{"id":3451607,"url":"https://alion.io/job/betty-machine-learning-engineer-betty-ca","title":"Machine Learning Engineer | Betty CA","company":{"id":1776028,"name":"Betty","domain":"betty.ca","url":"https://alion.io/company/betty-ca","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Sofia, Bulgaria"],"countries":["BG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"AI Agents","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Apache Kafka","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Feature Store","optional":false},{"name":"Flink","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SQL","optional":false},{"name":"Kubernetes","optional":true},{"name":"MLFlow","optional":true},{"name":"Tableau","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-29T09:32:19Z","employer_posted_date":null,"last_verified_at":"2026-10-29T09:32:19Z","board_verified":false,"closed_at":null,"days_open":3,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":3},"description":"About Us:\n\nBetty is an innovative entertainment company pioneering at the intersection of real-money online casinos and casual mobile gaming.\n\nBetty Canada is a scale up company accredited by the Alcohol and Gaming Commission of Ontario (AGCO) as a B2C operator in February 2023, we’ve set a new standard in the industry.\n\nOur mission is to redefine the online casino experience by offering a uniquely transparent environment where players can relax, unwind, and enjoy themselves safely. We are committed to accessibility, fairness, and inclusivity, fostering a community of like-minded individuals who value ethical gaming practices and prioritize our players’ safety and enjoyment above everything else.\n\nOur Values:\n\nWe are honest: we value honesty in all aspects.\n\nBring the Olives: we offer premium customer experience.\n\nThink Big: we believe in always striving for more.\n\nKey responsibilities:\n\nDesign, build and ship AI solutions based on LLMs, such as AI agents, retrieval-augmented generation (RAG) and automated analysis and reporting, that teams across the business use every day.\n\nHelp shape how Betty adopts AI: find high-value use cases, evaluate models and tools, and set up checks that AI outputs are accurate, reliable and cost-effective.\n\nPartner with the marketing and user acquisition teams on channel and campaign performance, using metrics such as CAC, ROAS, CPA, first-time depositors (FTDs), conversion rates and predicted LTV.\n\nBuild marketing models such as predicted LTV for newly acquired players, attribution, marketing mix modeling, incrementality measurement and budget allocation across channels.\n\nWork with analysts, marketing, product and business stakeholders to turn business questions into clear requirements, success metrics and use cases.\n\nWork with large event-level data in Redshift, and combine and clean data from internal and external sources such as player activity, transactions, payments, CRM and marketing platforms.\n\nBuild statistical and machine learning models for problems such as player lifetime value, churn and retention, segmentation, forecasting and driver analysis.\n\nForm and test hypotheses about player and commercial behavior, and turn the answers into clear recommendations, including how they affect our players.\n\nFind opportunities and inefficiencies across player segments, games, providers, payment flows and channels, and run deep-dives that support product launches and marketing campaigns.\n\nSupport experimentation and A/B testing: define success metrics, analyze results and know when a result is real.\n\nTake models from prototype to production and own them end to end, from batch jobs on daily, weekly and monthly schedules to real-time inference where speed matters.\n\nBuild and run real-time pipelines that stream player events (for example with Kafka or Flink), compute features on live data and serve predictions with low latency, such as real-time churn and retention signals.\n\nSet up the MLOps foundations: CI/CD for models, model registry and versioning, a feature store, automated retraining, and monitoring for drift, data quality and model performance.\n\nPresent results through dashboards and clear recommendations to any audience, up to C-level.\n\nHelp other teams use data and AI on their own, through self-service analytics and shared environments where they can safely deploy their own AI tools.\n\nWork within the rules of a regulated market, including responsible gambling and data privacy requirements.\n\nRequirements:\n\n3+ years of experience as a Data Scientist/ML Engineer.\n\nStrong knowledge of statistics and machine learning methods, such as predictive modeling, classification, clustering, regression, and optimization.\n\nAdvanced Python with strong software engineering practices (testing, code review, Git), and advanced SQL with Redshift or a comparable cloud data warehouse.\n\nProven experience deploying and running ML models in production, including CI/CD, containers (Docker), model versioning, automated retraining and monitoring for drift and performance.\n\nHands-on experience building solutions with LLMs and generative AI, such as retrieval-augmented generation (RAG), AI agents and tool use, prompt engineering and NLP.\n\nExperience working with LLM APIs and frameworks, and with evaluating AI outputs for accuracy, reliability, and cost.\n\nGood judgment on where AI adds value and where a simpler method works better, and you keep up with new models and tools.\n\nProven experience applying models to business problems such as forecasting, segmentation, lifetime value, retention, churn, or engagement.\n\nExperience with large datasets (100M+ rows and many variables).\n\nThe ability to work with messy, incomplete, and changing data and still produce reliable results.\n\nClear communication: you can explain complex work to people who don’t want the detail, and manage expectations honestly.\n\nComfortable working in a fast-paced environment.\n\nFluent English, written and spoken.\n\nNice to have:\n\nStrongly preferred: experience with marketing data and its terminology, such as user acquisition, CAC, ROAS, FTDs, attribution, marketing mix modeling, incrementality, predicted LTV, and campaign and creative performance.\n\nOnline casino experience from any part of the business, or experience in iGaming, sports betting, gaming, fintech or another high-volume consumer business.\n\nHands-on Tableau or a comparable BI tool.\n\nExperience with streaming data and real-time ML: event streaming (Kafka, Flink or similar), feature computation on live data and low-latency model serving through APIs.\n\nHands-on experience with MLOps and orchestration tools such as MLflow, Airflow, Kubernetes, Terraform or a feature store.\n\nExperience working with APIs and third-party data sources.\n\nExperience running LLM applications in production, including vector databases, agent frameworks, output evaluation and cost monitoring.\n\nWhat we offer:\n\nCompetitive salary\n\nPerformance-based bonus\n\nCareer and skills development opportunities\n\nFun and collaborative team environment\n\nNew modern office 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