Machine Learning Engineer

Koda Staff; San Francisco (CA); On-site; USD 125,000 - 175,000; Full time

Job summary

A leading AI startup in San Francisco is seeking a Machine Learning Engineer specializing in speech and audio technology. This full-time position revolves around designing advanced models, optimizing audio data pipelines, and collaborating with product and research teams. Candidates should have 2-6 years of relevant experience and a solid understanding of deep learning frameworks. Competitive salary ranges from $125,000 to $175,000, reflecting the demand for expertise in this innovative field.

Qualifications

• 2–6 years of experience in machine learning, focusing on speech/audio.
• Strong background in deep learning with PyTorch or TensorFlow.
• Hands-on with tools like Hugging Face Transformers and FFmpeg.

Responsibilities

• Design, train, and optimize ML models for speech recognition and audio classification.
• Collaborate with teams to implement state-of-the-art models in production.
• Analyze and clean large-scale voice datasets.

Skills

Machine Learning

Deep Learning

Speech Recognition

Audio Classification

Digital Signal Processing

Education

BS or MS in Computer Science

Tools

PyTorch

TensorFlow

Hugging Face Transformers

FFmpeg

NumPy

SciPy

Job description

Direct message the job poster from Koda Staff

Connecting Top AI Engineering / Research Talent with Leading Companies Across the U.S.

Machine Learning Engineer – Speech & Audio AI

Employment Type: Full-time

Experience Level: Mid to Senior

Are you passionate about shaping the future of voice and sound technology? Join a cutting-edge AI startup in San Francisco that’s building the next generation of speech and audio intelligence products.

We're looking for a Machine Learning Engineer who enjoys solving complex problems and working across multiple areas of AI and data-driven technology in a dynamic environment.

What You’ll Do

• Design, train, and optimize ML models for speech recognition, audio classification, speaker diarization, or text-to-speech (TTS).
• Collaborate with product and research teams to bring state-of-the-art models into production.
• Develop scalable pipelines for model training, evaluation, and deployment.
• Apply techniques like self-supervised learning, transformers, or diffusion models to real-world audio data.
• Analyze and clean large-scale voice datasets (structured and unstructured).
• Monitor and improve inference performance in real-time audio systems.

What We’re Looking For

• 2–6 years of experience in machine learning, with a focus on speech/audio.
• Strong background in deep learning (PyTorch or TensorFlow).

Hands-on experience with tools and frameworks such as:

• Hugging Face Transformers
• Voice conversion frameworks (e.g., RVC, DiffVC, YourTTS)
• Self-supervised learning tools like S3PRL
• Solid understanding of digital signal processing and acoustic modeling, with experience in: FFmpeg, SoX, NumPy/SciPy, Praat
• Experience deploying ML models in cloud environments (AWS, GCP, or Azure).
• BS or MS in CS, EE, ML, or related field (or equivalent industry experience).

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Industries

  Staffing and Recruiting

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