Principal ML Engineer

Annual releases gave way to two-week sprints years ago, and the platform now handles over 200 million API calls a day. We run one of the larger SaaS platforms for commercial insurance carriers, processing millions of policy transactions a year. Most engineers work remotely and come into the office one week a quarter for planning.

Role overview

This role opened up after a team member moved internally. The Personalization team trains and serves models that run on every customer request. We need someone who cares about latency as much as accuracy. Our team is spread across 8 countries. Headquarters is in Waltham. You will join as an independent contractor on a long-term agreement. Payment is monthly in USD. You will need at least 4 hours of overlap with US Eastern time. Please make sure you have a quiet place to work and a solid internet connection.

Duties

• Orchestrate pipelines with Kubeflow, SageMaker Pipelines, Vertex AI or Airflow
• Handle on-call for the ML services the team owns
• Fine-tune open-weight models with LoRA when it beats prompting
• Monitor models for drift, data quality issues and latency regressions
• Cut inference cost with quantization, batching and caching
• Track experiments, artifacts and versions in MLflow or Weights & Biases

Required qualifications

• 8-10 years of software engineering experience, with at least two spent on ML systems in production
• Experience deploying models as services and monitoring them
• Knowledge of LLM APIs, prompt design and evaluation methods
• Familiarity with Docker, Kubernetes and a cloud ML platform (SageMaker, Vertex AI, Azure ML)

Nice to have

• Computer vision background (OpenCV, detection, segmentation)
• Recommendation or ranking systems at scale

Compensation and benefits

• Monthly internet allowance
• Monthly payments via wire transfer or Wise

Duration: 9 months. Start: Immediately.

Demo job created on 11jobs for testing and demonstrations. It is not an actual opening at Torres Labs.