Karim Lulu

Senior Software Engineer

London, England, United Kingdom11 yrs experience

Most Likely To SwitchHighly Stable

Key Highlights

Designed ML Feature Store improving deployment efficiency.
Led team to develop innovative ML/NLP products.
Enhanced AutoML performance by 5% on NLP datasets.

Stackforce AI infers this person is a Machine Learning Engineer with expertise in SaaS and NLP solutions.

Contact

Skills

Core Skills

Machine LearningMl InfrastructureNatural Language ProcessingData Science

Other Skills

A/B TestingAWS LambdaAlgorithmsAmazon KinesisAmazon Web Services (AWS)AnalyticsAnomaly DetectionApache SparkApplied Machine LearningApplied MathematicsAutomated Machine Learning (AutoML)Bayesian inferenceBayesian statisticsCollaborative FilteringComputer Science

About

Machine Learning Engineer with experience in working on various ML/AI projects. Enjoy working on solving complex data challenges. Competencies: data science, machine learning, NLP, Spark, Python/SQL/R, AWS (EC2, S3, EMR, Athena, Glue, Amazon API), Docker, NoSQL (MongoDB).

Experience

11 yrs

Total Experience

1 yr 7 mos

Average Tenure

3 yrs 8 mos

Current Experience

Roku inc.

Senior Software Engineer, Machine Learning

Sep 2022 – Present · 3 yrs 8 mos · London, England, United Kingdom

Leading key initiatives in the field of production-oriented machine learning and ML infrastructure, significantly enhancing the platform's capabilities and user experience. Key accomplishments include:
ML Feature Store: Designed and developed the ML Feature Store, enabling the team to reuse common features, collaborate efficiently, and utilize a unified interface for both batch ingesting and inference. The feature store's versioning support improved synchronization between data and models, resulting in faster deployments and contributing to a 0.57% reduction in abandonment rate and a 0.21% increase in visit-to-focus rate.
Leveraging LLMs: Led efforts to leverage LLMs across the team and organization. Designed and developed the necessary infrastructure, collaborating closely with key stakeholders to integrate LLMs effectively into our workflows.
Enhanced Search Experience: Implemented a row-based search experience on the platform, which improved result diversity, enabled effective cross-vertical searches, reduced the abandonment rate by 1.5%, and increased streaming hours on the platform by 3.5%.
Infrastructure Improvements: Led the replacement of the Redis cache with an in-house solution, working on both the infrastructure and software tiers to ensure seamless integration and performance enhancement.
Optimized Ranking Models: Enhanced the ranking system by optimizing BERT-based cross-encoder models, reducing latency by 25% and increasing throughput by 30% without compromising ML performance.

Data ManipulationMachine LearningML Infrastructure

Datarobot

Senior Machine Learning Engineer

Mar 2021 – Sep 2022 · 1 yr 6 mos · Kyiv, Kyiv City, Ukraine

Led significant advancements in the AutoML and Text AI capabilities, driving innovation and enhancing performance across various NLP-related workflows. Key accomplishments include:
Improved AutoML Performance: Enhanced the performance of DataRobot's AutoML system by approximately 5% on diverse NLP datasets through leveraging transfer learning and fine-tuning techniques. This led to a 10% increase in the number of deployed models by users.
Enhanced Language Detection: Implemented an ML-based system that improved language detection capabilities by 20%, and decreased the optimal model search time by 10%.
Integration of Advanced Models: Led the initiative to integrate new deep learning and transformer models into the platform, particularly for text data, significantly broadening the platform's capabilities.
Text AI Component: Designed and developed the Text AI component of DataRobot’s platform, enabling users to unlock insights from vast amounts of text data.

PythonNatural Language Processing (NLP)Machine LearningAutomated Machine Learning (AutoML)MLOpsElasticsearch+11

Galactica labs

ML Architect and Lead

Aug 2019 – Present · 6 yrs 9 mos · Remote

Focused on building ML and NLP automation products to streamline patent application drafting. Key responsibilities and accomplishments include:
Technical Roadmap and Solution Design: Defined the technical roadmap and designed robust ML and NLP solutions to automate patent application drafting, leveraging technologies such as Python, spaCy, fastText, and AWS.
Leadership and Team Management: Led a team of engineers, providing guidance and direction to ensure the successful development and deployment of automation services.
Code Reviews and Development Oversight: Conducted comprehensive code reviews and navigated the development of the system, ensuring high-quality and efficient codebase.
Industry Impact: Contributed to significant advancements in the legal tech industry by implementing innovative ML/NLP products, enhancing the efficiency and accuracy of patent application drafting processes.

Machine LearningNatural Language Processing

Ninety percent of everything

Machine Learning Engineer

Jul 2019 – Mar 2021 · 1 yr 8 mos

Created a streaming service for IoT data correction and enrichment. Ensured high availability and accuracy of the vessels’ data
Automated an optimal distribution of the personnel across a fleet. Reduced time costs from 1 week to a few seconds
Applied computer vision techniques to build feasibility maps for vessels' routes
R&D of a fuel consumption prediction for a variety of vessels in the ocean

MLOpsElasticsearchWorkflow OrchestrationUnit TestingFlaskData Manipulation+3

Grammarly

Research Engineer

Sep 2018 – Jun 2019 · 9 mos

R&D, building and supporting production-ready DL / ML systems
Applying Deep Learning and Machine Learning methods to Grammatical Error Correction
Creating and designing end-to-end pipelines for data preparation, model training, and evaluation

Unit TestingFlaskData ManipulationMachine Learning

Digamma.ai

Machine Learning Engineer

Feb 2017 – Aug 2018 · 1 yr 6 mos · Kyiv, Kyiv City, Ukraine

Improved relevance of recommended items by ~30% by implementing a machine learning-based recommendation system, leading to investments from Google’s Assistant fund
Reduced “time-to-find” by ~40% by implementing a machine-learned ranking system
Developed Python API for Time Extractor NLP library
R&D of the distributed anomaly detection framework for time series data

MLOpsElasticsearchUnit TestingFlaskData ManipulationMachine Learning

Innovizo

Data Scientist

Jul 2016 – Jun 2018 · 1 yr 11 mos · Washington D.C. Metro Area (remote)

Conducting machine learning, data analytics, data mining, and building predictive data models for U.S. clients
R&D of the intelligent demand response system (IoT ML solution)

FlaskData ManipulationData Science

Ideals™ solutions group

Data Analyst & BI

Apr 2016 – Feb 2017 · 10 mos · Kyiv, Ukraine

R&D of a click fraud detection system
R&D of a duplicate detection system
Created a data management and analytical system
Build and automate reports on business performance
Produce and present data insights for CEO

Data ManipulationData Science

Allbiz global

Data Analyst

Oct 2015 – Apr 2016 · 6 mos · Kyiv, Ukraine

Conducted data analytics for B2B e-commerce platform
Developed predictive data models for customer retention strategies

Kyiv school of economics (kse)

2 roles

Statistics and Mathematics Teaching Fellow

Sep 2015 – Jun 2016 · 9 mos · Kyiv, Ukraine

Taught Econometrics and Mathematics courses for MA students
Taught Mathematics and Statistics courses for enrollees to MA programs

Research Assistant (Data Analyst)

Jan 2015 – Jul 2015 · 6 mos · Kyiv, Ukraine

Regression analysis and data cleaning for various academic projects
Analysis of the online parallel market for USD in Ukraine (review of 2014 and 2015)