Rajiv Abraham
Staff Machine Learning Platform Engineer @Mistplay
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WORK HISTORY
Staff Machine Learning Platform Engineer @Mistplay
Toronto, ON, CA
Led a team of two ML developers to identify and address platform debt, while strategically planning and implementing updates- Deployed Random Forest models using MLFlow for serving on AWS Sagemaker with best engineering practices like unit testing, API replay and load testing. Minimized business risk by performing shadow deployments to validate the model before full production usage. Monitored live deployments with a combination of Datadog for service statistics and Delta Lake for debugging predictions- Developed and optimized Airflow Directed Acyclic Graphs (DAGs) for seamless data extraction from Databricks Delta Lake using Spark and synchronization with AWS Elasticache(Redis), ensuring efficient and reliable data workflows- Deployed jobs on the Databricks platform leveraging Spark, Delta Lake and Workflows- Led the Proof of Concept (POC) engineering effort for A/B testing models using Statsig. Successfully identified Statsig as the vendor of choice after comparing it with another vendor in live experiments. Delivered the project on time, disseminated knowledge across the organization, and provided ongoing support to various projects with expertise in A/B testing methodologies- Advocated for and prototyped robust monitoring systems using Databricks Lakehouse Monitoring to detect feature drift- Conducted feature store optimization benchmarking showing the optimal compression and serialization technologies to get up to 60% space savings in AWS Elasticache(Redis). Wrote locust like load testing scripts for benchmarking latencies of different Elasticache configurations for production workloads- Researched and presented new technologies like Featureform, OpenTelemetry, Flyte to the ML Platform team.
EDUCATION
University of Mumbai
Bachelor, Computer Engineering
Concordia University
Masters, Computer Science
SKILLS
ABOUT RAJIV ABRAHAM
Interested in ML engineering (or MLOps) research. I seek to build libraries, IDEs, compilers, domain specific languages or programming languages, databases for ML.Personal Project Showcase: https://rabraham.github.io/site/posts/notable-projects.htmlBlog: https://rabraham.github.io/site/Youtube: (TheCodePlumber)# Summary:Fast learner: Proven experience in learning different technologies in infrastructure, machine learning, web development and data engineering.Innovative: Passionate about learning new programming languages and building libraries to improve developer productivity.Engineering focused: Experienced and passionate in practices like Test Driven Development.Community builder: Organized a functional programming meetup group called FunctionalTO for three years.(Youtube Channel: Big Data/Machine Learning- Early adopter of Apache Spark- Achieved an 100% score for the machine learning course on Coursera (by Andrew Ng)- Built Thampi(https://rabraham.github.io/site/posts/thampi-introduction.html), a machine learning model prediction server built on AWS Lambda(serverless). With a single command, a data scientist can deploy his trained model to AWS Lambda and not worry about devops.# Other GitHub projects- Mercylog(https://rabraham.github.io/site/posts/introducing-mercylog.html). Mercylog is an exploration of using Datalog(a language similar to SQL) as a foundation for analytics and machine learning- Jaya(https://github.com/RAbraham/jaya). Jaya was a pioneering prototype in building AWS Service pipelines in code. Using Python, one could specify pipelines like s3_bucket1 >> copy >> s3_bucket2. It also made it easy to deploy Python code to AWS Lambda.Mercylog-DataScript(https://github.com/RAbraham/mercylog-datascript): mercylog-datascript is a Python based query composer for the excellent frontend data store DataScript. All of this runs in the browser using Brython.# Community Involvement- Organizer of the FunctionalTO meetup for 3 years:
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