{"id":26729,"url":"https://alion.io/job/toogeza-ml-engineer","title":"ML Engineer","company":{"id":7168,"name":"Toogeza","domain":"toogeza.tech","url":"https://alion.io/company/toogeza","size_band":"51-200","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":93,"open_postings":45,"ghost_share":0,"stale_share":0.067,"repost_share":0,"time_to_fill_p50_days":126,"computed_at":"2026-10-16T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":99000,"max_usd":254000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2102},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Agile","optional":false},{"name":"Anthropic","optional":false},{"name":"Computer Vision","optional":false},{"name":"Fine-tuning","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenAI","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-06-22T10:59:36Z","employer_posted_date":"2026-06-22","last_verified_at":"2026-10-17T03:25:35Z","board_verified":true,"closed_at":null,"days_open":116,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":115},"description":"We are toogeza, a Ukrainian recruiting company that is focused on hiring talents and building teams for tech startups worldwide. People make a difference in the big game, and we may help to find the right ones.\nCurrently, we are looking for an experienced Senior ML Engineer to join one of toogeza’s clients.\nProfessional qualifications\n7+ years’ experience in Machine Learning / Data Science, with 3+ years in credit-lending organisations.\n\nDemonstrated delivery and productionisation of Probability-of-Default (PD) models, credit-limit strategies, fraud-detection, conversion-uplift, and collections-optimisation models.\n\nAdvanced Python proficiency and solid grasp of modern ML algorithms, feature engineering, and model-evaluation best practices.\n\nAbility to write, structure, and optimise complex SQL queries.\n\nDeep understanding of the credit lifecycle, especially online lending workflows.\n\nProven skill in sourcing, cleansing, and generating features from data sets.\n\nComfortable setting up and maintaining modelling environments (local, cloud, or on-prem).\n\nDetail-oriented, accountable, and committed to both team and individual targets.\n\nEnglish: Intermediate (B1) or higher.\n\nPreferred / bonus qualifications\nPractical experience with LLM solutions:\n\nUsing commercial APIs (e.g., OpenAI, Anthropic, etc.).\n\nSelf-hosting of open-source models\n\nFine-tuning of open-source models.\n\nBuilding voice chatbots.\n\nBuilding RAG chatbots.\n\nExperience with Computer Vision models for document or image processing.\n\nBuilding ML pipelines and deploying models to production.\n\nCreating executive dashboards and model reports in Power BI.\n\nMain responsibilities\nDesign, train, and deploy probability of default models.\n\nBuild credit-limit strategies.\n\nDiscover and scope AI/ML opportunities that boost efficiency and revenue of the company, including collections optimisation, fraud control, conversion lift, etc.\n\nAnalyse data sources and engineer features for modelling.\n\nProduce and update internal model documentation.\n\nImplement model monitoring.\n\nPlan and execute A/B tests.\n\nBuild Computer Vision pipelines to automate lending workflows.\n\nDevelop LLM-based solutions that streamline internal processes or enhance customer experience.\n\nExpected results\nImplemented probability of default models and credit-limit strategies.\n\nLaunched A/B tests for models that potentially can boost the efficiency and/or revenue of the company.\n\nThorough, audit-ready documentation for models.\n\nWhat We Offer\nJoin a fast-scaling FinTech company where your decisions shape the business and your contributions truly matter.\n\nEnjoy 20 paid days off annually, flexible scheduling, and a supportive, people-first culture.\n\nPartial compensation for medical insurance, sports activities, and foreign language.\n\nWork in an international, agile team with ambitious goals, modern tools, and a strong sense of purpose.\n\nProfessional qualifications\n7+ years’ experience in Machine Learning / Data Science, with 3+ years in credit-lending organisations.\n\nDemonstrated delivery and productionisation of Probability-of-Default (PD) models, credit-limit strategies, fraud-detection, conversion-uplift, and collections-optimisation models.\n\nAdvanced Python proficiency and solid grasp of modern ML algorithms, feature engineering, and model-evaluation best practices.\n\nAbility to write, structure, and optimise complex SQL queries.\n\nDeep understanding of the credit lifecycle, especially online lending workflows.\n\nProven skill in sourcing, cleansing, and generating features from data sets.\n\nComfortable setting up and maintaining modelling environments (local, cloud, or on-prem).\n\nDetail-oriented, accountable, and committed to both team and individual targets.\n\nEnglish: Intermediate (B1) or higher.\n\nPreferred / bonus qualifications\nPractical experience with LLM solutions:\n\nUsing commercial APIs (e.g., OpenAI, Anthropic, etc.).\n\nSelf-hosting of open-source models\n\nFine-tuning of open-source models.\n\nBuilding voice chatbots.\n\nBuilding RAG chatbots.\n\nExperience with Computer Vision models for document or image processing.\n\nBuilding ML pipelines and deploying models to production.\n\nCreating executive dashboards and model reports in Power BI.\n\nMain responsibilities\nDesign, train, and deploy probability of default models.\n\nBuild credit-limit strategies.\n\nDiscover and scope AI/ML opportunities that boost efficiency and revenue of the company, including collections optimisation, fraud control, conversion lift, etc.\n\nAnalyse data sources and engineer features for modelling.\n\nProduce and update internal model documentation.\n\nImplement model monitoring.\n\nPlan and execute A/B tests.\n\nBuild Computer Vision pipelines to automate lending workflows.\n\nDevelop LLM-based solutions that streamline internal processes or enhance customer experience.\n\nExpected results\nImplemented probability of default models and credit-limit strategies.\n\nLaunched A/B tests for models that potentially can boost the efficiency and/or revenue of the company.\n\nThorough, audit-ready documentation for models.\n\nWhat We Offer\nJoin a fast-scaling FinTech company where your decisions shape the business and your contributions truly matter.\n\nEnjoy 20 paid days off annually, flexible scheduling, and a supportive, people-first culture.\n\nPartial compensation for medical insurance, sports activities, and foreign language.\n\nWork in an international, agile team with ambitious goals, modern tools, and a strong sense of purpose.","description_format":"text","description_chars":5477,"description_truncated":false,"requirements":{"experience_years_min":7,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"Intermediate (B1)","optional":false}]},"benefits":["Health insurance","Sports 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