Machine Learning Engineer, Speech LLM Training

About the role

This role is part of the Jobright TNT - the private hiring network connecting top talent with top AI startups like Perplexity, Mercor, Cresta, Suno and 150 more.

This is not a mass job posting. Only select, high-signal candidates are invited to Jobright TNT and recommended directly to hiring teams

Hiring Company: Plaud

One-liner: Plaud Inc. is a hardware and software company making AI-powered voice recorders for note-taking, with over 1M users globally.

Salary: $200K/yr - $540K/yr

Why Join Us:

Role Responsibilities

• Have a proven track record of building and training large-scale audio or speech models from the ground up, whether that involves unified SpeechLLMs, advanced ASR, expressive TTS, or generative audio architectures
• Love living at the intersection of research and engineering, eager to design novel sequence modeling architectures one day and debug distributed training clusters the next
• Are highly comfortable traversing the entire stack—from fundamental signal processing and raw acoustic representations to massive foundation model training and edge-device optimization
• Possess deep expertise in PyTorch or JAX, with battle scars from optimizing large-scale distributed training runs, managing GPU memory utilization, and resolving complex performance bottlenecks
• Thrive in a fast-paced, high-growth startup environment where you are expected to take extreme ownership of ambiguous problems and drive them directly into production
• Are obsessed with building AI systems that natively understand and generate speech, ultimately creating a hardware-software AI companion that amplifies human productivity

Qualitications

Required

• Have a proven track record of building and training large-scale audio or speech models from the ground up, whether that involves unified SpeechLLMs, advanced ASR, expressive TTS, or generative audio architectures
• Love living at the intersection of research and engineering, eager to design novel sequence modeling architectures one day and debug distributed training clusters the next
• Are highly comfortable traversing the entire stack—from fundamental signal processing and raw acoustic representations to massive foundation model training and edge-device optimization
• Possess deep expertise in PyTorch or JAX, with battle scars from optimizing large-scale distributed training runs, managing GPU memory utilization, and resolving complex performance bottlenecks
• Thrive in a fast-paced, high-growth startup environment where you are expected to take extreme ownership of ambiguous problems and drive them directly into production
• Are obsessed with building AI systems that natively understand and generate speech, ultimately creating a hardware-software AI companion that amplifies human productivity

Preferred

• Text-based LLMs: Hands-on experience with core text-based Large Language Model pretraining, instruction tuning, or RLHF
• Neural Audio Codecs: Hands-on experience designing and training state-of-the-art neural audio codecs for streamable, high-fidelity audio
• Generative Architectures: Designing and training diffusion models, flow matching, or autoregressive architectures specifically for speech and voice generation
• Alignment & Steerability: Applying Reinforcement Learning (RL) techniques (like RLHF or GRPO) to improve conversational cadence, steerability, and alignment in foundation models
• Deep System Optimization: End-to-end inference and performance optimization, leveraging high-throughput serving frameworks (e.g., vLLM, TensorRT-LLM, SGLang) to minimize latency for real-time cloud streaming
• Large-Scale Infrastructure: Managing massive GPU clusters, utilizing advanced distributed training frameworks (e.g., FSDP, DeepSpeed), and navigating orchestration tools like Kubernetes

How can I join Jobright TNT:

If this is your first time applying to a Jobright TNT role, the process works as follows:

• Apply to your first Jobright TNT role
• We review your background to determine if you meet the TNT quality bar
• If qualified, your application is directly recommended to the employer
• Once accepted into TNT, you may be:
• Invited to apply for other exclusive TNT-only roles
• Invited to private, invite-only hiring events with top startups

You will be notified of your TNT selection result.

PS: All Jobright TNT roles are 100% real, directly hired by top AI startups we partner with, and come with priority review and higher response rates than the normal application queue.