Machine Learning Engineer

Job Description

About Sadaora & This Opportunity:

At Sadaora, we believe your life deserves more than noise—it deserves clarity, purpose, and power. That’s why we are building NewBlazr, the world’s most advanced lifestyle platform, designed to know you, grow with you, and guide you. By combining the richness of your identity with a living intelligence system,** NewBlazr delivers deeply personalized insights and recommendations** that meet you exactly where you are. It understands your rhythms, anticipates your needs, and empowers every decision with confidence. This is more than technology. It’s your trusted companion in becoming the fullest, most informed version of yourself.

We are a startup company that raised $130k in our pre-seed round. We built an MVP that excited our community and allowed us to obtain critical feedback to help guide our next steps. Now we are expanding our team to create the next version of the app , while driving the company to new heights. We expect to raise our seed round in months, and establish our Discord community within weeks.

About This Role

Are you a data-savvy innovator with a passion for crafting intelligent systems? As a Machine Learning Engineer at Sadaora you'll be instrumental in transforming vast datasets into actionable insights, driving the evolution of our AI capabilities. You'll design and implement sophisticated machine learning models, optimize algorithms for performance, and deploy scalable solutions that enhance our products and services.

This role is ideal for someone who thrives on tackling complex challenges, excels in dynamic environments, and is dedicated to building high-impact AI applications. You'll collaborate closely with cross-functional teams—including data scientists, software engineers, and product managers—to bring visionary ideas to fruition. If you're eager to push the boundaries of machine learning and contribute to cutting-edge solutions in a collaborative setting, let's innovate together!

Your Tasks

Model Development & Deployment

• Design, train, and evaluate machine learning models using best-in-class frameworks.
• Architect scalable ML solutions and pipelines, from feature engineering to deployment.
• Implement rigorous testing, validation, and monitoring processes to ensure model reliability in production.

Data Engineering & Infrastructure

• Work closely with data engineers to shape the data architecture required for robust ML workflows.
• Build efficient ETL pipelines to clean, preprocess, and transform large-scale datasets.

Collaboration & Integration

• Partner with product managers, engineers, and business stakeholders to define ML use cases.
• Collaborate with software engineers to integrate ML models into production-grade APIs and applications.
• Translate complex ML concepts into business-relevant insights and recommendations.

Research & Innovation

• Stay current with advancements in machine learning, AI, and related fields.
• Experiment with new algorithms, architectures, and tools to continuously enhance our capabilities.
• Contribute to a culture of experimentation, technical excellence, and intellectual curiosity.

Requirements

Required Qualifications

• 5+ years of experience developing, deploying, and maintaining ML models in production environments.
• Proficiency in Python and common ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch, XGBoost).
• Strong foundation in statistics, linear algebra, probability, and optimization.
• Deep understanding of a range of ML techniques (regression, classification, clustering, NLP, deep learning).
• Experience with cloud platforms such as AWS, GCP, or Azure.
• Familiarity with containerization and orchestration tools (Docker, Kubernetes).
• Solid understanding of software engineering principles, version control (Git), and CI/CD workflows.

Preferred Qualifications

• Experience working with unstructured data (e.g., text, images, audio).
• Exposure to MLOps tools and workflows (e.g., MLflow, TFX, SageMaker, Vertex AI).
• Background in building recommender systems, time series models, or generative AI applications.
• Working knowledge of data privacy, ethics, and model explainability (e.g., SHAP, LIME).
• Contributions to open-source ML projects or publications in peer-reviewed forums.

Benefits

Salary + Equity

USD $130k – $200k + 0.5% – 1.25%

• Competitive salary, bonus, & equity packages
• Fully Remote & Flexible Work Schedule
• 401(k) retirement plan
• Unlimited PO
• Health, Dental, & Vision Insurance premiums fully covered by the company
• Leadership, Stretch Assignment and Growth Opportunities

We are actively securing growth funding while preparing for our public launch in summer of 2025, when user-driven revenue begins. At that time, this role will transition into a full-time salaried position within the stated annual range. Until then, compensation will be deferred.