Engineering Manager, Machine Learning
RunwayFull Time
Junior (1 to 2 years), Senior (5 to 8 years)
Candidates should possess 6-10 years of experience in back-end or full-stack engineering, with at least one Gen-AI product or workflow in production, demonstrating proficiency in Java and fluency in Python or Node for ML tooling. They should have practical experience with large language models, embeddings, vector search, and retrieval-augmented generation, along with deep familiarity with AWS or GCP services, container orchestration, CI/CD, and monitoring.
The AI Engineering Manager will own the AI roadmap, translating business priorities into model, data, and infrastructure milestones; build data & ML infrastructure including a data lake, feature store, vector search, model registry, and CI/CD for ML; develop and deploy models by training or fine-tuning them on doola’s domain data and serving them behind low-latency APIs; ensure quality, cost, and compliance by setting up automated evaluation, token-spend monitoring, and GDPR-safe data flows; and provide leadership in code reviews, technical mentoring, and cross-functional communication.
Assists global entrepreneurs with U.S. business formation
Doola helps international entrepreneurs set up and manage their businesses in the United States. They provide services that simplify the process of incorporating a business, accessing U.S. payment systems, and ensuring compliance with legal requirements. Doola assists clients by obtaining necessary documents like the Employer Identification Number (EIN) and guiding them through state regulations. Unlike many competitors, Doola offers a free 10-minute consultation to attract clients and has a custom dashboard for easy access to important documents. Their goal is to make it easier for global entrepreneurs to navigate the complexities of starting a business in the U.S. and to support them as they grow.