Senior Machine Learning Engineer

Key Responsibilities
Design, build, and deploy scalable machine learning and generative AI solutions for legal technology products.
Develop and optimize NLP, LLM, and Retrieval-Augmented Generation (RAG) applications for production environments.
Engineer agentic AI workflows and multi-step reasoning systems to automate complex legal processes.
Implement and improve retrieval systems, including vector databases, semantic search, lexical search, and hybrid search architectures.
Build and maintain ML pipelines, APIs, model serving infrastructure, and cloud-based AI platforms.
Establish MLOps best practices for model deployment, monitoring, observability, versioning, and lifecycle management.
Evaluate and optimize model performance, latency, scalability, and cost efficiency across AI applications.
Partner with product managers, legal subject matter experts, data scientists, and software engineers to deliver business-focused AI solutions.
Troubleshoot production ML systems, identify performance bottlenecks, and implement continuous improvements.
Provide technical leadership and mentorship on machine learning engineering, LLM architecture, and AI platform best practices.

Required Qualifications
7+ years of experience
Bachelors Degree

Skills
Machine Learning Engineering
Generative AI Solutions
Python Programming
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG) Systems
Natural Language Processing (NLP)
Agentic AI Workflows
Retrieval Systems
ML Pipelines
Cloud-based AI Platforms
Unstructured Data Processing
Prompt Engineering
Technical Leadership
Cross-functional Collaboration
MLOps Best Practices
Production System Troubleshooting
Product Development Lifecycle

Schedule
Start date: 2026-08-27