Senior Machine Learning Engineer, AI Decisioning

🕒 May 5

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Insider One

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2012

☁️ SaaS

🤖 Artificial Intelligence

🤝 B2B

💰 $500M Series E on 2024-12

SaaS • Artificial Intelligence • B2B

Insider One is an AI-native customer engagement and personalization platform delivered as SaaS. It provides a unified customer data platform (CDP), personalization, journey orchestration, reporting/analytics, and behavioral insights, and connects to 100+ integrations to support multichannel marketing across web, email, mobile apps, site search, SMS/RCS, WhatsApp, push, and conversational CX. The platform targets marketing and customer engagement teams at enterprise and e-commerce brands to improve engagement, conversions, and lifetime value.

📋 Description

• Design, build and release real-time decisioning systems that learn from interaction feedback at scale. • Own the modeling logic from how we represent users and signals to how reward attribution closes the loop and improves the next interaction. • Move ideas from papers and notebook prototypes including online learning policies and counterfactual estimators to production code that runs behind real-time APIs. • Design and build resilient streaming/batch pipelines that feed user state, reward signals, and offline replay. • Run honest experiments, A/B test what you ship, design offline evaluation for what you cannot, and kill your own work. when it doesn’t outperform against the baseline. • Continuously monitor and improve the quality, latency, observability, and scalability of the systems. • Collaborate across platform and product teams to turn research-grade ideas into production-grade products. • Share context, mentor engineers, raise the technical bar of the team, and help set direction for how we do ML at scale.

🎯 Requirements

• You don’t need to tick every box • if you likely have: • - Designed and deployed personalization, ranking, or recommendation systems used by real users; improved core engagement metrics (CTR, conversion, retention, revenue) and can talk concretely about the lift • - Familiarity with sequential recommendation, ranking, or joint / multi-objective optimization problems where you can't optimize one metric without trading off another • - A/B tested the impact you’ve provided and iterated based on what the data said • - Comfortable with the messy reality of production ML: cold start, sparse signal, label delay, feedback loops, distribution shift • - Solid grounding in probabilistic modelling (Bayesian inference, calibration, hierarchical models) and modern recommender techniques (embeddings, sequence models, LLM-driven content understanding), applied to sequential, ranking, or multi-objective problems • - Software engineering, production-quality code and at least one programming language, care about API contracts, testing, and observability, not just notebooks • - Built high-throughput real-time or batch pipelines supporting ML training and inference, on AWS (or an equivalent major cloud) comfortable owning a service end to end across compute, storage, networking, and CI/CD • - Have moved at least one model from a paper, a notebook, or a whiteboard sketch into a real system that serves traffic, and can speak honestly about what broke along the way • and it would be a strong plus if you have any of below: • - Hands-on experience with online decision-making under uncertainty, multi-armed bandits, contextual bandits, Thompson sampling, UCB, or RL agents that have served traffic • - Comfortable reasoning about exploration vs exploitation, regret, off-policy evaluation (IPS, doubly robust), counterfactual estimation, and the failure modes of each • - Causal inference / uplift modeling • - Academic research experience or publications in online decision-making under uncertainty, reinforcement learning, sequential recommendation, optimization, or related fields.

🏖️ Benefits

• Curiosity and initiative you love to figure things out and solve complex problems. • Collaborative ownership and team/product-first approach. • Breadth and depth you’re excited to grow into M-shaped product engineer. • Self-organization and full ownership through real-world impact. • A strong team that ships and learns together. • Continuous mentorship and technical coaching. • Enjoy a monthly meal allowance designed to enhance your daily routine. • Access comprehensive private health insurance. • Feed your curiosity with access to Spotify, LinkedIn Learning, Blinkist, MasterClass, Neoskola, and CloudGuru. • Level up with internal trainings covering AI fundamentals, coding, foreign languages, and a wide range of personal development skills. • Be part of a diverse team that’s as global as it gets, where every voice is heard and 50+ nationalities build together. • Become a Shareowner through our eligibility-based “ESOP” and own a piece of what you build. • Help build the team you want to work with and enjoy rewarding referral bonuses. • Opportunities to give back to your community through volunteering and purpose-driven social impact projects. • From global retreats to team-building activities, expect year-round events that turn into lifelong memories. • Get inspired by the greatest minds in the tech industry through events like our Tech & Dev Talks. • Work from anywhere in Turkey through our fully remote setup.