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Sohaib Munawar

Sohaib Munawar

Machine Learning Engineer
Munich, Kreisfreie Stadt München, Oberbayern

Soziales


Über Sohaib Munawar:

A seasoned ML Engineer with a track record of utilizing strong engineering and design principles to drive market-leading products in the AI/ML space. My technical proficiency extends to scalable application architecture design, distributed systems, and the full spectrum of Machine Learning product lifecycle. My forte lies in leadership, with an emphasis on communication and collaboration, business acumen, and an unwavering attention to detail.

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Turing Inc. | Machine Learning Engineer (May 2022 - Sept 2022)

• Designed and developed ML infrastructure for Turing Inc.’s matching platform to intelligently pair software developers with relevant openings from client companies.

• Built, tested and deployed robust pipelines for search and ranking models handling a pool of nearly 1.5M developer profiles.

• Engineered deep-learning models that could generate developer embeddings through the utilization of both resume and profile data.

• Wrote a scheduling service to streamline feature generation, indexing, and storage, optimizing the efficiency of our workflow.

Skills: Google BigQuery · Jupyter · Elasticsearch · Data Engineering · DVC · Data Analysis · Google Cloud Platform (GCP) · pandas · pytest · Engineering Data Management · Algorithms · Scikit-Learn · Data Visualization · Apache Airflow · PyTorch · SQL · Vertex AI · Python (Programming Language)


I2c Inc. | Machine Learning Engineer (Aug 2019 - April 2022)
• Led the design and implementation of a robust and adaptable ML pipeline that caters to a diverse range of business use-cases, including compliance and customer insights, for top-tier financial institutions.

• Pioneered the development of an in-house distributed model storage system based on HDFS and 
MySql to build configurable interfaces enabling efficient storage, retrieval, and management of a wide 
spectrum of models. (ML, DL, and rule-based).

• Drove performance optimization of a prediction RESTful service through the use of multi-threading, 
culminating in a notable 30% reduction in initialization time.

• Spearheaded the research, development, and deployment of cutting-edge Vision models to 
authenticate the signature and handwritten endorsements of cardholders on remotely deposited 
checks, reinforcing the reliability and security of financial transactions.

• Constructed complex NLP pipelines for entity extraction from checks, with logging as transactions in a 
MySql database for relevant financial institutions, thereby advancing the efficiency and accuracy of the 
transaction process.

• Orchestrated a dramatic 2-3X enhancement of prediction bandwidth by deploying Kubernetes and 
TorchServe, enabling seamless scaling and management of model instances across node clusters in 
real-time.

• Fostered a collaborative and cooperative environment with cross-functional teams, encompassing data 
scientists, product managers, and leadership, to ensure alignment with business goals and objectives, 
and promote cohesive and effective decision-making.

Skills: Java · Google Cloud Platform (GCP) · pandas · NumPy · Bitbucket · Bash · Deep Learning · pytest · Engineering Data Management · MLOps · Jira · Hadoop · Algorithms · Data Structures · Computer Vision · Scikit-Learn · Data Visualization · Transformer Models · MLflow · MySQL · TensorFlow · Kubernetes · Docker · Python (Programming Language)

Bildung

  • Ludwig-Maximilians-Universität München
    • MSc. Data Science
  • University of Management & Technology
    • BS Computer Science

 

 

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