ML Engineer – Signal Processing, ASR

This is a fully remote position, open to applicants in India.

📋 Description

• Design, develop, and enhance ASR, audio, and speech-related machine learning systems for production environments.

• Create signal processing pipelines tailored for noisy, compressed, telephony-style, or real-world audio scenarios.

• Train, fine-tune, assess, and deploy models for ASR, audio classification, diarization, redaction, or other related tasks.

• Manage machine learning workflows comprehensively: data preparation, model training, validation, inference, monitoring, and iteration.

• Optimize inference processes to balance latency, throughput, cost, and reliability effectively.

• Troubleshoot model quality issues by conducting data analysis, focused evaluations, and production monitoring.

• Partner with product and engineering teams to transform business challenges into actionable machine learning solutions.

⛳️ Requirements

• A minimum of 5 years of hands-on experience in deploying ASR or other machine learning systems in production settings.

• A robust background in signal processing, speech recognition, audio machine learning, or telephony/audio pipelines.

• Experience with production ASR systems, streaming inference, voice activity detection, noise management, diarization, speaker/channel issues, or comparable speech technologies.

• Proficient Python engineering skills with a track record of building production services.

• Familiarity with frameworks such as PyTorch, TensorFlow, JAX, ONNX Runtime, or similar technologies.

• Experience in deploying models using Docker, Kubernetes, FastAPI, Triton, vLLM, TorchServe, custom inference services, or cloud-based machine learning platforms.

• A solid understanding of model evaluation, regression testing, observability, latency, memory, GPU/CPU utilization, and cost-performance trade-offs.

• Ability to work effectively with messy real-world data, noisy labels, domain drift, and ambiguous production challenges.

🏝️ Benefits

• Medical insurance

• Professional development opportunities

• Flexible work hours

• Remote work options