Senior AI / Machine Learning Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design and implement production-quality machine learning models for identity resolution, propensity scoring, deliverability, and personalization.

• Construct and sustain feature pipelines across both batch and real-time systems.

• Create and enhance classification models adept at managing class imbalance and noisy labels.

• Connect machine learning models directly with graph databases to facilitate real-time inference and identity scoring.

• Manage model lifecycle aspects including evaluation, monitoring, drift detection, retraining, and performance reporting.

• Collaborate with engineering to provide models through low-latency APIs and scalable services.

• Contribute to efforts involving GPU acceleration and large-scale data processing.

• Assist in establishing machine learning best practices, tools, and standards across the team.

• Define machine learning architecture and deliver models that operate with sub-second latency.

• Report directly to the Head of Data Science & AI.

⛳️ Requirements

• Over 5 years of experience in developing and implementing machine learning systems in production environments.

• Strong expertise in Python for machine learning, data processing, and model serving.

• Practical experience in feature engineering, model training, and evaluation for real-world datasets.

• Experience in deploying machine learning models via APIs or services, including FastAPI, containers, or Kubernetes.

• Solid grasp of data modeling, SQL, and analytical workflows.

• Experience in a cloud environment such as GCP, AWS, or similar.

• Preferred: Familiarity with graph data, graph databases, or graph-based machine learning.

• Preferred: Knowledge of Neo4j, Cypher, or graph algorithms.

• Preferred: Experience with XGBoost, tree-based models, or comparable classical machine learning techniques.

• Preferred: Exposure to real-time or streaming systems, such as Kafka, Pub/Sub, or event-driven architectures.

• Preferred: Experience with MLOps tools and practices, including CI/CD for machine learning, monitoring, and retraining pipelines.

• Preferred: Experience with GPU or large-scale data processing technologies, such as RAPIDS, CUDA, or Spark.

• Preferred: Domain knowledge in identity resolution, marketing technology, or email deliverability.

🏝️ Benefits

• Health, vision, and dental insurance.

• Equity options.

• Performance incentives.

• Remote-first culture.

• High ownership and autonomy in a senior, hands-on role.

• Clear growth path toward Staff / Principal IC roles.