Senior Machine Learning Engineer

About the Role

We’re looking for a Senior Machine Learning Engineer to join the team that designs, builds, and scales ML systems powering personalization and customer engagement at a massive scale.
You’ll work on production-ready ML pipelines, real-time decision-making systems, and experimentation frameworks that directly impact millions of users worldwide.
 

What You’ll Do

• Develop pipelines that transform behavioral, demographic, and contextual data into real-time features.
• Design APIs and services for low-latency prediction and decision-making.
• Implement frameworks for A/B testing, bandit algorithms, and model evaluation.
• Collaborate with product and engineering teams to balance engagement, business value, and compliance.
• Build monitoring, logging, and retraining workflows to continuously validate and improve models.

What We Expect

• 5+ years of experience in applied ML engineering (recommendation systems, personalization, ranking, or ads).
• Strong knowledge of Python and/or Go, SQL, and ML frameworks such as TensorFlow or PyTorch.
• Hands-on 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).
• Solid understanding of multi-objective optimization and personalization trade-offs.
• Ability to thrive in a fast-paced, startup-style environment.

➕ Nice to Have

• Experience in martech, adtech, CRM, or large-scale consumer personalization.
• Exposure to bandit algorithms or reinforcement learning.
• Previous work on systems serving millions of users.
• Experience with Google Cloud Platform (GCP).

We Offer

• Opportunity to shape large-scale personalization technology.
• Competitive compensation matching your skills and experience.
• Professional growth budget for conferences and training.
• Fully remote and flexible work setup.
• Collaborative and innovative team culture focused on impact.
• Online & offline team activities.

Schedule: 9am–4pm EST
Format: Full-time / Remote / Worldwide
 

🚀 Join us to build personalization systems that reach millions!
Send your resume or Djinni profile — we’d love to meet you.