Senior Machine Learning Engineer

Job not on LinkedIn

🔥 0 minutes ago

🗽 New York – Remote

🗽 New York – Remote

💵 $180k - $250k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

Apply Now

Find Similar Remote Jobs

Receive Emails For Remote Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Orita

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2021

🤖 Artificial Intelligence

🛍️ eCommerce

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.

📋 Description

• 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.

🎯 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. • 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. 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.

🏖️ Benefits

• Offers Equity