Audio Inference Engineer, Model Efficiency

Role Overview:

Our team is a fast-growing group of committed researchers and engineers. The mission of the team is to build reliable machine learning systems and optimize audio inference serving efficiency using innovative techniques. As an engineer on this team, you will work on advancing core audio model serving metrics, including latency, throughput, and quality by diving deep into our systems, identifying bottlenecks, and delivering creative solutions for audio processing and streaming workloads.

You’ll collaborate closely with both the training and serving infrastructure teams to ensure seamless integration between model development and deployment, with a special focus on real-time and streaming audio inference.

Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, expertise, and time zones to promote collaboration and flexibility. You'll find the Model Efficiency team concentrated in the EST and PST time zones, these are our preferred locations.

Qualifications:

• Significant experience developing high-performance audio or machine learning inference systems.
• Proficiency with programming languages such as C++ and Python.
• Hands-on experience with deep learning models for audio, speech, or language applications.
• A bias for action and a strong results-oriented mindset.

It is a big plus if you also have considerable experience with:

• GPU programming, low-level system optimization, model parallelization techniques over multiple GPUs
• Have experience with duplex real-time streaming architectures.
• Internals of machine learning frameworks for audio (such as PyTorch, TensorFlow, or specialized audio libraries).
• Have experience with inference framework like vLLM, SGLang, Tensort-LLM, or custom distributed inference systems
• Sequence modeling (e.g., transformers for audio/speech) and end-to-end audio pipeline optimization

Working location:
This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role.

Full-Time Employees at Cohere enjoy these Perks:

• A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch.
• Full health and dental benefits, including a separate budget for mental health.
• RRSP matching, 401K, Pension Scheme.
• 100% Parental Leave top-up for up to 6 months, for either parent.
• Annual enrichment benefits:

• 6 weeks of paid vacation (30 working days!)
• Budget for traveling to other offices if you are remote, plus an annual company offsite.

How and Where We Work:

• Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon.
• For those in the office: a daily lunch program, plenty of snacks, and regular community and social events.
• For those not near an office: a co-working benefit so you can work alongside others in your city.
• Everyone receives a $500 home office stipend to set up your workspace properly.