I'm a Machine Learning Engineer

Scalable ETL Pipelines | MLOps | AWS

Hello! I'm Raymond Lam, a Machine Learning Engineer specializing in building scalable ETL pipelines and robust ML systems on AWS.

My journey into Machine Learning began as a self-taught programmer, where I immersed myself in the world of Python, data analytics, machine learning, and deep learning through online platforms like DataCamp and Coursera. My professional career started at Hong Kong Productivity Council (HKPC) where I developed Anomaly Detection for industrial sensors at a smart manufacturing centre. Few years later, in Orient Overseas Container Line (OOCL), I had the incredible opportunities to truly shape my expertise in MLOps by participating in diverse ML projects like LLMs, NLP, recommendation engine, and Time-series forecasting. After several rewarding years of growth and accomplishment in Hong Kong, I made an exciting move to Toronto, seeking new challenges and growth opportunities beyond my comfort zone.

Finding a job in Canada is not as easy as in Hong Kong. In this blog, I would like to share the lessons I learnt along my journey. If you are a job seeker in Canada, a fellow data science enthusiast, or someone just beginning your journey, I hope my story encourages you to persist, stay curious, and keep believing in your abilities.

Keep your head up, stay motivated, and never stop learning.
As Steve Jobs famously said, "Stay Hungry, Stay Foolish".

喺度搵工
全是運氣
To be precise,
係睇你同interviewer岩唔岩傾
佢like唔like你
所以多d small talk 係有幫助,好似平時傾計吹兩嘴就ok

比d stats 比大家:
Duration: 6months
Applied: 840
First in / tech assessment: 9
Rejected: 1
Ghosted / not yet responsed: 6
Second in: 2
Final in: 1
Offer: 1

喺度搵工有幾難搵,相信有試過既你大家都會知,所以負面野唔多講,threads 搵一下大把
喺度想share 下the lessons I have learnt during this job seeking journey.

Resume-wise:
Resume我都大改過好多次
由一開頭一份好廢既CV
變到依家一份看似好勁既CV
點樣執自己份resume 上網搵大把人已經有教,喺度唔講
但想講一句就係
唔好以為依家份CV已經好好,其實點樣都有得執得更好,不斷改,不斷進步
我自己就分兩份resume,一份AWS,一份Azure,分完之後有interview rate提高左

Learning-wise:
  • 我自己有睇晒statquest 所有關於Machine Learning 既片,黎reinforce 自己ML knowledge,都幾有用,interview 真係會問到好多基本ML 野
  • AWS Certified Machine Learning Engineer - Associate 呢個course 都好值得讀,會學到好多AWS infrastructure 野,對成個ML system點build你會有更全面既睇法,build個ML system有咩considerations? 學完之後你就會識system design,同埋有interview rate提高左

搵工-wise:
  • 有工就9 apply得,apply 工都幾嘥時間,會令到你無時間學野,chatgpt會幫到你(我自己用poe,一定要課金,無得慳)
  • Apply 100份都唔夠1個referral 黎,厚面皮d 去r 多d referral,Linkedin 9 connect 人去r referral
  • Leetcode唔係間間公司都會考,但建議都要操,先溫data structure and algo on geeksforgeeks,再操晒neetcode果150題,咁你leetcode就應該做到大概200題,能夠搞得掂medium題目,咁u will be fine,得閒重溫下就ok.
  • Behaviour questions 要準備定d 基本野,strengths, weeknesses果d 行野,其他吹水
  • Your Projects: 呢個重要,你做過既project,可能太耐你會唔記得左d details。我自己就有份notes for each project,要做到interviewer問到所有project details 你都會識,即刻答到。chatgpt 會幫到你,叫chatgpt 去generate some missing project details. 總之你個project details要make sense
  • System Design 我自己無乜經驗,應該要in FAANG先會考到

我個working environment就好似右手邊張相咁,貼晒memo紙,去排果日既working priority
成功方法有好多,我呢一套只係其中一套比大家做參考
以上經驗希望幫到你,令你花少d 時間去撞板

最後亦係最重要,希望搵緊工既你,繼續保持希望!揸緊個信念!
加拿大搵工地獄 image

Scalable ETL Pipelines

SQL, Scala, Hadoop, Hive, Spark, Argo Workflow

MLOps

EDA, Data Preprocess, Model Training Pipeline, CI/CD, Inference Pipeline, Model Monitoring

AWS

Kinesis, Glue, Lambda, DynamoDB, S3, EC2, ECS, EKS, SageMaker, CloudFormation, CDK, Infrastructure as code, CloudWatch, CodePipeline

Projects

Market News Summarization (LLMs) Cargo Demand Forecasting (Time-series Forecasting) Email Classification (NLP Text Classification) Search Recommendation (Recommendation Engine) Industry 4.0 (Anomaly Detection)

 

City University of Hong Kong

Graduated with a bachelor degree in Mechatronics Engineering with First Class Honors

01-07-2014
 

Alco Electronics Limited

Mechanical Engineer Trainee: Product development of home appliances

01-05-2015
 

The University of Hong Kong

Graduated with a Master's degree in Mechanical Engineering with Credit

01-07-2016
 

Hong Kong Productivity Council

Engineering Officer: Anomaly detection for industrial pressure sensors in Industry 4.0 project

01-06-2018
 

Orient Overseas Container Line

Associate Data Scientist: Market News Summarization (LLMs), Cargo Demand Forecasting (Time-series Forecasting), Email Classification (NLP Text Classification), Search Recommendation (Recommendation Engine)

01-12-2020
 

Moved to Toronto!

Enjoy the summer while looking for job opportunities!

01-07-2024
  • Toronto, 安大略加拿大