{"id":3272469,"url":"https://alion.io/job/accesa-senior-machine-learning-engineer-recommendation-systems-personalization","title":"Senior Machine Learning Engineer (Recommendation Systems & Personalization)","company":{"id":6720,"name":"Accesa","domain":"accesa.eu","url":"https://alion.io/company/accesa","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"B","score":80,"open_postings":4,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":11,"computed_at":"2026-10-29T05:49:05Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Tashkent, Uzbekistan"],"countries":["UZ"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":18000,"max_usd":47000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2365},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"CI/CD","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Terraform","optional":false},{"name":"Vertex AI","optional":false}],"status":"live","first_seen_at":"2026-10-26T12:18:53Z","employer_posted_date":null,"last_verified_at":"2026-10-26T12:18:53Z","board_verified":false,"closed_at":null,"days_open":3,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":3},"description":"Responsibilities: \n Develop real-time product and bundle recommendation engines, including dynamic slot placement optimized for conversion and margin.\n Build targeted promotion algorithms: personalized coupon and points issuance, behavioral triggers and dynamic bundling.\n Scale the multi-market customer segmentation engine (behavioral, demographic, psychographic and lookalike audiences, wallet push).\n Extend personalization models across web, app and in-store employee touchpoints.\n Build and operate ML pipelines, from feature preparation in BigQuery and Snowflake to deployment and monitoring.\n Design and evaluate A/B tests to prove the business impact of each model.\n Requirements: Hands-on experience building ranking or recommender systems that run in production.\n Strong Python and SQL skills; experience with TensorFlow or PyTorch.\n Solid grounding in model evaluation and validation, both offline metrics and online results.\n Experience designing and analyzing A/B tests and experiments.\n MLOps experience: ML pipelines, model deployment, performance monitoring and CI/CD.\n Experience with cloud data warehouses, ideally BigQuery and/or Snowflake, and pipeline orchestration with Airflow.\n Experience with real-time or low-latency model serving.\n Experience with promotion, pricing or uplift modeling (e.g. coupon targeting, bundling).\n Customer segmentation and lookalike modeling across several markets.\n Infrastructure as code with Terraform.\n Experience on GCP ML tooling such as Vertex AI.\n Background in retail or e-commerce personalization.\n Fluent English for working in an international team.\n At Accesa We nurture genuine connections, encourage an active lifestyle, and support the development of a healthy mindset. Our benefits programme is inspired by Maslow’s hierarchy of needs and is designed to prioritise your overall wellbeing.\n To live a wholesome experience inside and outside our offices, we need to take care of our overall wellbeing, from the physical aspect to creating a healthy work-life fusion and looking at learning as a lifelong journey and a shared responsibility between our people and our organisation.\n Physical Wellbeing Our wellbeing program includes medical insurance, In-house fitness trainer available remotely and 1 on 1 remote sessions with our Sports and Health Coach focused on nutrition counselling and tailored training plans.\n\n Work-Life Fusion Start with at least 21 vacation days (based on seniority) and earn 1 extra day for each completed year of collaboration - up to 29 days - depending on your tenure in the company and/or industry. 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