{"id":160012,"url":"https://alion.io/job/pollfish-staff-machine-learning-engineer","title":"Staff Machine Learning Engineer","company":{"id":55561,"name":"Pollfish","domain":"pollfish.com","url":"https://alion.io/company/pollfish","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["El Segundo, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":240000,"max":290000,"currency":"USD","period":"year","gross":null,"usd_annual":290000},"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Apache Kafka","optional":false},{"name":"Machine Learning","optional":false},{"name":"Feature Store","optional":true}],"status":"live","first_seen_at":"2026-07-28T00:00:00Z","employer_posted_date":"2026-09-22","last_verified_at":"2026-10-15T04:13:06Z","board_verified":true,"closed_at":null,"days_open":80,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":80},"description":"Job Description:\nRead this part first:\nThis is a role for someone who wants to solve hard machine learning problems by building production systems that matter.\nWe're looking for aStaff Machine Learning Engineer who loves shipping production ML systems, owning complex technical problems end-to-end, and partnering closely with Product, Data Engineering, and the business to deliver measurable outcomes.\nThis is a deeply hands-on individual contributor role. You'll spend the majority of your time building, deploying, experimenting with, and improving production machine learning systems, not managing people or operating primarily at the architectural strategy level.\nIf you enjoy taking ownership of difficult ML problems, iterating quickly through experimentation, and seeing your work directly improve revenue, marketplace efficiency, and customer experience, this role is for you.\nYou'll build production ML systems for a business serving120M+ registered users that has delivered$2B+ in lifetime rewards, powered by a data platform with50M daily events, 500M daily pipeline records, a 100TB Iceberg lake, and 50 Kafka topics supporting both batch and real-time workflows.\nProdege:\nA cutting-edge marketing and consumer insights platform, Prodege has charted a course of innovation in the evolving technology landscape by helping leading brands, marketers, and agencies uncover the answers to their business questions, acquire new customers, increase revenue, and drive brand loyalty & product adoption. Bolstered by a major investment by Blackstone in Q1 2026, Prodege looks forward to more growth and innovation to empower our partners to gather meaningful, rich insights and better market to their target audiences.\nAs an organization, we go the extra mile to \"Create Rewarding Moments\" every day for our partners, consumers, and team. Come join us today!\nWhat you'll own\nDesign, build, and operate production machine learning systems from development through deployment\n\nProduction models supporting ranking, recommendations, personalization, rewards optimization, ROAS/LTV prediction, and offer optimization\n\nFeature engineering, model training pipelines, online inference, experimentation, monitoring, and continuous improvement\n\nReliable production ML practices including testing, observability, retraining, and model health\n\nTechnical leadership through code reviews, collaboration, and mentoring less experienced engineers\n\nCross-functional partnerships with Product, Data Engineering, Analytics, and Business stakeholders to solve high-impact problems\n\nWhat makes this role exciting\nYou'll work on machine learning problems that directly impact revenue, marketplace efficiency, and customer experience.\n\nYou'll own production systems-not just models-from experimentation through deployment and optimization.\n\nYou'll build on top of a production platform processing50M daily events,500M daily pipeline records, and a 100TB Iceberg lake.\n\nYou'll join a team with an active experimentation culture, shipping ML improvements that quickly reach production.\n\nYou'll have significant ownership while partnering with senior technical leaders to shape the future of ML at Prodege.\n\nYou'll work in an engineering culture embracing AI-assisted development to improve productivity and accelerate experimentation.\n\nWhat you'll do\nDesign, build, deploy, and maintain production machine learning systems.\n\nDevelop scalable ML solutions across ranking, recommendation, personalization, rewards optimization, ROAS/LTV prediction, and experimentation.\n\nImprove feature engineering, model performance, inference latency, and operational reliability.\n\nDesign and analyze offline evaluations and A/B experiments to validate business impact.\n\nPartner with Data Engineering to build reliable data pipelines and feature sets for ML.\n\nContribute to MLOps practices including deployment, monitoring, retraining, and model lifecycle management.\n\nReview code, mentor teammates, and help raise engineering quality across the ML organization.\n\nLeverage AI-assisted development to accelerate research, prototyping, debugging, documentation, and experimentation.\n\nWhat you'll bring (must-haves)\n6+ years of experience in Machine Learning Engineering, Software Engineering, MLOps, or related technical fields.\n\n3+ years building, deploying, and operating production machine learning systems.\n\nStrong experience building production recommendation, ranking, personalization, optimization, or prediction systems.\n\nExperience working in AdTech, MarTech, Growth, Consumer Products, Marketplace platforms, or adjacent domains.\n\nStrong understanding of:\nFeature engineering\n\nOffline and online inference\n\nExperimentation and A/B testing\n\nModel serving\n\nMonitoring and retraining\n\nMLOps best practices\n\nExperience partnering closely with Product, Engineering, and Data teams to deliver measurable business outcomes.\n\nStrong software engineering fundamentals with excellent coding skills.\n\nComfort operating in ambiguous environments while independently driving technical solutions.\n\nDemonstrated ability to mentor engineers and influence technical decisions across teams.\n\nBonus points\nExperience with ROAS optimization, bidding systems, rewards platforms, or monetization models.\n\nExperience with streaming or near-real-time ML systems.\n\nExperience with recommendation engines or personalization at scale.\n\nExperience using feature stores or shared ML infrastructure.\n\nExperience with causal inference, uplift modeling, or counterfactual reasoning.\n\nMaster's degree or PhD in Machine Learning, AI, Computer Science, or a quantitative discipline.\n\nExperience using AI-assisted development tools in software engineering workflows.\n\nPay Transparency:\nThe anticipated base salary range for this position is $240,000 to $290,000. The final salary offered to a successful candidate will be dependent on several factors that may include, but are not limited to; the type and length of experience within the job, type and length of experience within the industry, the type and length of knowledge and skills for the position, education, training, etc. Prodege is a multi-state employer and final compensation within this range could be impacted by work location. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.\nProdege Benefits:\nProdege offers a comprehensive benefits package to US Full-time employees including medical, dental, vision, STD, LTD and basic life insurance. Employees receive flexible PTO, as well as paid sick leave prorated based on hire date. US Employees have eight paid holidays throughout the calendar year.\nEqual Employment Opportunity Statement\nAt Prodege, we are committed to creating a diverse and inclusive environment. We are proud to be an Equal Opportunity Employer and do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other characteristic protected by law. We encourage individuals of all backgrounds to apply.\nFCIHO\nEmployers will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of FCIHO.","description_format":"text","description_chars":7272,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity","Life insurance"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Commerce","Media & Entertainment","Gift Cards & Loyalty Programs"],"lifecycle":[{"event":"open","at":"2026-07-28T00:00:00Z"}],"visa":[],"liveness":{"score":22,"band":"cold","label":"Long shot","p_open":1,"p_active":0.796,"p_room":0.28,"age_days":80,"expected_fill_days":35,"reasons":["conf:25","win:tail","crowd:"],"computed_at":"2026-10-16T05:45:00Z"},"pay":{"stated_usd_annual":290000,"is_top_pay":false},"html_url":"https://alion.io/job/pollfish-staff-machine-learning-engineer","json_url":"https://alion.io/job/pollfish-staff-machine-learning-engineer.json","meta":{"generated_at":"2026-10-16T16:44:22Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":1247,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-17T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":55561},"rest":"https://alion.io/mcp/rest/get_company?id=55561"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fpollfish-staff-machine-learning-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fpollfish-staff-machine-learning-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fpollfish-staff-machine-learning-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/pollfish-staff-machine-learning-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fpollfish-staff-machine-learning-engineer"}]}