Sanas

Company

Principal ML Engineer

Palo Alto

Job Description

Sanas is revolutionizing the way we communicate with the world’s first real-time algorithm, designed to modulate accents, eliminate background noises, and magnify speech clarity. Pioneered by seasoned startup founders with a proven track record of creating and steering multiple unicorn companies, our groundbreaking GDP-shifting technology sets a gold standard.

Sanas is a 200-strong team, established in 2020. In this short span, we’ve successfully secured over $100 million in funding. Our innovation have been supported by the industry’s leading investors, including Insight Partners, Google Ventures, Quadrille Capital, General Catalyst, Quiet Capital, and other influential investors. Our reputation is further solidified by collaborations with numerous Fortune 100 companies. With Sanas, you’re not just adopting a product; you’re investing in the future of communication.

Weʼre looking for an experienced and forward-thinking Principal Machine Learning Engineer to lead the design and implementation of our end-to-end Machine Learning infrastructure for industry leading Voice AI products. This is a high impact role where you will shape the technical vision, own strategic architecture decisions, and mentor a growing team of Machine Learning engineers focused on delivering reliable and scalable Machine Learning training and inference systems.

Youʼll work cross-functionally with AI research scientists, Infrastructure and product teams to ensure that Machine Learning infrastructure is designed and built for accelerating innovation through increased experimentation and deployment velocity. Youʼll help push the boundaries of real-time Voice AI

Weʼre looking for an experienced and forward-thinking Principal Machine Learning Engineer to lead the design and implementation of our end-to-end Machine Learning infrastructure for industry leading Voice AI products. This is a high impact role where you will shape the technical vision, own strategic architecture decisions, and mentor a growing team of Machine Learning engineers focused on delivering reliable and scalable Machine Learning training and inference systems.

Youʼll work cross-functionally with AI research scientists, Infrastructure and product teams to ensure that Machine Learning infrastructure is designed and built for accelerating innovation through increased experimentation and deployment velocity. Youʼll help push the boundaries of real-time Voice AI

Key Responsibilities

Architect robust, modular ML pipelines for model experimentation, feature extraction, and production inference

Collaborate with data engineering to improve audio dataset quality, labeling pipelines, and feature engineering

Mentor and collaborate with other ML engineers and research scientists to ensure best practices in model development, evaluation, and deployment.

Optimize models for latency, memory, and real-time performance on CPU/GPU/edge hardware.

Introduce frameworks for continual learning, model versioning, and A/B testing in production.

Stay current with advancements in Voice AI, Deep learning and multimodal model architectures

Qualifications:

10+ years of experience in Machine Learning Systems, ML workflows with atleast 3+ years in a technical leadership capacity

Advanced proficiency in Python and ML frameworks like PyTorch, TensorFlow, or JAX

Strong understanding of Deep learning architectures like RNNs, LSTMs, CNNs,Transformers, CTC and their application in Accent translation, Noise cancellation, Acoustic Modeling, Language Modeling and Language Translation

Experience deploying ML models to production (e.g., via ONNX, TensorRT, TorchScript, or custom inference stacks)

Nice to Have:

Familiarity with audio data and its unique challenges, like large file sizes, time- series features, metadata handling, is a strong plus.

Experience with Voice AI models like ASR, TTS and speaker verification.

Familiarity with real-time data processing frameworks like Kafka, Flink, Druid and Pinot

Familiarity with ML workflows including: MLOps, feature engineering, model training and inference.

Experience with labeling tools, audio annotation platforms, or human-in-the- loop annotation pipelines.

Experience at a high-growth startup or tech company operating at scale.

Deep experience with ML tooling for training and serving models, ideally in audio or speech domains (e.g., PyTorch, ONNX, Hugging Face Transformers, torchaudio).

Experience deploying real-time ASR, TTS, or voice synthesis models in production.

Background in DSP, audio augmentation, or working with noisy or multilingual datasets.

Joining us means contributing to the world’s first real-time speech understanding platform revolutionizing Contact Centers and Enterprises alike.

Our technology empowers agents, transforms customer experiences, and drives measurable growth. But this is just the beginning. You'll be part of a team exploring the vast potential of an increasingly sonic future

Sanas is revolutionizing the way we communicate with the world’s first real-time algorithm, designed to modulate accents, eliminate background noises, and magnify speech clarity. Pioneered by seasoned startup founders with a proven track record of creating and steering multiple unicorn companies, our groundbreaking GDP-shifting technology sets a gold standard.

Sanas is a 200-strong team, established in 2020. In this short span, we’ve successfully secured over $100 million in funding. Our innovation have been supported by the industry’s leading investors, including Insight Partners, Google Ventures, Quadrille Capital, General Catalyst, Quiet Capital, and other influential investors. Our reputation is further solidified by collaborations with numerous Fortune 100 companies. With Sanas, you’re not just adopting a product; you’re investing in the future of communication.

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Principal ML Engineer

Job Description

Key Responsibilities

Qualifications:

Nice to Have:

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