Senior Software Engineer – Machine Learning, AI

🔥 0 minutes ago

🌐 United States, Canada – Remote

🇺🇸 United States – Remote 🇨🇦 Canada – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Givelify

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2013

🤲 Charity

🤝 Non-profit

☁️ SaaS

Charity • Non-profit • SaaS

Givelify is a platform focused on empowering donors and organizations through its highly rated giving app, designed to make charitable contributions simple and accessible. The company provides comprehensive solutions for donor management and engagement, integrating AI-powered insights to improve donor relationships. Givelify partners with over 70,000 organizations and has facilitated over $1 billion in donations, positioning itself as a leader in charitable giving technology, particularly for nonprofits and places of worship.

📋 Description

• Design, build, and ship machine learning models powering real-time decisions across Givelify’s giving platform • Build personalized recommendation systems connecting donors with relevant organizations and causes • Develop AI-based fraud detection and risk-scoring systems • Own ML problems end-to-end, including mathematical framing, model training, evaluation, and deployment • Ensure models operate within Givelify’s value systems and avoid negative donor experiences • Own production reliability and model quality • Maximize product goals while minimizing false positives and negative experiences • Research and prototype computational, statistical, and AI models using real-world donor datasets • Productize machine learning systems for personalized recommendations • Build AI systems using large-scale real-time data for engineering reliability and fraud prevention • Translate ambiguous product problems into ML formulations involving ranking, classification, and anomaly detection • Build and maintain end-to-end ML pipelines covering feature engineering, training, evaluation, A/B testing, and deployment • Ship real-time inference services and collaborate with Platform/DevOps on scalability, latency, and monitoring • Mentor engineers on ML best practices, scientific rigor, and code quality

🎯 Requirements

• Master’s or PhD in Computer Science, Computer Engineering, Electrical Engineering, Statistics, Applied Mathematics, or a STEM field, or equivalent research experience • 2+ years of building and deploying machine learning systems in production • Deep grounding in probability and statistics, linear algebra, and optimization • Hands-on experience with classical ML and deep learning, including gradient-boosted trees, embedding models, and transformers • Experience with large-scale data processing, Spark, distributed training, feature stores, and modern ML tooling • Experience with PyTorch or TensorFlow, scikit-learn, and MLflow or similar • Track record in recommender systems, fraud/risk modeling, search ranking, or real-time classification • Research background, publications, thesis work, or applied research is a strong plus • Scientific rigor, ownership mindset, effective communication, customer focus, integrity, and problem-solving

🏖️ Benefits

• Competitive pay • Full benefits • Flexible PTO • Amazing perks • Opportunity to put passion and purpose front and center