{"id":4326688,"url":"https://alion.io/job/true-talent-solutions-partners-senior-data-machine-learning-engineer-3","title":"Senior Data & Machine Learning Engineer","company":{"id":4415660,"name":"True Talent Solutions Partners","domain":"truetalentsolutionspartners.com","url":"https://alion.io/company/true-talent-solutions-partners","size_band":"11-50","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"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":"explicit","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":200000,"max":300000,"currency":"USD","period":"year","gross":null,"usd_annual":300000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"dbt","optional":false},{"name":"Embeddings","optional":false},{"name":"ETL/ELT","optional":false},{"name":"FAISS","optional":false},{"name":"Machine Learning","optional":false},{"name":"Milvus","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"Recommender Systems","optional":false},{"name":"SQL","optional":false},{"name":"PostgreSQL","optional":true}],"status":"live","first_seen_at":"2026-11-15T01:14:57Z","employer_posted_date":"2026-11-15","last_verified_at":"2026-11-15T01:36:59Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"About the Role\nJoin a small team building AI-powered consumer modeling and personalized advertising technology. You will own the recommendation and matching stack end to end, from model development through production serving, helping improve relevance and performance for advertisers, publishers, and subscribers.\nWhat You'll Do\nBuild retrieval, ranking, and re-ranking systems that match ads with recipients.\n\nDevelop embedding and vector-search infrastructure for real-time ad selection.\n\nOptimize ranking across click-through rate, advertiser return, publisher revenue, and subscriber relevance.\n\nOwn feature storage and the full serving path, including offline training, online inference, and pipeline health.\n\nApply large language models and foundation models to subscriber tagging, content understanding, and user modeling.\n\nLead initiatives from prototype to production, including online learning, feedback loops, ETL/ELT pipelines, and warehouse transformations.\n\nBuild dashboards and automated scorecards to track performance and key metrics.\n\nWork with company leadership and engineering to prioritize and scale the recommendation system.\n\nHelp shape the future of the ML team and grow into a leadership role.\n\nWhat We're Looking For\n5 to 16 years of experience in production machine learning or data engineering, including at least 3 years working with recommendation, ranking, or advertising systems.\n\nExperience building and shipping production recommendation or matching systems across candidate generation, ranking, embedding-based retrieval, serving, and evaluation.\n\nBackground building advertising recommender models, such as ad ranking, click-through or conversion prediction, or ad matching.\n\nHands-on experience with embeddings and real-time vector search tools such as FAISS, Milvus, Pinecone, pgvector, or similar.\n\nExperience building and maintaining data pipelines and transformation layers using SQL and dbt or comparable tools.\n\nAbility to independently investigate data, develop hypotheses, and run experiments.\n\nMust be authorized to work in the United States without visa sponsorship.\n\nEarly-stage startup, founder, advanced degree, or ML team-building experience is a plus.\n\nCompensation & Benefits\nBase salary: $200,000 to $300,000 annually. 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