Senior AI Machine Learning Engineer for High-Volume Prompt Workflow Setup

Keystone Digital

Contract · Remote · Flexible hours

About the role

Keystone Digital is scaling its B2B analytics platform and needs an AI Machine Learning Engineer to lead multi‑tenant feature delivery. You will design and ship reusable ML components that serve multiple customers while maintaining data isolation and performance.

Key responsibilities

• Architect the "TenantLens" ML module using TensorFlow and PyTorch to support per‑tenant model training pipelines.
• Implement data preprocessing pipelines in Apache Spark that partition raw logs by tenant ID.
• Deploy containerized inference services on Kubernetes with Helm charts, ensuring tenant‑specific resource quotas.
• Write CI/CD scripts in GitHub Actions to automate model versioning, testing, and rollout across 10+ tenant environments.
• Collaborate with product managers to define feature flags for gradual rollout of new predictive features.
• Monitor model drift and latency using Prometheus and Grafana dashboards, delivering weekly performance reports.

Must-have skills

• Advanced Python for data science, including NumPy, pandas, and scikit‑learn.
• Experience building and serving ML models with TensorFlow or PyTorch.
• Proficiency in container orchestration (Kubernetes, Docker) and Helm.
• Strong understanding of multi‑tenant architecture and data isolation strategies.
• Ability to write scalable Spark jobs and RESTful APIs for model inference.

Nice to have

• Familiarity with MLOps tools such as MLflow or Kubeflow.
• Background in NLP for text‑based analytics within B2B contexts.