Senior Machine Learning AI Engineer / Fully Remote / PyTorch

Job Description
This is a full-time position based in Los Angeles, with flexibility for hybrid or fully remote work for the right candidate. You'll be joining a stealth-mode startup focused on building next-generation AI infrastructure for the connected home. The team is reinventing how hardware, software, and machine learning interact at the operating system level-enabling real-time intelligence through multimodal inputs such as voice, video, and contextual data.
Work alongside a world-class group of engineers, scientists, and designers to reshape how humans interact with their environments. This role is ideal for someone with expertise in audio machine learning or intent recognition who's excited to contribute to a consumer-facing product that makes AI genuinely helpful in everyday life. You'll have a high level of ownership, hands-on access to advanced ML models, and the opportunity to shape foundational tech that delivers real-time responsiveness.

Required Skills & Experience

• 4+ years of applied machine learning experience with a focus on audio, speech, or intent modeling
• Strong background in training and deploying sequence models (e.g., RNNs, Transformers, Whisper, BERT, CLIP, Wav2Vec)
• Experience working on ML applications using speech/audio input, embedded systems, or multimodal signals
• Proven ability to build and train models from the ground up, not just utilize prebuilt APIs
• Proficiency with core ML tools such as PyTorch, TensorFlow, Hugging Face, torchaudio, librosa, OpenCV

Desired Skills & Experience

• Experience with signal processing, VAD, speaker identification, and audio embeddings
• Familiarity with model evaluation, inference latency, data augmentation, and model tuning
• Exposure to video-based sequence modeling, context recognition, or action detection
• Background in organizations like OpenAI, DeepMind, Amazon Alexa, Dolby, Sonos, Roku, AssemblyAI, etc.
• Bonus: Experience with ONNX, ffmpeg, NVIDIA Triton, or model optimization for edge devices

What You Will Be Doing
Tech Breakdown

• Applied ML in audio and signal processing
• Developing systems for intent recognition and sequence classification
• Research and development in multimodal fusion (e.g., integrating audio + video inputs)
• System-level optimization and real-time integration

Daily Responsibilities

• 80% hands-on model building, training, and iteration
• 20% collaboration across engineering, design, and architecture teams to drive innovation

The Offer

• Equity eligibility included

Benefits Include:

• Medical, Dental, and Vision Insurance
• Paid Vacation and Holidays
• Generous Equity Package

Applicants must be currently authorized to work in the U.S. on a full-time basis, now and in the future.