Orita
Tech / AI / Software
SeniorMachineLearningEngineer
Neural analysis suggests this role is
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“Senior Machine Learning Engineer at Orita. Skills: Machine Learning, MLOps, Python, GCP, experimentation, model deployment. Build and Productionize Models. Design, train, and deploy models that directly power our marketing-focused products, primarily for marketing use cases”
Industry & Context.
own problems end-to-end; performance optimization; Self-starter mentality with the ability to own projects from ideation to deployment
What They're Looking For.
Must Have
5+ years of full-time software engineering experience, 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), distributed training (Spark, Ray, Dask, etc.), Experience iterating models in a production environment is a must, 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
Nice to Have
Familiarity with marketing technology or ads is a 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
What You'll Do.
Build and Productionize Models
and deploy models that directly power our marketing-focused products
primarily for marketing use cases
Develop Scalable ML Infrastructure
Architect and maintain robust
MLOps pipelines to ensure reliable training
and monitoring of models in production
Experiment & Optimize
Drive continuous improvement using A testing
and other advanced experimentation frameworks to validate and refine model performance
How You'll Work.
Team & Collaboration
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
Communication Scope
Excellent communication—able to explain complex ML concepts to non-technical stakeholders
Process & Methodology
own problems end-to-end, ownership of the full lifecycle, own projects from ideation to deployment
Full Job Description
About Orita Orita builds AI customer segments for many of the best brands in the world including (deep breath) Spanx, ThirdLove, True Classic, Tracksmith, Harney & Sons, Sun Bum, Ministry of Supply, Thursday Boots, gorjana, and hundreds more. Orita’s algorithms help brands understand who wants to hear from them, when, and through what channel (email, SMS, direct mail today, more coming soon …). By messaging prospects and customers when they’re actually listening, you’re able to make a bunch of money. In a world where acquisition costs are skyrocketing, fixing retention and driving LTV is the key to profitable growth. 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 CEO and CTO, 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,
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