Senior Machine Learning Engineer

April 24

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Orita

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Artificial Intelligence • eCommerce • Marketing

Orita is an AI-driven customer engagement platform that helps businesses optimize their email and direct mail marketing efforts by creating custom machine learning models. Orita analyzes customer data to identify behaviors that predict outcomes such as purchases and user engagement. By segments audiences accurately, it improves the performance of marketing campaigns, thereby maximizing the return on investment (ROI) for its clients. With a focus on deliverability and incremental sales, Orita offers reliable solutions for brands looking to enhance their existing marketing strategies without requiring complex setups.

11 - 50 employees

Founded 2021

🤖 Artificial Intelligence

🛍️ eCommerce

📋 Description

• Build and Productionize Models: Design, train, and deploy models that directly power our marketing-focused products. • Develop Scalable ML Infrastructure: Architect and maintain robust, scalable, MLOps pipelines. • Experiment & Optimize: Drive continuous improvement using A/B testing, uplift modeling, causal inference, and other advanced experimentation frameworks. • Collaborate & Mentor: Work closely with cross-functional teams to align on product goals and foster best practices.

🎯 Requirements

• 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. • 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.). • Strong proficiency in Python (numpy, pandas, etc.). • Experience with scalable data processing (Spark, Ray, BigQuery). • 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.

🏖️ 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.