{"id":428737,"url":"https://alion.io/job/target-lead-machine-learning-engineer-merchandising-ai-ml-ops","title":"Lead Machine Learning Engineer - Merchandising AI (ML Ops)","company":{"id":3684,"name":"Target","domain":"target.com","url":"https://alion.io/company/target","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":95,"open_postings":327,"ghost_share":0.021,"stale_share":0.306,"repost_share":0.04,"time_to_fill_p50_days":8,"computed_at":"2026-10-30T05:48:23Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Brooklyn Park, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":132000,"max":238000,"currency":"USD","period":"year","gross":null,"usd_annual":238000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Apache Kafka","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Hadoop","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"Spark","optional":false},{"name":"Vertex AI","optional":false}],"status":"live","first_seen_at":"2026-09-06T05:25:51Z","employer_posted_date":"2026-09-06","last_verified_at":"2026-10-30T21:33:20Z","board_verified":true,"closed_at":null,"days_open":54,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":54},"description":"The pay range is $132,000.00 - $238,000.00Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits.\nJOIN US AS A LEAD MACHINE LEARNING ENGINEER - MERCHANDISING AI\nAbout Us:\nWorking at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here.\nA role with Target Data Sciences means the chance to help develop and manage state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale. Whether you join our Applied Data Sciences or Machine Learning teams, you’ll be challenged to harness Target’s impressive data breadth to build the algorithms that power solutions our partners in Digital Marketing, Supply Chain Optimization, Advanced AI, Search and Personalization rely on. Every Scientist on Target’s Data Sciences team can expect modeling and data science, software/product development of highly performant code for model performance at scale.\nAs the Lead Machine Learning Engineer - Merchandising, you will join a Data Sciences team responsible for creating and optimizing the data and models used to build a world-class merchandising product. You will play a crucial role in designing, implementing, and optimizing production machine learning solutions. We will also expect you to understand best practice software design, participate in code reviews, and create a maintainable well-tested codebase with relevant documentation. At an organizational level, you may conduct training sessions, present work to technical and non-technical peers/leaders, build knowledge on business priorities/strategic goals and leverage this knowledge while building requirements and solutions for each business need.\nCore responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs.\nAbout you:\n4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience\nMS in Computer Science, Applied Mathematics, Statistics, Physics or equivalent work or industry experience in applied machine learning\n5 plus years of experience in end-to-end machine learning application development, including data pipelining, model optimization, deployment and API design\nExtensive experience with applied machine learning frameworks and the ability to developing highly distributed machine learning systems at scale \nHighly proficient in Python programming\nStrong understanding of CI/CD practices for machine learning systems and ML Ops principles\nExtensive experience with Google Cloud’s Vertex AI and/or the broader cloud-based ML ecosystem \nDemonstrated knowledge of various testing frameworks and containerization like Docker and Kubernetes\nLead the development of agentic AI solutions that connect data, tools, APIs and business rules into end-to-end decisioning workflows\nDemonstrated experience in REST API design and development\nExtensive understanding of Big Data technologies including Hadoop, Spark and Kafka\nProven ability to collaborate with data scientists, software engineers and product managers to deliver scalable machine learning solutions\nExcellent communication skills with an ability to tell data-driven stories through visualizations and narratives \nAbility to mentor engineers and help establish engineering standards, architecture patterns, and best practices for AI/ML and cloud-native development.\nSelf-driven, results-oriented and able to meet tight deadlines \nMotivated team player who thrives in a collaborative global environment\nThis position may be considered for a Remote or Hybrid (known internally at Target as \"Flex for Your Day\") work arrangement based on Target's needs. A Remote work arrangement means the team member works full-time from home or an alternate location that's not a Target location, does not have a desk at a Target location and may travel to HQ up to 4 times a year. A Hybrid/Flex for Your Day work arrangement means the team member's core role may be performed either remote or onsite at a Target location depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by Target.Benefits Eligibility\nPlease paste this url into your preferred browser to learn about benefits eligibility for this role: https://tgt.biz/BenefitsForYou_EAmericans with Disabilities Act (ADA)\nIn compliance with state and federal laws, Target will make reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, please reach out to -accommodation-relatedrequests, such as application follow-ups or technical issues, will not be addressed through this channel.","description_format":"text","description_chars":5679,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":true},"security_clearance":false,"languages":[]},"benefits":["Life insurance"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","E-commerce Platforms","Online Groceries"],"lifecycle":[{"event":"open","at":"2026-09-06T05:25:51Z"}],"visa":[],"liveness":{"score":11,"band":"cold","label":"Long shot","p_open":1,"p_active":0.389,"p_room":0.28,"age_days":54,"expected_fill_days":8,"reasons":["conf:0","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-30T05:48:23Z"},"pay":{"stated_usd_annual":238000,"is_top_pay":true},"html_url":"https://alion.io/job/target-lead-machine-learning-engineer-merchandising-ai-ml-ops","json_url":"https://alion.io/job/target-lead-machine-learning-engineer-merchandising-ai-ml-ops.json","meta":{"generated_at":"2026-10-30T23:27:56Z","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":14767,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-31T00:00:00Z"}},"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":3684},"rest":"https://alion.io/mcp/rest/get_company?id=3684"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Ftarget-lead-machine-learning-engineer-merchandising-ai-ml-ops"},{"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%2Ftarget-lead-machine-learning-engineer-merchandising-ai-ml-ops"},{"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%2Ftarget-lead-machine-learning-engineer-merchandising-ai-ml-ops"},{"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/target-lead-machine-learning-engineer-merchandising-ai-ml-ops\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Ftarget-lead-machine-learning-engineer-merchandising-ai-ml-ops"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":428737}},{"tool":"search_jobs","arguments":{"company":"target.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":428737},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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