Rachel Park
Verified Expert in Engineering
Python Developer
Los Angeles, CA, United States
Toptal member since April 21, 2020
Rachel is a big data professional experienced in various domains, including robotics, biotech R&D, entertainment/media, and healthcare. With 10+ years of experience in data mining and machine learning technologies, she's a proactive leader with strengths in communication and collaboration. With her expertise in the ML ecosystem, both on-prem and cloud-based, Rachel promotes automated data solutions and manages concurrent objectives to drive efficiency and influence positive outcomes.
Portfolio
Experience
- Python - 12 years
- Machine Learning - 7 years
- Amazon Web Services (AWS) - 7 years
- Google Cloud Platform (GCP) - 5 years
- Architecture - 5 years
- Deep Learning - 5 years
- Kubernetes - 5 years
- Technical Leadership - 4 years
Preferred Environment
Visual Studio Code (VS Code), Amazon Web Services (AWS), Google Cloud Platform (GCP), Spark ML, Kubernetes, Large Language Models (LLMs), Machine Learning, Deep Learning, Python 3, Go
The most amazing...
...experience I've had in Toptal was when I led cross-disciplinary teams to deploy predictive ML models for Navy-funded projects, securing extended funding.
Work Experience
Senior Machine Learning Engineer | Team Lead
Elevance Health
- Led an ML Engineering project component team to oversee the entire product cycle, from designing and engineering solutions to configuring and deploying services while supporting software in the cloud (AWS, GCP) and on-prem environments.
- Owned GPU-based computing APIs that support data scientists with model development. Dockerized different code bases and implemented E2E pipelines for production in Airflow. Implemented the automated release in GitLab CI/CD for testing and deployment.
- Provided mentorship and technical guidance to team members, fostering a collaborative and innovative work environment (code review, literature review, best code practices, design/architecture solutions, etc.).
- Implemented automated release in GitLab CI/CD for testing and deployment. Developed Kubernetes applications. Collaborated with stakeholders to define project goals, requirements, and timelines, ensuring alignment with business objectives.
Tech Lead
Culmen International
- Collaborated closely with government data scientists and domain experts to understand project objectives and requirements, facilitating seamless communication between technical and non-technical stakeholders.
- Spearheaded prototyping of a predictive model for estimating the longevity of CAD/PAD devices, leveraging machine learning techniques and domain-specific knowledge.
- Crafted a government proposal outlining a comprehensive architecture for deploying a machine learning (ML) application in the cloud.
Data Engineer
Hart Inc.
- Designed and developed an ML-based health data search engine via automated schema prediction.
- Modified existing databases to meet unique needs and goals determined during initial evaluation and planning process.
- Wrote scripts and processes for data integration and bug fixes in Python, Scala, and Java.
- Planned, engineered, configured, and deployed ML tooling and big data solutions while supporting software in a Hadoop-Spark ecosystem.
TechOps Engineer
Telescope Inc.
- Built business logic for voting applications and directly support the world's largest live shows such as The Voice, American Idol, and Dancing with the Stars.
- Advised and provided versatile big data solutions using AWS (Dynamo, S3, EC2, etc.) to meet needs of clients.
- Wrote unit tests in Python to automate product validation.
- Researched and developed the integration of smart home devices to the current platform, provided prototypes as a proof of concept to executives/clients, and improved profit margins by launching new add-on projects for existing clients.
Development Engineer/Engineering Consultant
UCLA, Various Startups (Vortex Biosciences Inc., Ferrologix Inc., etc)
- Wrote code to automate statistical analysis on vision data (live/recorded microscopic images/videos) using data science and computer vision tools in Python, MATLAB, and R.
- Trained employees on usage of aforementioned codes remotely.
- Addressed R&D issues from data mining perspective in developing microfluidics platforms for medical applications.
- Authored publications in peer-reviewed scientific journals.
- Consulted start-up companies and assist director with project management.
Robotics Researcher
UCLA
- Developed algorithms to be tested on custom humanoid platforms using Simulink, Python, C++, Lua, ROS, LabView, and COMSOL.
- Maintained robot platforms using CAD, 3D rapid prototyping and CNC mill.
- Competed in DARPA Robotics Challenge Final as Team THOR. (USA, Jun 2015).
- Competed in RoboCup as Team THORwIn (China, Jul 2015) – 1st place winner in the adult-sized humanoid open platform.
- Work as robotics education outreach activity coordinator.
Experience
Data Type Predictor
Semantic Type Predictor
This implementation predicts the semantic type of fields in a given database. It is useful for cleaning data and matching schema.
Single Cell Image Identifier
Education
Master of Science Degree in Mechanical Engineering
University of California, Los Angeles - Los Angeles, CA
Bachelor of Science Degree in Biomedical Engineering
Johns Hopkins University - Baltimore, MD
Certifications
Big Data Hadoop Certification
Edureka
Skills
Libraries/APIs
Spark ML, PySpark, Pandas, REST APIs
Tools
Apache Airflow, Spark SQL, ChatGPT, MATLAB, PyCharm, Atom, Sublime Text, Flume, Tableau
Languages
Python 3, SQL, Python, Snowflake, XML, C++, Scala, Java, Go, GraphQL, JavaScript, R, C#
Frameworks
Spark, Selenium, Flask, Hadoop, Django
Paradigms
ETL, Object-oriented Programming (OOP), RESTful Development, DevOps
Platforms
Amazon Web Services (AWS), Docker, Kubernetes, Visual Studio Code (VS Code), Google Cloud Platform (GCP), Linux, Databricks, Azure, Arduino, Raspberry Pi, Anaconda, Apache Kafka
Storage
PostgreSQL, MySQL, Google Cloud, Data Integration, Redis
Other
Machine Learning, Deep Learning, Scraping, Web Scraping, Data Scraping, Technical Leadership, Architecture, Back-end, Chatbots, Software Architecture, AWS Cloud Architecture, Data Science, Generative Artificial Intelligence (GenAI), Large-scale Projects, Large Language Models (LLMs), Large Language Model Operations (LLMOps), Artificial Intelligence (AI), Vector Databases, Authentication, APIs, Robotics, Full-stack, OpenAI, Computer Vision, Image Processing, Image Generation, Robot Operating System (ROS), Visualization Tools, Technical Hiring, Data Analytics, Data Modeling, Data Profiling, Big Data, Airtable
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