This role requires candidates who are currently authorized to work in the U.S. without sponsorship, and C2C arrangements are not accepted.

About the RoleWe’re looking for a Staff Machine Learning Engineer to serve as a senior technical leader on a growing AI team. In this collaborative and high-impact role, you’ll design and deploy ML systems that support scalable solutions in domains such as natural language processing, intelligent matching, and conversational AI powered by large language models.

You’ll work across the full ML lifecycle — from ideation and prototyping to production deployment and monitoring. You’ll also collaborate closely with backend engineering teams (primarily Python/Django) to integrate intelligent features into a unified platform.

This position is ideal for someone with deep ML expertise who thrives in fast-paced, mission-driven environments.

Key Responsibilities

• Design, develop, and deploy production-grade ML systems for tasks such as coordination, triage, recommendation, and automation

• Build and fine-tune models for natural language understanding, search and ranking, classification, and routing

• Work with both unstructured text and structured data, including LLMs and embedding-based retrieval methods

• Collaborate with backend engineers to integrate ML models into a Python/Django-based infrastructure

• Improve experimentation and evaluation frameworks to maintain scientific rigor in deployments

• Stay current with advances in machine learning and NLP (e.g., foundation models, fine-tuning techniques, distillation) and apply them to real-world applications

• Help define the future of ML architecture and practices in close partnership with technical leadership

Required Skills & Experience

• 7+ years of experience applying ML in production environments

• Strong software engineering background, especially in Python; experience with Django is a plus

• Hands-on experience with NLP tools and techniques (e.g., transformers, embeddings, classification, semantic search)

• Proficient with ML libraries and frameworks such as scikit-learn, XGBoost, PyTorch, TensorFlow, and Hugging Face

• Demonstrated experience deploying models, managing pipelines, monitoring, and handling the full model lifecycle

• Solid understanding of ML fundamentals and best practices (bias/variance tradeoff, overfitting, model explainability)

• Excellent communication skills and ability to collaborate across multidisciplinary teams

Preferred Qualifications

• Experience fine-tuning LLMs or building retrieval-augmented generation (RAG) systems

• Background in search ranking or recommender systems

• Familiarity with real-time inference, voice AI, or multi-agent systems

• Experience with MLOps tooling (e.g., MLflow, Airflow, Docker) and cloud platforms (AWS preferred)

• Exposure to regulated environments such as healthcare or insurance

Why Join

• Work on meaningful ML and NLP problems with real-world impact

• Contribute to projects that touch millions of users

• Collaborate closely with AI leadership in shaping long-term strategy and innovation

• Competitive compensation and a high-impact role in a fast-moving, purpose-driven organization