Alex Kim, Developer in Montreal, QC, Canada
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Alex Kim

Verified Expert  in Engineering

Software Developer

Montreal, QC, Canada
Toptal Member Since
December 3, 2019

Alex is an ML engineer with 10+ years of experience in the tech industry. He has shared his expertise as an invited speaker at various conferences and meetups, helped companies with their ML strategy, and advised startups on their Data Science curriculum. He's also the founder and organizer of PyData Montreal, Canada's largest PyData meetup.


Machine Learning Operations (MLOps), Continuous Machine Learning (CML)...
Amazon Web Services (AWS), PyTorch, Keras, Scikit-learn, Jupyter...
Rio Tinto
Python, Amazon Web Services (AWS), PyTorch, Scikit-learn, SQL, Linux,




Preferred Environment

Python, Keras, PyTorch, Scikit-learn, SQL, DVC, CI/CD Pipelines, Data Science, Machine Learning

The most amazing...

...project I've done is build machine learning-based services used by millions of users a day.

Work Experience

Solutions Engineer

2022 - PRESENT
  • Acted as the technical account manager for large enterprise clients that account for over 65% of the company's revenue.
  • Supported clients in integrating iterative tools into their existing systems and processes. Led training sessions on the best MLOps practices.
  • Partnered with founders and product and sales teams to drive sales, define the product roadmap, and demonstrate the technical capacities of iterative tools.
Technologies: Machine Learning Operations (MLOps), Continuous Machine Learning (CML), CI/CD Pipelines, PyTorch, Data Science, Machine Learning, Amazon Web Services (AWS), Education, Training

Data Science Consultant

2017 - PRESENT
  • Delivered corporate training on data science, machine learning, and MLOps.
  • Developed and refined the data science curriculum to improve outcomes at online boot camp programs and universities.
  • Worked with several organizations, namely O'Reilly Media, McKinsey, Lambda School, Yandex Practicum, and Concordia University.
Technologies: Amazon Web Services (AWS), PyTorch, Keras, Scikit-learn, Jupyter, Machine Learning, Neural Networks, Python, Data Science, Education, Training

Senior Data Scientist

2020 - 2022
Rio Tinto
  • Led the development of predictive maintenance and computer vision applications at Rio Tinto's smelters and hydroelectric power stations.
  • Mentored junior software engineers and data scientists.
  • Established team processes and best engineering practices.
Technologies: Python, Amazon Web Services (AWS), PyTorch, Scikit-learn, SQL, Linux,, Machine Learning, Neural Networks, Data Science

Senior Data Scientist

2018 - 2020
  • Automated a part of the post-production team's workflow by developing a deep learning-based video action recognition system.
  • Designed and developed a public-facing web application to crowd-source image labeling and annotation data, eliminating the need for expensive 3rd party services.
  • Improved the process of deploying and monitoring the performance of ML models in production by utilizing the best CI/CD practices, such as code and model versioning and unit and integration testing.
Technologies: Elasticsearch, Splunk, MongoDB, Redis, Apache Hive, SQLite, PostgreSQL, OpenCV, PyTorch, Keras, Scikit-learn, Jupyter, Bokeh, Plotly, Matplotlib, Blaze, Dask, Pandas, SciPy, NumPy,, Machine Learning, Neural Networks

Machine Learning Engineer

2017 - 2018
  • Built machine learning applications within the Splunk ecosystem to allow users without a strong data science background to train, validate, and deploy ML models quickly.
  • Implemented novel parameter-free machine learning algorithms in Splunk Machine Learning Toolkit.
  • Provided consulting services to Splunk's clients, solving their operational and domain-specific challenges and establishing their data analytics strategy using Splunk.
Technologies: Elasticsearch, Splunk, MongoDB, Scikit-learn, Jupyter, Bokeh, Plotly, Matplotlib, Blaze, Dask, Pandas, SciPy, NumPy, Windows, MacOS, Linux, Machine Learning, Data Science

Software Engineer

2013 - 2017
  • Designed and developed software systems to process and classify satellite images using modern software development practices, including unit testing, continuous integration, and configuration management.
  • Performed statistical modeling to test and verify the performance of developed algorithms.
  • Administered on-premise and cloud-based Linux servers by installing and troubleshooting system software and programs.
  • Developed an operations database system for convenient monitoring of space segment's health status, command execution, and data flow by allowing the execution of interactive queries and creating custom dashboards.
Technologies: Amazon Web Services (AWS), Elasticsearch, Splunk, MongoDB, Redis, Apache Hive, SQLite, PostgreSQL, OpenCV, Scikit-learn, Jupyter, Bokeh, Plotly, Matplotlib, Blaze, Dask, Pandas, SciPy, Linux, Data Science, Machine Learning

NSFW Data Scraper
NSFW data scraper and image classifier.

Featured in:

Presentation on Approximate Nearest Neighbors
Built using Jupyter slides and RISE extension.

Parameter-free K-means Clustering: X-means
Implementation of X-means algorithm based on Pelleg, Dan, and Andrew W. Moore. "X-means: Extending K-means with Efficient Estimation of the Number of Clusters." ICML. Vol. 1. 2000.

Video Frame Remover
Remove frames and borders around videos.
2011 - 2013

Master's Degree in Physics

Unviersity of Alberta - Edmonton, Canada

2007 - 2011

Bachelor's Degree in Physics

Moscow State University - Moscow, Russia


AWS Cloud Architect



Splunk Certified Power User



Machine Learning Engineer Nanodegree



NumPy, Pandas, Matplotlib, Scikit-learn, SciPy, PyTorch,, Keras, OpenCV, Dask


PyCharm, Plotly, Jupyter, Splunk, ELK (Elastic Stack), Amazon SageMaker, Git, GitLab, GitHub, MATLAB, Confluence, Jira


Python, R, SQL


Linux, Jupyter Notebook, Docker, Amazon Web Services (AWS), Visual Studio Code (VS Code), MacOS, Windows, Amazon EC2, Azure


Data Science


Elasticsearch, PostgreSQL, SQLite, Apache Hive, Redis, MongoDB, Amazon S3 (AWS S3)


Machine Learning, Computer Vision, Image Recognition, Neural Networks, Continuous Machine Learning (CML), Blaze, Bokeh, Windows Subsystem for Linux (WSL), CI/CD Pipelines, Machine Learning Operations (MLOps), Education, Training

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