{"id":2580726,"url":"https://alion.io/job/newbridge-alliance-machine-learning-engineer-ops","title":"Machine Learning Engineer (Ops)","company":{"id":4423579,"name":"Newbridge Alliance Pte","domain":"newbridgealliance.com","url":"https://alion.io/company/newbridgealliance","size_band":"51-200","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Manatal","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":60000,"max_usd":130000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":26},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Alation","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"Azure","optional":false},{"name":"BigQuery","optional":false},{"name":"CI/CD","optional":false},{"name":"Collibra","optional":false},{"name":"dbt","optional":false},{"name":"Docker","optional":false},{"name":"Feast","optional":false},{"name":"Feature Store","optional":false},{"name":"GCP","optional":false},{"name":"GDPR","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Great Expectations","optional":false},{"name":"Informatica","optional":false},{"name":"ISO 42001","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"MLFlow","optional":false},{"name":"NIST AI RMF","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Vertex AI","optional":false},{"name":"Evidently AI","optional":true},{"name":"Hallucination","optional":true},{"name":"LLM","optional":true},{"name":"RAG","optional":true}],"status":"live","first_seen_at":"2026-10-15T01:52:06Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-15T06:12:41Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Role Overview\nYou will build trusted data and trusted AI - ensuring our clients data is accurate, compliant, and governed, and our ML models are reproducible, monitored, and responsibly deployed to production.\nThis role is 50% Data Governance, 50% MLOps / ML Platform Governance.\nKey Responsibilities\nA. Data Governance (50%)\nFramework & Stewardship\nDesign and run enterprise Data Governance framework, policies, and RACI for data owners/stewards\nEstablish Data Governance Council and operating model across Product, Engineering, Analytics, and Business\nDefine KPIs: catalog coverage, data quality score, policy adherence\n\nData Quality, Catalog & Lineage\nImplement business glossary, data catalog (Collibra / Alation / Purview / DataHub), and end-to-end lineage\nDefine and monitor data quality rules, SLAs, anomaly detection for critical domains (Customer, Product, Transaction)\nManage data classification, PII/PHI tagging, retention, and access control policies\n\nCompliance & Security\nEnsure compliance with PDPA, GDPR, CCPA and internal security standards\nPartner with DPO / Legal / GRC for consent, purpose limitation, anonymization, and audit readiness\nOwn access governance - RBAC/ABAC for data warehouse, lakehouse, and feature store\n\nB. MLOps & AI Governance (50%)\nML Lifecycle & Platform\nOwn MLOps best practices: from feature engineering -> training -> validation -> deployment -> monitoring\nBuild and manage ML platform components: Feature Store (Feast / Tecton / SageMaker Feature Store), Model Registry (MLflow / SageMaker Model Registry), Experiment Tracking\nStandardize CI/CD/CT for ML with Git, Docker, Airflow / Kubeflow / SageMaker Pipelines\n\nModel Governance & Responsible AI\nImplement Model Governance: model inventory, model cards, lineage (data -> features -> model -> endpoint), approval workflows\nEnforce responsible AI checks: bias/fairness, explainability, drift, and reproducibility\nAlign with AI Governance frameworks: NIST AI RMF, Singapore Model AI Governance Framework, AI Verify, ISO 42001\n\nMonitoring & Operations\nImplement monitoring for data drift, concept drift, feature skew, and model performance degradation\nSet up alerting, automated retraining triggers, and rollback strategies\nOptimize model serving costs, latency, and scalability on AWS / Azure / GCP\n\nTech Stack You Will Work With\nGovernance: Collibra, Alation, Purview, Informatica, DataHub, AWS Glue, Apache Atlas\nData: Snowflake / BigQuery / Redshift, S3 / GCS, dbt, Airflow, Spark, Kafka\nMLOps: MLflow, Kubeflow, SageMaker, Vertex AI, Feast, Evidently, Great Expectations, Docker, Kubernetes, GitHub Actions\nLanguages: Python (must), SQL (must), PySpark\nRequirements\n6-10 years total in Data Engineering / Data Governance / MLOps\nAt least 2+ years owning data governance and at least 2+ years deploying ML models to production\nStrong hands-on with DAMA-DMBOK and MLOps principles\nProven experience setting up Model Registry, Feature Store, and monitoring for production ML systems\nDeep understanding of PDPA/GDPR, data security, and AI risk\nExcellent stakeholder management - you can talk to both Data Scientists and Risk/Legal\nNice-to-Have\nCDMP, AWS Certified ML Specialty, or similar\nExperience with LLM / GenAI governance - prompt logging, RAG governance, hallucination monitoring\nExperience with Great Expectations, Monte Carlo, Evidently AI\nIndustry experience in Media, FinTech, or other regulated industry\nWhat Success Looks Like in 12 Months\nTop 5 data domains governed with SLAs and quality monitoring >95%\n100% of production models registered with model cards, lineage, and approval workflow\nAutomated drift detection live for all critical models with Data catalog adoption >80% and zero compliance audit findings","description_format":"text","description_chars":3721,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-15T01:52:06Z"}],"visa":[],"liveness":{"score":52,"band":"ok","label":"Likely open","p_open":1,"p_active":0.516,"p_room":1,"age_days":0,"expected_fill_days":38,"reasons":["conf:3","agency","win:early"],"computed_at":"2026-10-15T05:46:00Z"},"pay":null,"html_url":"https://alion.io/job/newbridge-alliance-machine-learning-engineer-ops","json_url":"https://alion.io/job/newbridge-alliance-machine-learning-engineer-ops.json","meta":{"generated_at":"2026-10-15T07:06:56Z","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":10742,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-16T00:00:00Z"}},"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":4423579},"rest":"https://alion.io/mcp/rest/get_company?id=4423579"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fnewbridge-alliance-machine-learning-engineer-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%2Fnewbridge-alliance-machine-learning-engineer-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%2Fnewbridge-alliance-machine-learning-engineer-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/newbridge-alliance-machine-learning-engineer-ops\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fnewbridge-alliance-machine-learning-engineer-ops"}]}