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Senior Machine Learning Engineer

Roles & Responsibilities

  • 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).

Requirements:

  • 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.
  • Establishing monitoring, logging, and retraining workflows to continuously validate and improve models.

Job description

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.

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