We are seeking a skilled ML/AI Engineer to join our team and deliver cutting-edge ML/AI models in the ASR domain and legal insights more broadly. The core of this role is building, deploying, and serving ML models in production.
A key part of this role is speech engineering — prior ASR/speech experience is not a must, but a willingness to learn and grow into this domain is essential. Experience with LLM-based solutions and agentic flows is an advantage, not a requirement.
What you’ll do: * Build, deploy, and serve ML models in production — the core of the role — optimizing inference performance, latency, and efficient GPU utilization. * Support and extend our speech solutions, including 3rd-party ASR integrations and self-hosted ML models. * Evaluate and optimize key ASR/ML metrics such as WER, latency, F1 score, EER, and DER. * Secondary: Integrate LLMs and agentic flows into production solutions where they add value, including fine-tuning existing models.
What you’ll bring:
Core (required): * Solid background in machine/deep learning, with 4+ years of experience. * Strong Python skills and experience working in Linux environments. * Familiarity with deep learning libraries (e.g., PyTorch, TensorFlow) and training workflows. * Experience with MLOps pipelines and serving/deploying models 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 (e.g. streaming pipelines, live sessions).
Nice to have (secondary / optional): * Experience building and productizing agentic flows and AI-driven solutions (1+ year). * Familiarity with LLM / agent orchestration frameworks such as CrewAI, AWS Bedrock, Temporal, AgentCore, or LiteLLM. * Prior ASR / speech experience — not required; willingness to learn this domain is what matters most.
