SENIOR MACHINE LEARNING ENGINEER

You will be joining the team that designs, builds, and scales machine learning systems powering personalisation and customer engagement at a large scale. This is an opportunity to work on production-ready ML pipelines, real-time decision-making systems, and experimentation frameworks that directly impact millions of users. Your responsibilities will include : • Developing pipelines that transform behavioral, demographic, and contextual data into real-time features. • Designing APIs and services for low-latency prediction and decision-making. • Implementing frameworks for A/B testing, exploration/exploitation strategies, and model evaluation. • Working closely with product and engineering teams to balance engagement, business value, and compliance. • Establishing monitoring, logging, and retraining workflows to continuously validate and improve models. What we expect from you: • 5+ years of applied ML engineering experience (recommendation systems, personalization, ranking, or ads). • Strong background in Python and/or Go, SQL, and ML frameworks such as TensorFlow or PyTorch. • Experience deploying real-time ML systems (low-latency serving, feature stores, event-driven architectures). • Familiarity with cloud ML platforms (Vertex AI, SageMaker, or similar). • Experience with data warehouses (BigQuery, Snowflake, Redshift). • Understanding of multi-objective optimisation and trade-offs in personalisation. • Ability to thrive in a fast-paced, startup-style environment Will be a plus: • Experience in martech, adtech, CRM, or large-scale consumer personalisation. • Exposure to bandit algorithms or reinforcement learning. • Prior work on systems serving millions of users at scale. • Experience with Google Cloud Platform (GCP). Soft Skills: • Fluent English and strong communication skills. • Proactive and positive attitude. • Ability to work 9am- 4pm EST. We offer: • Opportunities to shape large-scale personalisation technology. • Salary range: 6000 USD • Competitive compensation package that matches your skills and experience. • Professional growth, conferences, and skill development budget. • Flexible remote work with support for your productivity. • Collaborative and innovative environment where impact is valued over years of experience. • Online&Offline activities Our Recruitment Process • CV Screening: Applications are reviewed within 24 hours. • Pre-Screening Interview: A short, structured AI-assisted Q&A session to assess experience and role suitability. • Shortlisting: Qualified candidates are presented to the hiring manager for review. • Formal Interviews: Online discussions with the hiring manager or project team, with feedback provided within 1-2 weeks. • Offer and Onboarding: Successful candidates receive a formal offer and begin a structured onboarding process. Information about the processing of your personal data is provided in our Privacy Policy, which is available online at Privacy Policy.