Senior Research Engineer at AssemblyAI

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Full Time

Start Date

Immediate

Expiry Date

26 Dec, 25

Salary

275000.0

Posted On

27 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Machine Learning, Deep Learning, C++, Rust, GPU Acceleration, CUDA, Profiling, Kernel-Level Optimization, Compiler Frameworks, Graph Optimizations, Parallelization Strategies, Debugging, Optimization, Communication, Collaboration

Industry

Software Development

Description

About AssemblyAI At AssemblyAI, we’re building at the forefront of Speech AI, creating powerful models for speech-to-text and speech understanding available through a straightforward API. With more than 200,000 developers building on our API and over 5,000 paying customers, AssemblyAI is helping unlock and support the next generation of powerful, meaningful products built with AI. Progress in AI is moving at an unprecedented pace– and our team is made up of experts in AI research that are focused on making sure that our customers are able to stay on the cutting edge, with production-ready AI models that are constantly updating and improving as our team continues to improve accuracy, latency, and what’s possible with Speech AI. Our models consistently rank highest in industry benchmarks for accuracy, outperforming models from Google and Amazon, and up to 30% fewer hallucinations than OpenAI’s Whisper. Our models power more than 2 billion end-user experiences each day, helping companies better understand customer feedback, run more productive meetings with automated meeting notes, and helping improve childhood literacy via ed tech tools. 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. We’re a remote team looking to build one of the next great AI companies, and are looking for driven, talented people to help us get there! About the Role We are seeking a highly skilled Senior Research Engineer to collaborate closely with both Research and Engineering teams. The role involves diagnosing and resolving bottlenecks across large-scale distributed training, data processing, and inference systems, while also driving optimizations for existing high-performance pipelines. The ideal candidate possesses a deep understanding of modern deep learning systems, combined with strong engineering expertise in areas such as layer-level optimization, large-scale distributed training, streaming, low-latency and asynchronous inference, inference compilers, and advanced parallelization techniques. This is a cross-functional role requiring strong technical rigor, attention to detail, intellectual curiosity, and excellent communication skills. The position is embedded within the Research team and is responsible for developing and refining the technical foundation that enables cutting-edge research and translates its outcomes into production, bridging research and production engineering. Responsibilities Investigate and mitigate performance bottlenecks in large-scale distributed training and inference systems. Develop and implement both low-level (operator/kernel) and high-level (system/architecture) optimization strategies. Translate research models and prototypes into highly optimized, production-ready inference systems. Explore and integrate inference compilers such as TensorRT, ONNX Runtime, AWS Neuron and Inferentia, or similar technologies. Design, test, and deploy scalable solutions for parallel and distributed workloads on heterogeneous hardware. Facilitate knowledge transfer and bidirectional support between Research and Engineering teams, ensuring alignment of priorities and solutions. Qualifications Strong expertise in the Python ecosystem and major ML frameworks (PyTorch, JAX). Experience with lower-level programming (C++ or Rust preferred). Deep understanding of GPU acceleration (CUDA, profiling, kernel-level optimization); TPU experience is a strong plus. Proven ability to accelerate deep learning workloads using compiler frameworks, graph optimizations, and parallelization strategies. Solid understanding of the deep learning lifecycle: model design, large-scale training, data processing pipelines, and inference deployment. Strong debugging, profiling, and optimization skills in large-scale distributed environments. Excellent communication and collaboration skills, with the ability to clearly prioritize and articulate impact-driven technical solutions. 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, benefit, and other reward opportunities we provide. There are many factors that go into salary determinations, including relevant experience, skill level, 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 or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range. 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 will be communicated to candidates throughout the interview process. Salary range: $240,000 - $275,000 Working at AssemblyAI We are a small but mighty group of startup veterans and experienced AI researchers with over 20 years of expertise in Machine Learning, Speech Recognition, and NLP. As a fully remote team, we’re looking for people to join our team who are ambitious, curious, and lead with integrity. We’re still in the early days of AI and of AssemblyAI’s journey, and are looking for teammates who won’t just fit in, but will help us define and build our company culture. We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. No matter your race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply! Using AI to Interview: If you’re selected for an interview, please review this resource to better understand how AssemblyAI approaches the use of AI in our interview process. Keep Exploring AssemblyAI: Check us out on YouTube! Learn more about AI models for speech recognition Core Transcription | Audio Intelligence | LeMUR | Try the Playground Our $50M Series C fundraise

Responsibilities

Investigate and mitigate performance bottlenecks in large-scale distributed training and inference systems. Develop and implement optimization strategies for production-ready inference systems.