{"id":3453518,"url":"https://alion.io/job/experian-lead-machine-learning-engineer","title":"Lead Machine Learning Engineer","company":{"id":3558,"name":"Experian","domain":"experian.com","url":"https://alion.io/company/experian","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"B","score":76,"open_postings":20,"ghost_share":0,"stale_share":0.95,"repost_share":0,"time_to_fill_p50_days":26,"computed_at":"2026-10-31T05:58:55Z"}},"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":["Sofia, Bulgaria"],"countries":["BG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":46000,"max_usd":115000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1286},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ETL/ELT","optional":false},{"name":"FastAPI","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"Synthetic Data","optional":false},{"name":"Agile","optional":true},{"name":"Amazon EC2","optional":true},{"name":"Amazon EKS","optional":true},{"name":"Amazon S3","optional":true},{"name":"Amazon SageMaker","optional":true},{"name":"Apache Kafka","optional":true},{"name":"AWS","optional":true},{"name":"AWS Lambda","optional":true},{"name":"Azure","optional":true},{"name":"Azure Data Factory","optional":true},{"name":"CI/CD","optional":true},{"name":"Databricks","optional":true},{"name":"Delta Lake","optional":true},{"name":"Docker","optional":true},{"name":"Jenkins","optional":true},{"name":"Kubernetes","optional":true},{"name":"Linux","optional":true},{"name":"Microsoft Entra ID","optional":true},{"name":"Okta","optional":true},{"name":"OpenSearch","optional":true},{"name":"pySpark","optional":true},{"name":"Spark","optional":true},{"name":"SQL","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-29T10:25:14Z","employer_posted_date":"2026-10-29","last_verified_at":"2026-11-01T01:28:56Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Experian is a global data and technology company, powering opportunities for people and businesses around the world. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more. Experian invests in people and new advanced technologies to unlock the power of data. We have an amazing team of 25,200 people in 32 countries.\n We are looking for a Lead ML Engineer to provide technical leadership for the development and industrialisation of Scores & Attributes across multiple international markets. You will report to the Head of Analytics Product Development - EMEA and APAC. You will work at the intersection of machine learning, data engineering and platform engineering, helping transform analytical innovation and large-scale data assets into reusable, governed and production-ready capabilities.\nYou will lead the technical journey from data exploration and attribute development through testing, governance, deployment and production execution. An important part of the role will design reusable architectures and integration patterns that allow these capabilities to grow across markets and existing technology environments.\nThis is a hands-on technical leadership role: you will combine architecture and engineering leadership with direct contribution to complex implementations. You will mentor engineers and data scientists and establishing standards that help teams to operate independently.\nWhat you will do:\nML Engineering & Attribute Industrialisation\nLead the design and evolution of capabilities for developing, calculating, testing, governing, deploying and operating data attributes at scale. Build reusable frameworks, tooling and automation that allow attributes to move from experimentation and prototyping into governed, production-ready services. Ensure solutions meet requirements for performance, scalability, reliability and maintainability.\nTechnical Architecture & Platform Integration\nShape the end-to-end technical architecture and engineering patterns supporting the attribute lifecycle - from development in analytical environments through governance and deployment to production execution. Design integration patterns that allow attribute services to work with existing data and bureau platforms while minimising implementation effort for consuming systems. Lead performance and scalability validation and resolve complex cross-platform integration challenges.\nData & Attribute Innovation\nEvaluate new data sources and methodologies, quantifying their incremental predictive and analytical value. Develop and implement approaches for demonstrating the value of Experian data assets and translating them into new attributes and capabilities. Explore technical approaches such as synthetic data to support analytical experimentation, product development and data propositions.\nData Engineering & Asset Onboarding\nDesign reusable approaches for onboarding new data assets and existing attribute libraries, including data ingestion, transformation and ETL pipelines. Establish data-quality controls and engineering practices. Develop approaches for migrating legacy attributes and data processes onto strategic platforms while maintaining business continuity.\nTechnical Leadership & Market Enablement\nProvide hands-on technical leadership for complex implementations and proof-of-concepts across multiple markets. Establish reference architectures, reusable implementation patterns, engineering standards and development practices that can be adopted across teams. Conduct architecture and code reviews, troubleshoot complex technical issues, mentor engineers and data scientists, and help local Analytics and Engineering teams to adopt new capabilities and operate them independently.\n What we're looking for:\nSoftware & ML Engineering\nSoftware engineering fundamentals, including object-oriented programming, data structures, algorithms, design patterns, testing and maintainable software design.\nHands-on experience with Python and its data/analytical ecosystem, such as Pandas and NumPy.\nExperience developing production-grade data or ML applications, rather than only analytical prototypes or notebooks.\nExperience designing APIs and services for exposing data or ML capabilities; experience with FastAPI or similar frameworks is desirable.\nExperience with software development lifecycle, Agile development practices, code review and version control.\nMachine Learning & Data Processing\nExperience with applied machine learning and statistical concepts, including model evaluation, feature engineering, overfitting, cross-validation and appropriate train/validation/test methodologies.\nExperience working with large-scale data processing technologies, like Apache Spark / PySpark and Spark SQL.\nExperience with Databricks or a comparable modern data/ML platform, including data processing, jobs/workflows and ML lifecycle capabilities.\nUnderstanding of modern data technologies such as Delta Lake, distributed data processing and data-quality controls.\nExperience developing reusable features/attributes for ML or analytical applications.\nExperience with ML lifecycle, model/feature tracking, deployment or MLOps practices is desirable.\nCloud & Platform Engineering\nPractical experience with at least one major cloud platform - Amazon Web Services or Azure, and the ability to apply that knowledge across cloud environments.\nUnderstanding of core cloud concepts including compute, object storage, networking, identity and access management, security and managed data services.\nExperience with relevant Amazon Web Services services such as S3, EC2, Lambda, EKS, SageMaker, OpenSearch and managed Kafka services, or equivalents.\nExperience with Azure services such as Blob Storage, Virtual Machines, networking, Microsoft Entra ID, Databricks and Azure Data Factory is desirable.\nYou can design cloud solutions for performance, scalability, reliability, security and cost efficiency.\nDevOps & Production Engineering\nExperience designing and working with CI/CD pipelines; Jenkins experience is desirable.\nExperience with Infrastructure as Code, like Terraform.\nHands-on knowledge of Docker and Kubernetes and container-based deployment patterns.\nComfortable working in Linux environments.\nExperience troubleshooting production systems and identifying performance, scalability and reliability bottlenecks.\nUnderstanding of monitoring, logging and operational practices for production data/ML services.\nArchitecture & Technical Leadership\nYou can translate requirements into technical designs and evaluate architectural trade-offs.\nYou can design reusable solutions and integration patterns that can scale across multiple teams, markets and technology environments.\nExperience leading technical design and architecture reviews and establishing engineering standards.\nYou can review and improve code produced by engineers and data scientists, including performance, maintainability and production readiness.\nProvide hands-on technical leadership while mentoring and enabling other engineers.\nCommunication & Collaboration\nCommunicate complex technical concepts to both technical and non-technical audiences.\nPartner and work across engineering, analytics, product and geographically distributed teams.\nEvaluate alternatives and make technical decisions.\nManage technical and delivery risks.\nDesirable\nExperience with API management platforms like Apigee.\nExperience implementing SSO/identity integrations, such as Okta.\nExperience migrating legacy analytical/data workloads onto modern cloud platforms.\nExperience developing platforms, frameworks or tooling used by Data Science/Analytics teams.\nExperience in regulated, data-intensive environments such as financial services is advantageous.\n What you will get:\nPersonal Development - career pathway for professional growth supported by learning and development programs and unlimited access to online educational training courses, learning materials and books.\nWork environment - excellent work conditions with friendly environment, recognized team spirit, and fun and quality recreation time.\nSocial benefit package including life insurance, food vouchers, additional health insurance, dental coverage, monthly flex allowance, corporate discounts, marriage and childbirth / adoption allowance, Multisport card, Sharesave plan, Employee assistance program, а birthday gift and many other benefits!\nWork-life balance - 25 days paid vacation, 1 additional day off for your birthday and extra 3 paid days for participation in Social responsibility event.\nOpportunity for Flexible working hours and Home Office.Our uniqueness is that we celebrate yours. Experian's people first, inclusive and purpose-driven culture is multi award-winning; World's Best Workplaces™ 2025 (Fortune Global Top 25), Great Place To Work™ in 26 countries to name a few. Check out Experian Life on social or explore our Careers Site to understand why. Experian is also proud to be an Equal Opportunity and Affirmative Action employer. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.\nRecruitment Fraud Awareness - Experian's recruitment process is conducted only through authorised channels. Recruitment communications will only be sent from an @experian.com email address.\nExperian will never ask candidates to make any payment as part of an application, interview, assessment, onboarding, or recruitment process. To apply for roles or verify opportunities, please visit experian.com/careers.\nExperian Careers - Creating a better tomorrow together\nThis is a hybrid remote/in-office role.\nExperian Careers - Creating a better tomorrow together\nFind out what its like to work for Experian by clicking here","description_format":"text","description_chars":9791,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"All levels","optional":false}]},"benefits":["Flexible schedule","Health insurance","Home office","Life insurance"],"hiring_locations":[{"name":"Bulgaria","iso":"BG","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Fraud Detection","Credit Bureaus & Rating Agencies"],"lifecycle":[{"event":"open","at":"2026-10-29T12:31:56Z"}],"visa":[],"liveness":{"score":63,"band":"ok","label":"Likely open","p_open":1,"p_active":0.632,"p_room":1,"age_days":1,"expected_fill_days":26,"reasons":["conf:2","stale_co","velocity","win:early","comp:brand"],"computed_at":"2026-10-31T05:58:55Z"},"pay":null,"html_url":"https://alion.io/job/experian-lead-machine-learning-engineer","json_url":"https://alion.io/job/experian-lead-machine-learning-engineer.json","meta":{"generated_at":"2026-11-01T02:49:13Z","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":4258,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-02T00:00:00Z"}},"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":3558},"rest":"https://alion.io/mcp/rest/get_company?id=3558"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fexperian-lead-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%2Fexperian-lead-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%2Fexperian-lead-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/experian-lead-machine-learning-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fexperian-lead-machine-learning-engineer"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3453518}},{"tool":"search_jobs","arguments":{"company":"experian.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3453518},"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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