMs and ASR models with billions of parameters.

• Write and optimize training code for maximum efficiency and memory utilization.

• Stay up-to-date on the latest AI research and share insights across the company.

• Collaborate with the technology leadership team to prioritize the research and engineering agenda, define project scopes, and lead their execution.

What You’ll Need:

• 2+ years of professional experience in deep learning research & development. 

• Hands-on experience with JAX/TPUs and distributed training. 

• Excellent knowledge of GPU and TPU hardware. 

• Strong Python programming skills. 

• Expertise in deep learning architectures and techniques such as CNNs, Transformers, SSMs, self-supervised learning, etc. 

• Experience with training large Transformer models on distributed systems. 

• Strong written and verbal communication skills for technical matters. 

 

Nice to Have:

• Experience in training/fine-tuning (multimodal) Large Language Models. 

• Experience in LLM inference using frameworks like vLLM or JetStream. 

 

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 - $260K