Senior Machine Learning Engineer

This is a fully remote position, open to applicants in New York.

📋 Description

• Design and Productionize Models: Create, train, and implement models that serve as the backbone for our marketing-oriented products, primarily targeting marketing applications.

• Develop Robust ML Infrastructure: Engineer and uphold resilient, scalable MLOps pipelines to guarantee dependable training, serving, and monitoring of models in a production setting.

• Experiment & Optimize: Foster ongoing enhancements through A/B testing, uplift modeling, causal inference, and other sophisticated experimentation frameworks to assess and refine model efficacy.

• Collaborate & Mentor: Partner closely with cross-functional teams, including the CEO and CTO, to synchronize on product objectives and cultivate best practices for machine learning and data engineering throughout the organization.

⛳️ Requirements

• Over 5 years of full-time software engineering experience, with a minimum of 3 years dedicated to ML systems.

• Extensive understanding of contemporary machine learning algorithms (tree-based methods, deep learning architectures, transformers/LLMs).

• Practical experience with PyTorch, TensorFlow, XGBoost, or similar frameworks.

• Proficient in feature engineering utilizing aggregations, embeddings, and sub-models.

• Proven experience in building production-scale ML infrastructures, preferably using GCP (Vertex AI, KubeFlow, BigQuery, etc.).

• Knowledge of CI/CD, containerization (Docker/Kubernetes), and distributed training (Spark, Ray, Dask, etc.).

• Demonstrated experience in iterating models within a production environment is essential.

• Strong command of Python (numpy, pandas, etc.).

• Experience with scalable data processing (Spark, Ray, BigQuery).

• Familiarity with job orchestration tools (Airflow).

• Comfortable applying advanced experimentation methodologies.

• Understanding of performance metrics in real-world applications.

• Versatile in taking on diverse roles—data wrangling, model development, deployment, monitoring, and performance enhancement. We value ownership over the complete lifecycle.

• Excellent communication skills—capable of conveying intricate ML concepts to non-technical audiences.

• Self-driven with the capability to manage projects from ideation to deployment, adept at acquiring and mastering new technologies as needed.

🏝️ Benefits

• Offers Equity