Diego Marinho de Oliveira

Senior Engineering Manager / Principal AI · Production Agentic AI, Search & Recommender Platforms

Melbourne, Victoria, Australia dmarinho.ai@gmail.com linkedin.com/in/dmztheone github.com/dmoliveira

Executive Summary

AI/ML leader with 10+ years leading production AI products and platforms across search, recommendations and agentic experiences in Oceania, Asia and South America.
Built and led data science and machine learning engineering teams, including 12 people across up to three teams, from strategy through reliable customer impact.
Built the production agent platform behind customer-facing AI search and conversational experiences, standardizing orchestration, evaluation, observability, guardrails and cost control.
Delivered measurable impact through 150+ online experiments, multi-market platform rollouts and customer-facing AI launches.

Selected Impact

Unified recommender systems across 8+ SEEK markets in Asia and ANZ, delivering 5–10x gains and a 12x peak uplift in one Asia market.
Launched the RED brand’s first GenAI property search in under one month.
Delivered real-time multimodal computer vision extraction of 45+ property attributes.
Launched multilingual personalized AI search for JobsDB in Hong Kong with a 14% improvement on a core metric.
Served millions of users with real-time recommendations across homepage, email and push notifications.

Professional Experience

Senior Engineering Manager / Principal AI — Machine Learning, REA Group

Melbourne, Australia · April 2024 — Present

Global digital property business; home to realestate.com.au.

Built and led data science and machine learning engineering teams across production agentic AI, AI search and personalization: 12 people across up to three teams.
Launched the RED brand’s first GenAI property search end to end in under one month to validate conversational discovery in production.
Built the production agent platform behind AI search and conversational experiences, including orchestration, observability, evaluation, guardrails and cost controls.
Delivered real-time multimodal computer vision attribute extraction in production, covering 45+ property attributes.
Established GenAI observability for real-time monitoring, evaluation, tracing and operational debugging.
Owned GenAI economics and latency through prompt caching, token-level cost tracking and performance controls, keeping production responses within 1–2 second service-level targets.
Owned AI governance controls across rate limiting, evaluation, monitoring, guardrails and security validation, including a completed penetration test.

AI / Data Scientist Manager; Senior Data Scientist; Data Scientist — SEEK

Melbourne, Australia · March 2017 — April 2024

Online employment marketplace across Australia, New Zealand and six Asian markets.

Built and led a global data science team of approximately 10 while hiring across multiple AI teams.
Led the recommender platform transformation across multiple markets, producing 5–10x gains and a 12x peak uplift in one Asia market.
Delivered a unified recommender platform across 8+ markets in Asia and ANZ.
Launched multilingual personalized AI search for JobsDB in Hong Kong with a 14% improvement on a core metric.
Used 150+ online experiments to de-risk search, ranking and personalization decisions and compound gains on core marketplace metrics.
Served millions of users with real-time recommendations across homepage, email and push notifications.
Used offline evaluation, online testing and load tests to meet approximately 500 ms recommendation targets.

Lead Data Scientist — Catho

São Paulo, Brazil · July 2015 — February 2017

Brazilian technology and online recruitment platform.

Built candidate recommendation systems that delivered more than 115% uplift on core marketplace metrics.
Delivered hybrid recommenders combining collaborative filtering and content-based methods.
Applied NLP and machine learning to hiring-marketplace challenges at scale.

Earlier Engineering and Machine Learning Roles

2009 — 2015

Machine Learning Engineer, RBS Group / Appus; Machine Learning Specialist, Zunnit Technologies; Software Engineer, Vale Mining / Visagio; Software Analyst, TOTVS.

Selected AI Systems

Production Agent Platform, REA: shared orchestration, evaluation, observability, guardrails and cost governance behind customer-facing AI search and conversational experiences.
GenAI Property Search, REA: production natural-language property discovery launched in under one month.
Multimodal Attribute Extraction, REA: real-time computer vision and multimodal transformer inference covering 45+ property attributes.
Unified Recommender Platform, SEEK: 8+ markets, 5–10x gains and a 12x peak uplift in one Asia market.
Personalized AI Search, SEEK JobsDB: 14% improvement on a core metric in Hong Kong.

Capabilities

Leadership: organization design, hiring, mentoring, executive OKRs and cross-functional product strategy.

Agentic AI and GenAI: AI agents, multi-agent orchestration, tool calling, stateful workflows, memory, structured outputs, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), embeddings and fine-tuning.

AI Search and Recommendations: information retrieval, hybrid and semantic search, search relevance, ranking and reranking, learning-to-rank, sequential recommenders and personalization.

Evaluation, Safety and MLOps: agent evaluation, continuous evaluation, A/B testing, observability, tracing, guardrails, AI governance, latency and cost control.

Cloud and Platforms: GCP, Vertex AI, AWS, BigQuery, Kubernetes, Terraform, CI/CD and data pipelines.

Machine Learning: PyTorch, TensorFlow, scikit-learn, XGBoost, LightGBM, CatBoost, Spark, transformers, embeddings, matrix factorization and clustering.

Languages and Datastores: Python, R, Julia, Java, Scala, Go, C/C++; SQL, Solr, OpenSearch, Elasticsearch, Redis, MongoDB, PostgreSQL and vector databases.

Education

M.Sc. Computer Science, Universidade Federal de Minas Gerais (2010–2012).
B.Sc. Computer Science, Pontifícia Universidade Católica de Minas Gerais (2006–2009).

Awards

Winner, REA Hackdays — Hack it Forward Award for Community, Social & Environmental Good (2024).
Top performer, Databricks Gen-AI Australia Cup (2023).
Winner, SEEK International Volponi Award (2017).
Student Medal for Excellence, B.Sc. Computer Science (2009).

Selected Publications

Imbalanced Data Sparsity as a Source of Unfair Bias in Collaborative Filtering (RecSys 2022).
Offline Evaluation Standards for Recommender Systems (RecSys 2021).
FS-NER: a lightweight filter-stream approach to named entity recognition on twitter data (WWW ’13 Companion).
Applying neural networks to determine the socio-environmental factors responsible for potable water consumption (SMC 2010).
The usage of Artificial Neural Networks in the classification and forecast of potable water consumption (IJCNN 2009).

Languages

English (fluent), Portuguese (native), Spanish (basic).