Senior Machine Learning Engineer

About Orita

Direct-to-consumer brands pay us, in order to market less. Well, technically, they pay us to market more effectively. And, strangely (!), that often means marketing a lot less.

How? We use a lot of math and a lot of machine learning to decide which people on their subscriber lists actually want to hear from them right now.

The Role

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 CTO and Director of Data, to align on product goals and foster best practices for machine learning and data engineering across the organization.

Ideal Background

Please apply even if you don’t meet every requirement. We’re looking for a versatile engineer who can learn quickly and own problems end-to-end.

Education & Experience

5+ years of full-time software engineering experience, including at least 3 years working on ML systems.

ML Expertise :

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.

MLOps & Cloud :

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.

Software Engineering Skills

Strong proficiency in Python (numpy, pandas, etc.).

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

Analytical & Statistical Background

Comfortable with advanced experimentation techniques.

Understanding of performance measurement in real-world deployments.

Soft Skills & Culture

Comfortable wearing many hats—data wrangling, model development, deployment, monitoring, and performance optimization. We value ownership of the full lifecycle.

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.

Bonus Points

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.

Why Orita?

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.

Orita is an Equal Opportunity Employer and does not discriminate on the basis of an individual's sex, age, race, color, creed, national origin, alienage, religion, marital status, pregnancy, sexual orientation, or affectional preference, gender identity and expression, disability, genetic trait or predisposition, carrier status, citizenship, veteran or military status and other personal characteristics protected by law. All applications will receive consideration for employment without regard to legally protected characteristics.