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We are looking for a Senior Machine Learning Engineer who wants to take their career one step further by working on one of the most consequential AI surfaces at Insider One, the engine that powers personalized experiences in real time. If you are drawn to problems like online decision-making under uncertainty, sequential recommendation, joint optimization across competing objectives, read on.
At Insider One, we work on the hard problems behind making customer engagement feel personal at scale — where machine learning meets a real user, in real time, across every channel they use.
What You Will Do
- 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.
What You Will Need
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.
What We Offer
- 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.
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