Machine Learning Engineer

Company Description

Dream Opportunity is a global organization focused on expanding access to high-income career pathways for under-resourced students.

We partner with multi-billion-dollar companies, including JPMorgan Chase, AT&T, EY, Blackstone, Paramount, Informa, Kelloggs, Kellanova, and others to provide students with real exposure to careers and professional networks.

Building on this foundation, we are launching Dreamari, a global AI-powered, gamified ed-tech platform designed to help students discover careers, build skills, and unlock opportunity at scale.

Dreamari will launch with immediate distribution across eight countries: the United States, the United Kingdom, Canada, India, the Philippines, Mexico, Singapore, and the UAE.

We are forming the first selected core technical team to build this platform from the ground up. These roles will influence product architecture, user experience, global scalability, and long-term technical direction.

Role Overview

As a Machine Learning Engineer, you will build and scale the intelligence layer of the platform. You will design and deploy the recommendation, personalization, and inference systems that power tailored guidance for students globally.

This is a founding engineering role with direct influence on model architecture, production deployment, and long-term system scalability.

What Youll Do

• Design, train, and deploy production-grade machine learning models
• Build and iterate on recommendation and personalization systems
• Implement real-time inference pipelines across global user bases
• Optimize models for latency, reliability, and cloud efficiency
• Integrate embeddings, LLM APIs, and vector search systems where appropriate
• Monitor, evaluate, and continuously improve deployed models in production
• Ensure responsible, ethical, and transparent AI system design

Required Skills & Experience

• 5+ years of professional experience in machine learning or ML engineering roles
• Strong proficiency in Python
• Experience with PyTorch, TensorFlow, or comparable ML frameworks
• Demonstrated experience deploying production ML systems
• Experience with real-time inference systems
• Familiarity with embeddings, LLM APIs, and vector databases
• Experience deploying ML systems on cloud platforms (GCP, Vertex AI, or equivalent)
• Strong communication skills and ability to collaborate in a fast-moving startup environment

Nice to Have

• Experience building large-scale recommendation systems
• Experience optimizing ML systems for high concurrency and low latency
• Background in applied NLP or conversational AI

Compensation & Benefits

Compensation: 4548 LPA (approximately $51,000 USD annually)

Equity: Meaningful equity participation as an early founding engineer

Role Type: Full-time, founding technical role

Ownership: High autonomy and real influence over technical decisions

Growth: Opportunity to build a global AI system used across multiple countries from day one