machine learning engineer

Verbit.ai provides AI-driven solutions that help organizations extract value from audio and video content. The company offers a verbal-intelligence platform that integrates LLMs, GenAI, and speech AI to power automation, real-time insights, and intelligent workflows for the legal, media, and education sectors.

• Build, deploy, and serve ML models in production;
• Optimize inference performance, latency, and GPU utilization;
• Support and extend speech solutions, including 3rd-party ASR integrations and self-hosted models;
• Evaluate and optimize key ASR/ML metrics such as WER, latency, F1 score, EER, and DER;
• Integrate LLMs and agentic flows into production solutions;
• Fine-tune existing models.

• 4+ Years of experience in machine/deep learning;
• Strong Python skills and experience in Linux environments;
• Familiarity with deep learning libraries like PyTorch or TensorFlow and training workflows;
• Experience with MLOps pipelines and model deployment in production;
• Experience optimizing models for inference, including GPU acceleration;
• Experience with Docker, gRPC, and serverless/micro-services architectures on cloud infrastructure (AWS/GCP/Azure);
• Experience with real-time/streaming systems and low-latency processing;
• Nice to have: Experience building and productizing agentic flows and AI-driven solutions (1+ year), familiarity with LLM/agent orchestration frameworks (e.g., CrewAI, AWS Bedrock, Temporal, AgentCore, LiteLLM), prior ASR/speech experience.

• No conditions specified