About Orita
Directtoconsumer 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.
As a Senior Machine Learning Engineer at Orita, you will:
Build and Productionize Models: Design, train, and deploy models that directly power our marketingfocused 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 AB testing, uplift modeling, causal inference, and other advanced experimentation frameworks to validate and refine model performance.
Collaborate & Mentor: Work closely with crossfunctional 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.
Please apply even if you don’t meet every requirement. We’re looking for a versatile engineer who can learn quickly and own problems endtoend.
Education & Experience
5+ years of fulltime software engineering experience, including at least 3 years working on ML systems.
ML Expertise:
Deep knowledge of modern machine learning algorithms (treebased methods, deep learning architectures, transformersLLMs).
Handson experience with PyTorch, TensorFlow, XGBoost or equivalent frameworks.
Feature engineering using aggregations, embeddings, and submodels.
MLOps & Cloud:
Track record building productionscale ML infrastructures, ideally using GCP (Vertex AI, KubeFlow, BigQuery, etc.).
Familiarity with CICD, containerization (DockerKubernetes), 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 realworld 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 nontechnical stakeholders.
Selfstarter mentality with the ability to own projects from ideation to deployment, picking up and learning new technologies as needed.
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 fastpaced or startup environment.
You live in or near New York City. Most of us work in EST.
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 treebased methods to cuttingedge 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 individuals 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.
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