{"id":3900003,"url":"https://alion.io/job/iterable-remote-senior-machine-learning-engineer-nova-intelligence","title":"[Remote] Senior Machine Learning Engineer, Nova Intelligence","company":{"id":11773,"name":"Iterable","domain":"iterable.com","url":"https://alion.io/company/iterable","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":90,"open_postings":12,"ghost_share":0.167,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":55,"computed_at":"2026-11-07T05:47:08Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":150000,"max":250000,"currency":"USD","period":"year","gross":null,"usd_annual":250000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"bandit","optional":false},{"name":"Databricks","optional":false},{"name":"Feature Store","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Pulumi","optional":false},{"name":"Python","optional":false},{"name":"Ray","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-11-07T00:12:50Z","employer_posted_date":null,"last_verified_at":"2026-11-07T00:12:50Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Note: The job is a remote job and is open to candidates in USA. Iterable is hiring a Senior Machine Learning Engineer to design and build end-to-end machine learning systems that power intelligence across its product. The role owns model development and production systems, including personalization, recommendation, data pipelines, model serving, and online experimentation.\n\nResponsibilities\nBuild and ship core product ML capabilities, including send-time/frequency optimization, recommendation engines, and campaign personalization\nOwn the full model lifecycle end-to-end: EDA, feature engineering, distributed training, production deployment, latency monitoring, and online experimentation (e.g., multi-armed bandits, ensemble models)\nBuild and scale our data pipelines and serving architectures using Databricks, Spark, AWS, Ray, and Kubernetes\nPartner with Backend and Platform teams to elevate feature serving, improve overall data architecture, and establish engineering standards across the team\nMentor engineers on the team and help set the technical direction for ML at Iterable\nBuilding, evaluating, and integrating new models that add intelligence into our core product\nEnhancing models that optimize send time and frequency of outgoing message campaigns\nDesigning data pipelines that make it easy to implement and test new models\nWorking with platform engineers to enhance our feature- and model-serving architecture\nBenchmarking and improving our multi-armed bandit implementation\nBuilding tools to visualize and debug features and models\n\nSkills\n5+ years of hands-on MLE experience putting complex models into production at scale\nReal experience building, optimizing, and scaling production data pipelines using Databricks\nProven track record of taking deep learning and ensemble architectures from training through optimization to production deployment\nStrong Python and/or Scala skills with an emphasis on readable, modular, and maintainable systems code\nHands-on work with microservice backends, distributed compute (Ray/Spark), and containers (Kubernetes)\nYou care more about serving latency, reliability, and measurable customer impact than novel theoretical architectures\nPrior work on large-scale recommendation systems\nExperience setting up feature stores or model observability tools\nExposure to Infrastructure-as-Code (Terraform, Pulumi)\n\nBenefits\nVariable pay (where applicable)\nEquity\nMedical, dental, vision, and financial benefits\nRemote work in the US\n\nCompany Overview\nIterable is an AI-powered communication platform that improves customer retention with its marketing. It was founded in 2013, and is headquartered in San Francisco, California, USA, with a workforce of 501-1000 employees. Its website is https://www.iterable.com/.\n\nCompany H1B Sponsorship\nIterable has a track record of offering H1B sponsorships, with 17 in 2026, 10 in 2025, 6 in 2024, 12 in 2023, 21 in 2022, 7 in 2021, 5 in 2020. 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