Senior Machine Learning Engineer

Our client is one of the world’s leading hospitality companies, operating a global portfolio of iconic hotel brands and serving millions of guests each year. They are investing heavily in data science and machine learning to transform the guest experience, from real-time personalization on their consumer platform to intelligent automation across business operations.

This is a ground-floor opportunity to join a highly visible, growing ML Engineering team that sits at the intersection of data science and software engineering. You will work directly with senior data scientists and play a hands-on role in bringing machine learning models to life, end to end, at scale, in production.

What You’ll Do

• Design and implement end-to-end ML product architectures, from data ingestion and feature engineering through model serving and results activation.
• Partner closely with Data Scientists to translate prototype solutions into production-grade, scalable systems on AWS.
• Build and maintain real-time streaming and offline batch data pipelines that power algorithmic products.
• Implement solutions using infrastructure-as-code patterns with a focus on reliability, scale, and latency.
• Enhance the team’s Feature Store with impactful data, including cleansing and imputation logic.
• Collaborate cross-functionally with Data Engineering, Data Architecture, Security, and Governance teams.
• Stay ahead of the curve on ML engineering design patterns, emerging AWS services, and modern tooling.
• Serve as both solutions architect and hands-on implementation engineer. This is not a purely advisory role.

What We’re Looking For

The ideal candidate has a strong engineering foundation and the intellectual curiosity to adapt as the tech evolves. The team’s stack and models change frequently. They are looking for someone who can learn fast and apply first principles, not someone who only knows one specific toolchain.

Required

• 5 years of experience implementing software or ML product solutions in a cloud environment.
• Deep expertise in AWS cloud services for ML workloads.
• Strong proficiency in Python, SQL, PySpark, and Docker.
• Hands-on experience with both streaming and batch data architectures at scale.
• Solid understanding of machine learning concepts and model lifecycle management, framework-agnostic.
• Experience with DevOps, CI/CD, and Agile development practices.
• Excellent communication skills and a collaborative working style.

Preferred

• GCP experience alongside AWS.
• Familiarity with SageMaker or equivalent managed ML platforms.
• Background in companies with strong engineering cultures and complex, high-scale systems.
• Comfort operating with ambiguity and shifting priorities.

Education

• Master’s degree in Computer Science, Software Engineering, or a related field preferred.
• Bachelor’s degree with 4 to 5 years of strong, demonstrable experience equally considered.
• What matters most is your foundation, your thinking, and your track record of building things that work.

Why This Role

• High visibility. Your work directly impacts millions of guests and internal stakeholders.
• Collaborative, low-ego team that is serious about doing things the right way.
• Real problems, real scale. Not greenfield experiments that never ship.
• A culture that values intellectual curiosity and continuous learning over checkbox skills.
• 100% remote, U.S.-based candidates only.

MMD Services Inc. is an equal opportunity employer. All applicants are considered for all positions without regard to race, religion, color, sex, gender, sexual orientation, pregnancy, age, national origin, ancestry, physical/mental disability, medical condition, military/veteran status, genetic information, marital status, ethnicity, alienage or any other protected classification, in accordance with applicable federal, state, and local laws.