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Agoda

<div>
 
 About Agoda
 
 
 
 At Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to explore the world.
 
 
 Today, we are part of Booking Holdings [NASDAQ: BKNG], with a diverse team of over 7,000 people from 90 countries, working together in offices around the globe. Every day, we connect people to destinations and experiences, with our great deals across our millions of hotels and holiday properties, flights, and experiences worldwide.
 
 
 No two days are the same at Agoda. Data and technology are at the heart of our culture, fueling our curiosity and innovation. If you&rsquo;re ready to begin your best journey and help build travel for the world, join us.
 
 
 
 Get to Know Our Team
 
 
 
 The Engineering department oversees all Agoda&rsquo;s ML and software related requirements. Our goal is to enable and increase Agoda&rsquo;s business through creative approaches and the implementation of powerful resources such as operational and analytical databases, ML driven solutions, queue systems and data monitoring tools. We hire the brightest minds from around the world to take on this challenge and equip them with the knowledge and tools that contribute to their personal growth and success while supporting our company&rsquo;s culture of diversity and experimentation. The role the engineering team plays at Agoda is critical as business users, product managers, and many others rely on us to empower their decision making. We are equally dedicated to our customers by improving their search experience with faster results and protecting them from any fraudulent activities. Data is interesting only when you have enough of it, and we have plenty. This is what drives up the challenge as part of the ML engineering squad, but also the reward. We work across structured and non-structured data at scale. For example, our current ML models process millions of images every day to try and enhance the experience that our users get from our app.
 
 
 
 Why Agoda Engineering Team (ML role)?
 
 
 
 Our engineering teams are at the intersection of business analytics, ml engineering, data warehousing and software engineering. Our job involves dealing with distributed systems, stream processing, ml modeling and computation at tens of PB Scale. We focus on software engineering related to data replication, storage, centralized computation, and Data API&rsquo;s. By providing our users with ML products/tools, shared frameworks, and ML services, we enable our company to validate strategic decisions, make smarter choices, and react to the fast-changing world. We are a small but passionate team with people from different nationalities working together on a single goal.
 
 
 
 In this Role, you will get to:
 
 
 
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 Lead the team technically in improving scalability, stability, accuracy, speed and efficiency of our existing ML systems and processes. Build, administer and scale ML processing pipelines.
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 Be comfortable navigating the following technology stack: Python3, Scala Spark, scripting (Bash/Python), Hadoop, SQL, S3 etc.
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 Should be able to understand internals of ML models such as LightGBM, Random Forest, CNN, Regression models, etc
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 Design, build, test and deploy new libraries, frameworks or full systems for our core systems while keeping to the highest standards of testing and code quality.
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 Work with experienced engineers and product owners to identify and build tools to automate many large-scale data management / analysis tasks.
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 We believe in end-to-end ownership; this role will involve taking and building systems that enable us to deliver ML models to production at a scale.
 
 
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 </ul>
 
 What You&rsquo;ll need to Succeed:
 
 
 
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 Bachelor&rsquo;s degree in computer science /information systems/engineering/related field 6+ years of experience in software engineering with a minimum of 4+ years in ML
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 Expert in SQL, Python3, and JVM based programming language &ndash; ie, Java or Scala
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 Expert in software design/design patterns, functional programming and object-oriented programming.
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 Analytical problem-solving capabilities &amp; experience. A strong engineering driven mindset will be required to succeed in this role.
 
 
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 It&rsquo;s great if you have:
 
 
 
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 Good understanding of Hadoop ecosystems and Big Data architecture and techologies
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 Experience working with Open-source products
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 Experience with Scala development
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 Working in an agile environment using test driven methodologies
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 Systems administration skills in Linux
 
 
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 </ul>
 
 Benefits
 
 
 
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 Hybrid Working Model
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 WFH Set Up Allowance
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 30 Days of Remote Working from anywhere globally every year
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 Employee discount for accommodation globally
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 Global team of 90+ nationalities
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 40+ offices and 25+ countries
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 Annual CSR / Volunteer Time off
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 Benevity Subscription for employee donations
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 Volunteering opportunities globally
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 Free Headspace subscription
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 Free Odilo &amp; Udemy subscriptions
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 Access to Employee Assistance Program (third party for personal and workplace support)
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 Enhanced Parental Leave
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 Life, TPD &amp; Accident Insurance
 
 
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 </ul>
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 Please review our Hiring Process Guidelines before your interview &mdash; click here to learn how interviewing at Agoda works.
 
 
 
 Discover More About Working At Agoda
 
 
 
 <ul>
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 Agoda Careers https://careersatagoda.com
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 Facebook https://www.facebook.com/agodacareers/
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 LinkedIn https://www.linkedin.com/company/agoda
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 YouTube https://www.youtube.com/agodalife
 
 
 </li>
 </ul>
 
 Equal Opportunity Employer
 
 
 
 At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person&rsquo;s merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics.
 
 
 We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our privacy policy.
 
 
 
 Disclaimer
 
 
 
 We do not accept any terms or conditions, nor do we recognize any agency&rsquo;s representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee.
 
 
</div>

Senior/Staff Machine Learning Engineer - Bidding (Bangkok based, relocation provided)

Salla

<div>
 We're looking for a Senior Data Analyst/ Analytics Engineer to own data and analytics across our Gen AI and Recommendation Systems work. It's a hybrid role: you'll own the centralized reporting that turns data into decisions and build the pipelines and data models that feed it &mdash; defining the right metrics for each product we ship rather than waiting on others to prepare your data. For Recommendation Systems, you'll bring enough ML understanding to engineer the right features and evaluation metrics, partnering closely with Data Scientists, ML Engineers, Product, and Backend teams.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
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 Pipeline Architecture &amp; Development: Build and maintain scalable, fault-tolerant batch and streaming pipelines that serve analytical and ML use cases
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 Centralized Reporting &amp; Metrics: Define the key metrics for each product we ship and build rock-solid centralized reporting around them, surfacing the trends and insights that matter
 </li>
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 Data Modeling: Design and own multi-layer data models (staging to feature-ready marts) that stay consistent and performant across ML models, dashboards, and APIs, handling schema changes cleanly
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 Feature Store &amp; ML Data Flows: Engineer the data flows that populate and update our ML Feature Store (and graph data where relevant) with the availability and low latency recommendation models need
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 Experimentation &amp; A/B Testing: Build the pipelines and metrics frameworks behind A/B testing &mdash; experiment schemas, assignment logging, and reliable metric computation for statistically sound results
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 ClickHouse Mastery: Own ClickHouse as the domain expert &mdash; schema design, performance tuning, and fast queries for experiment aggregation and feature serving
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 Streaming &amp; CDC: Implement Change Data Capture (CDC) and event-driven flows (e.g. Apache Kafka) to keep data fresh where reporting and recommendations need it
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 Orchestration &amp; Automation: Build and manage workflows with modern orchestration tools (e.g. Mage AI, Airflow, Prefect) for reliable delivery and dependency management
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 ML-Aware Support: Define and interpret the right offline and online ranking metrics, and engineer the features the models actually need
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 Cross-Functional Collaboration: Partner with Data Scientists, ML Engineers, Product, and Backend to turn data requirements into production pipelines and actionable ML features
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
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 Experience: 4+ years as a Data/Analytics Engineer building data systems for analytics and ML
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 Programming: Expert Python and advanced SQL
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 BI &amp; Visualization: Strong BI/visualization skills (e.g. Looker, Tableau) and good intuition for which metrics matter and how to present them
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 Pipelines &amp; Orchestration: Hands-on building pipelines with modern orchestration (Mage AI, Airflow, Prefect) &mdash; you build your own data, not just consume it
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 Data Warehouse / ClickHouse: Deep production experience with ClickHouse (or BigQuery, Snowflake, or similar)
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 Data Modeling: Hands-on multi-layer modeling (raw, staging, marts) using Kimball, Data Vault, or OBT patterns
 </li>
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 Experimentation &amp; A/B Testing: Solid grasp of experimentation frameworks &mdash; assignment, holdouts, metric pipelines, variance reduction
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 <li>
 ML Exposure: Good grasp of the ML lifecycle &mdash; how models consume data, how Feature Stores work (e.g. Feast, Hopsworks), and how to engineer features at scale, plus enough ranking-metric knowledge to support Recommendation Systems
 
 
 </li>
 </ul>
 
 Nice to have:
 
 
 
 <ul>
 <li>
 DBT for modeling and transformation
 </li>
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 Building or integrating A/B platforms (e.g. Statsig, Optimizely, GrowthBook, or custom)
 </li>
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 Apache Kafka and CDC tools (e.g. Debezium, Maxwell)
 </li>
 <li>
 Graph Databases (e.g. Dgraph, Neo4j, Amazon Neptune) and structuring data for them
 </li>
 <li>
 JavaScript or Go
 </li>
 </ul>
</div>

Senior Data Analyst - AI (Gen AI & Recommendation Systems)

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2 jobs In Mecca

Senior/Staff Machine Learning Engineer - Bidding (Bangkok based, relocation provided)

Senior Data Analyst - AI (Gen AI & Recommendation Systems)