ML/AI Engineer

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.