Senior Machine Learning Engineer

Role Description

As a Senior Machine Learning Engineer at Orita, you will:

• Build and Productionize Models: Design, train, and deploy models that directly power our marketing-focused products, primarily for marketing use cases.
• Develop Scalable ML Infrastructure: Architect and maintain robust, scalable, MLOps pipelines to ensure reliable training, serving, and monitoring of models in production.
• Experiment & Optimize: Drive continuous improvement using A/B testing, uplift modeling, causal inference, and other advanced experimentation frameworks to validate and refine model performance.
• Collaborate & Mentor: Work closely with cross-functional teams, including the CEO and CTO, to align on product goals and foster best practices for machine learning and data engineering across the organization.

Qualifications

• 5+ years of full-time software engineering experience, including at least 3 years working on ML systems.
• Deep knowledge of modern machine learning algorithms (tree-based methods, deep learning architectures, transformers/LLMs).
• Hands-on experience with PyTorch, TensorFlow, XGBoost or equivalent frameworks.
• Feature engineering using aggregations, embeddings, and sub-models.
• Track record building production-scale ML infrastructures, ideally using GCP (Vertex AI, KubeFlow, BigQuery, etc.).
• Familiarity with CI/CD, containerization (Docker/Kubernetes), and distributed training (Spark, Ray, Dask, etc.).
• Experience iterating models in a production environment is a must.
• Strong proficiency in Python (numpy, pandas, etc.).
• Experience with scalable data processing (Spark, Ray, BigQuery).
• Job orchestration (Airflow).
• Comfortable with advanced experimentation techniques.
• Understanding of performance measurement in real-world deployments.
• Comfortable wearing many hats—data wrangling, model development, deployment, monitoring, and performance optimization.
• Excellent communication—able to explain complex ML concepts to non-technical stakeholders.
• Self-starter mentality with the ability to own projects from ideation to deployment, picking up and learning new technologies as needed.

Requirements

• Familiarity with marketing technology or ads is a strong plus.
• Experience with experimental design and methods such as causal inference or uplift modeling.
• Exposure to modeling with LLMs and modern AI tooling.
• Productionizing Reinforcement Learning and Bandit algorithms.
• Ph.D in a technical field.
• Experience in a fast-paced or startup environment.
• You live in or near New York City. Most of us work in EST.

Benefits

• Impact: Join a lean, agile team shaping the future of ML for leading global brands.
• Growth: Work directly with industry veterans with strong academic and professional backgrounds.
• Innovation: Experiment with the latest ML models, from tree-based methods to cutting-edge LLMs.
• Culture: We value ownership, iteration, and continuous learning—everyone’s voice matters.