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Pear VC

Founding ML Engineer - Outspeed

Reposted Yesterday
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In-Office
7 Locations
Expert/Leader
In-Office
7 Locations
Expert/Leader
As a Founding ML Engineer, you will build and optimize GPU infrastructure for real-time AI, focusing on model inference, architecture, and customer engagement.
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About Us

Outspeed is creating the most lifelike conversational voice systems to augment human-computer interaction. We are building the infrastructure and tools to unlock applications in therapy, coaching, companionship and gaming.

Outspeed is led by an experienced team of researchers and engineers with collective experience from MIT, Google, and Microsoft. Our team is based in San Francisco and values empathy, deep technical knowledge, and autonomy. 

Janak earned his bachelor's and master's degrees from MIT and built grid-scale AI algorithms and infra at Autogrid (acq. Schneider). Sahil is a published researcher who led AI infra efforts at Google and Microsoft.
Role Description
As a Founding Engineer, you will play a pivotal role in shaping the company's technical direction.

You will get to build and scale our GPU infrastructure for realtime AI performance, optimizing inference engines for lowest latencies, distributed inference and finetuning voice models. You will also engage directly with our customers, and contribute heavily to the architectural roadmap. Your technical leadership will be instrumental in supporting and growing our engineering and product teams.

This role requires a proactive individual comfortable working in a fast-paced environment with frequently shifting priorities.

Benefits

  • Competitive salary + Equity

  • Health, dental, and vision insurance.

  • Bonuses based on performance

  • We are a company founded by immigrants, and we are committed to providing support to immigrant workers throughout their journey.

Requirements

  • Experience in end-to-end ML application development, including data engineering, model tuning, and model serving

  • Experience contributing to the architecture and design of resilient, large scale distributed ML systems

  • Strong understanding of ML development technologies such as Pytorch, Transformers, CUDA etc.

  • Strong understanding of ML inference technologies such as vLLM, sglang, llama.cpp etc.

Nice-to-haves

  • Strong understanding of IaC technologies like Docker, Kubernetes, Nomad, Terraform and Firecracker

  • Strong understanding of public cloud features (e.g. SDN, block storage, distributed file systems, identity management)

  • Enjoy moving fast and making a large business impact

Top Skills

Cuda
Docker
Firecracker
Kubernetes
Llama.Cpp
Nomad
PyTorch
Sglang
Terraform
Transformers
Vllm

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