{"id":1809411,"url":"https://alion.io/job/chase-uk-software-engineer-iii-ml-model-delivery","title":"Software Engineer III - ML Model Delivery","company":{"id":1854819,"name":"Chase UK","domain":"chase.co.uk","url":"https://alion.io/company/chase-co-uk","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":100,"open_postings":273,"ghost_share":0.007,"stale_share":0,"repost_share":0.099,"time_to_fill_p50_days":3,"computed_at":"2026-10-05T05:45:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Plano, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":105000,"max_usd":210000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":383},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon ECS","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"Databricks","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Terraform","optional":false},{"name":"Docker","optional":true},{"name":"Feature Store","optional":true},{"name":"Kubernetes","optional":true},{"name":"LLM","optional":true},{"name":"RAG","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-09-30T23:07:57Z","employer_posted_date":"2026-09-30","last_verified_at":"2026-10-06T01:48:03Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.\nAs a Software Engineer III at JPMorgan Chase within the Consumer and Community Banking - Risk Technology Portfolio team, you will be part of an agile team that builds and delivers trusted technology products in a secure, stable, and scalable way. You will take ownership of technical deliverables, contribute to design decisions, and work across cloud, data, and machine learning domains to solve real business problems.\nJob Responsibilities:\nDesign, build, and maintain platform components that support end-to-end ML model lifecycle - from development and training to deployment and monitoring\nApplies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation\nLeverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards.\nDevelop and maintain data and feature pipelines that feed ML models in production\nBuild and manage cloud-based infrastructure on AWS (including Databricks, EMR, ECS, and S3) to support model training and serving workloads\nAutomate model deployment, testing, and release processes within the SDLC/MLOps toolchain\nSupport migration of legacy ML workloads to cloud-native, scalable platforms with zero downtime\nMonitor platform health and model serving infrastructure; identify and resolve performance and stability issues\nApply AI-assisted development tools and best practices to improve code quality and delivery speed\nCollaborate with data scientists and model developers to understand requirements and translate them into reliable platform capabilities\nContribute to a team culture of diversity, inclusion, and continuous improvement\nRequired Qualifications, Capabilities, and Skills:\nFormal training or certification in software engineering and 3+ years of applied experience\nHands-on experience building and maintaining production data or ML pipelines\nHands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs.\nUnderstanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.\nProficiency in Python and experience with ML libraries and frameworks (Pandas, NumPy, Scikit-learn, etc.)\nWorking knowledge of cloud platforms, particularly AWS, and cloud-native development patterns\nPractical experience with infrastructure-as-code and deployment automation (Terraform preferred)\nAbility to work independently on platform problems with moderate oversight\nPreferred Qualifications, Capabilities, and Skills:\nExperience with Databricks for model training and data pipeline development\nFamiliarity with MLOps practices - 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