Senior Machine Learning Engineer

We’re an early-stage startup building next-generation personalization technology for digital marketing. Our mission is to help brands deliver smarter, more relevant customer experiences using data and machine learning.

🤓 As a Senior Machine Learning Engineer, the company expects you to perform the following tasks

• Build and productionize ML models for ranking, personalization, and customer engagement.
• Develop pipelines that turn behavioral, demographic, and contextual signals into online/offline features.
• Design and deploy low-latency APIs and decision services for decision making.
• Implement experimentation frameworks, including A/B testing and exploration exploitation strategies.
• Operationalize the ML lifecycle: automated training, CI/CD for models, artifact and feature versioning, online/offline parity.
• Build observability into ML systems: monitor data quality, model drift, and decision outcomes; trigger retraining where needed.
• Establish closed feedback loops that connect decisions to outcomes (conversions, engagement, fatigue signals like unsubscribes).
• Collaborate with product and engineering to balance personalization, compliance, and business value in real-world systems

✨ You are the person they are looking for if you have...

• 5+ years experience in applied ML engineering (recommendation systems, personalization, ranking, or ads).
• Strong background in Python/Go, SQL, and modern ML frameworks (TensorFlow, PyTorch, or similar).
• Strong grasp of MLOps practices: CI/CD for ML, containerization (Docker), orchestration (Kubernetes, Airflow/Kubeflow), model registries, monitoring frameworks.
• Familiarity with cloud ML platforms (Vertex AI, SageMaker, or similar) and data warehouses (BigQuery, Snowflake, Redshift).
• Experience deploying real-time ML systems (low-latency serving, feature stores, event-driven architectures).
• Understanding of multi-objective optimization and trade-offs in personalization.
• Comfortable working cross-functionally in a startup environment.
• Strong spoken and written communication skills in English.

💜 They will be even more excited if you...

• Experience in martech, adtech, CRM, or large-scale personalization platforms.
• Exposure to bandit algorithms, reinforcement learning, or causal inference for adaptive decision-making.
• Prior work on systems serving millions of users at scale.
• Experience with Google Cloud Platform.
• Experience with observability tools (Prometheus, Grafana, Evidently, WhyLabs, Great Expectations) for monitoring data and model health.