{"id":2291427,"url":"https://alion.io/job/coinis-senior-machine-learning-engineer-ad-performance","title":"Senior Machine Learning Engineer , Ad Performance","company":{"id":56062,"name":"Coinis","domain":"coinis.com","url":"https://alion.io/company/coinis","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career sitemap","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Podgorica, Montenegro"],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":44000,"max_usd":110000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2002},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Pandas","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"bandit","optional":true},{"name":"Feature Store","optional":true},{"name":"Reinforcement Learning","optional":true}],"status":"live","first_seen_at":"2026-10-11T18:39:31Z","employer_posted_date":"2026-10-11","last_verified_at":"2026-10-11T23:12:43Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"About us\nWhat you will do\nBuild the performance feedback loop. Ad metrics in, creative patterns out.\nTrain models that predict creative win rate before spend.\nDesign ranking systems for creative variants under budget constraints.\nPartner with the generative team. Your signals guide their generation.\nBuild dashboards the media buying team actually uses daily.\nRun experiments. Hold-outs, uplift tests, counterfactual analysis.\nShip to production. Not notebooks.\nAbout your position\nEvery ad that runs through Coinis becomes a data point. You turn that data into an optimization loop that makes the next creative smarter. Creative scoring, audience matching, budget allocation, ROAS prediction. This is the flywheel that makes Coinis pull ahead of every creative-only tool.\nJob requirements\nMust have\n5+ years in ML, data science, or applied stats with a shipping track record.\nStrong Python. Pandas, scikit-learn, PyTorch or equivalent.\nCausal inference and experimentation design experience.\nProduction ML experience. Serving, monitoring, retraining.\nComfort with messy real-world ad performance data.\nNice to have\nMeta Marketing API data pipelines.\nContextual bandits or reinforcement learning in production.\nFeature stores. MLOps tooling.\nMulti-armed bandit budget allocation.\nQualifications\n01\nEducation\n MSc preferred in Statistics, ML, Computer Science, or related. BSc with strong experience also welcome.\n02\nExperience\n 5+ years\n03\nSkills\n Python, PyTorch, scikit-learn, Causal Inference, Experimentation, MLOps, Meta Marketing API, Contextual Bandits, ROAS Modeling, Feature Stores\nWhat we offer\nWhat you get\nCompetitive salary in EUR.\nEquity in the SaaS spinout.\nAccess to live Meta ad spend data across thousands of advertisers via our media buying operations.\nRare real data. Not a sandbox.\nRemote-first with flexible hours.\nCompute and research budget.\nOther information\nYou will work directly with our in-house media buying team. They run active daily Meta ad spend. 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