Özer Özdal
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Özer Özdal Email & Phone Number

Machine Learning Engineer at Caylent at Caylent
Location: Montreal, Quebec, Canada 11 work roles 4 schools
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Current company
Role
Machine Learning Engineer at Caylent
Location
Montreal, Quebec, Canada
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Özer Özdal is listed as Machine Learning Engineer at Caylent at Caylent, a company with 31 employees, based in Montreal, Quebec, Canada. AeroLeads shows a matched LinkedIn profile for Özer Özdal.

Özer Özdal previously worked as Machine Learning Engineer at Caylent and Senior Data Scientist at Canadian Red Cross. Özer Özdal holds Doctor Of Philosophy - Phd, Physics, 3.57/4.0 from Concordia University.

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Caylent

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Profile bio

About Özer Özdal

I am a dedicated ML/MLOps Engineer with a strong background in building, deploying, and optimizing scalable machine learning systems. My passion for designing software systems, APIs, and extensible products drives my work, enabling me to integrate ML models into production environments successfully. I focus on automating workflows, ensuring the reliability of ML/AI-driven solutions, and creating innovative, scalable systems that enhance performance and efficiency.My expertise lies in creating end-to-end pipelines that streamline the ML lifecycle, from data ingestion and model training to deployment and monitoring. I specialize in utilizing AWS services such as AWS SageMaker, AWS CloudFormation, and others to automate the design, deployment, and monitoring of scalable ML/AI SaaS products, ensuring they meet the highest standards of performance and reliability.At the core of my work is a passion for bridging the gap between data science and operations. My experience spans across various tools and technologies, including TensorFlow, PyTorch, Docker, Kubernetes, and CI/CD platforms like GitHub Actions and CircleCI. I have also worked with LangChain to build and deploy complex language models, enabling sophisticated natural language processing applications.Additionally, I have experience with federated learning on embedded devices, allowing for decentralized model training while preserving data privacy. This has been particularly valuable in scenarios where data security is crucial, and where edge computing resources are limited.Collaboration is key to my approach. I work closely with data scientists, machine learning architects, data engineers and other stakeholders to deliver high-impact solutions that drive business outcomes. My experience leading cross-functional teams has sharpened my ability to manage complex projects and ensure that ML/AI models are not just accurate, but also maintainable and scalable.Whether it's designing infrastructure for model deployment, optimizing ML workflows, or implementing monitoring and alerting systems, I am always focused on enhancing performance and ensuring seamless operations. I am continuously learning and staying updated with the latest advancements in MLOps, cloud computing, and AI technologies.I’m looking forward to connecting with professionals who share my passion for innovation in machine learning and operations. Let’s collaborate to build the future of ML/AI-driven solutions.

Current workplace

Özer Özdal's current company

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Caylent
Caylent
Machine Learning Engineer at Caylent
irvine, california, united states
Website
Employees
31
AeroLeads page
11 roles

Özer Özdal work experience

A career timeline built from the work history available for this profile.

Machine Learning Engineer

Current

Montreal, Quebec, Canada

Oct 2024 - Present

Senior Data Scientist

Montreal, Quebec, Canada

  • Designed and optimized machine learning solutions at the Canadian Red Cross by:
  • Building a machine learning model for the Canadian Red Cross to refine donor engagement by predicting donor behaviors through advanced propensity modeling.
  • Developing a bilingual chatbot that streamlined information retrieval for staff, enabling quick access to clear answers and relevant hyperlinks in both English and French.
  • Building and optimizing scalable, production-ready ML pipelines for predictive modeling by developing high-performance algorithms.
  • Automating testing, deployment, and monitoring to ensure reliability and efficiency in production environments.
May 2024 - Oct 2024

Machine Learning Engineer

Montreal, Quebec, Canada

  • Refined and enhanced ALS GoldSpot Discoveries' machine learning platform and SaaS products by:
  • Designing, developing, and optimizing ML models and feature engineering pipelines to boost accuracy and efficiency in prospectivity analyses across SaaS offerings.
  • Creating and maintaining robust backend API components to streamline geoscientists' workflows and integrate ML insights into SaaS solutions.
  • Debugging and modifying systems to resolve issues and add new features, maintaining the cutting-edge functionality of both the platform and SaaS products.
  • Developing an automated unsupervised clustering tool using Self-Organizing Maps (SOM) to generate detailed geological maps, enhancing precision in lithology exploration.
  • Designing an API that improves the resolution of GeoTIFF images using Adapted Super-Resolution Generative Adversarial Networks (GANs), while keeping the original content and intricate details intact.
Dec 2022 - Jan 2024

Data Scientist

Montreal, Quebec, Canada

  • Managed and successfully executed over 15+ consulting projects within the mineral exploration domain, delivering comprehensive results to stakeholders.
  • Designed a data transformation product that enhances signal strength and reduces noise levels by analyzing raster stacks in a thematic manner.
  • Design and guide experiments/analysis to measure impact and drive product improvements.
  • Initiate, develop, and maintain data pipelines with outstanding craftsmanship.
  • Conduct deep dives to help solve complex problems to drive impact and achieve ALS GoldSpot Discoveries' strategic business objectives.
  • Assisting in enhancing Goldspot's exclusive machine learning workflows.
Dec 2021 - Nov 2022

Data Scientist

Moncton, New Brunswick, Canada

  • Implemented and deployed machine learning solutions to enhance the efficiency, speed, and accessibility of lung cancer screening.
Jul 2021 - Oct 2021

Postdoctoral Researcher

Montreal, Quebec, Canada

  • My goal is to compare two D dimensional samples: the SM simulated events (background to BSM searches), and the real data, and to check if the two are drawn from the same probability density distribution. Lead to two.
  • Cross-fertilising extra gauge boson searches at the LHC, JHEP 11 (2021) 014
  • Electron and muon magnetic moments and implications for dark matter and model characterisation in non-universal U(1)′ supersymmetric models, JHEP 10 (2021) 063
Sep 2020 - Aug 2021

Teaching Assistant (Ta)

Montreal, Canada Area

  • TAed for 8 physics courses. Graded assignments and wrote solutions, lead office hours and tutorial sessions:
  • PHYS 204 Mechanics (Tutor, 2020 Summer)
  • PHYS 273: Energy and Environment (2020 Winter)
  • PHYS 284: Introduction to Astronomy (2019 Fall)
  • PHYS 204 Mechanics (Tutor, 2019 Summer)
  • PHYS 367 Modern Physics and Relativity (Tutor, 2019 Winter)
Sep 2016 - Jul 2020

Visiting Researcher

Southampton, United Kingdom

  • The project has been supported by MITACS Globalink Research Award. Lead to two scientific publications.
  • Leptophobic Z′ bosons in the secluded UMSSM - Phys.Rev.D 102 (2020) 11, 115025
  • E6​ motivated UMSSM confronts experimental data - JHEP 05 (2020) 123Talks:1) Higgs Couplings Workshop, Oxford, UK. 30 September - 4 October, 2019 Title: Mass spectrum and Higgs profile in B−L symmetric SSM2) University.
Sep 2019 - Jan 2020

Researcher Tubitak Project No: 114F461

Tubitak

Izmir, Turkey

  • Studied muon anomalous magnetic moment and yukawa quasi-unification in supersymmetric models. Lead to one scientific publication:
  • Muon g−2 in an alternative quasi-Yukawa unification with a less fine-tuned seesaw mechanism - Phys. Rev. D 97, 055007 (2018)
Sep 2015 - Aug 2016

Summer Internship

Istanbul, Turkey

Mechanical Characterization LabProject title: Vibration modeling in nanowire resonators with mechanical couplingUnder the supervision of Assoc. Prof. Erdem Alaca

Jun 2012 - Sep 2012
Team & coworkers

Colleagues at Caylent

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4 education records

Özer Özdal education

Doctor Of Philosophy - Phd, Physics, 3.57/4.0

Activities and Societies:Studied the phenomenology of new physics beyond the Standard Model: signals of dark matter and new gauge bosons.

Inter-University Transfer Student, Physics

Took two graduate courses: √ Physics 610 Quantum Field Theory I given by Prof. Simon Caron-Huot √ Physics 673 Quantum Field Theory II.

Master Of Science - Ms, Physics, 3.5/4.0

Studied the Higgs boson and right-handed neutrinos in supersymmetric models. Lead to a scientific publication: √ Mass spectrum and Higgs.

Bachelor Of Science - Bs, Physics, 3Rd Ranked

√ Winter School on Computer Applications in Accelerator and Particle Physics (Gaziosmanpaşa University, Tokat, Turkey - 2014, February.

FAQ

Frequently asked questions about Özer Özdal

Quick answers generated from the profile data available on this page.

What company does Özer Özdal work for?

Özer Özdal works for Caylent.

What is Özer Özdal's role at Caylent?

Özer Özdal is listed as Machine Learning Engineer at Caylent at Caylent.

Where is Özer Özdal based?

Özer Özdal is based in Montreal, Quebec, Canada while working with Caylent.

What companies has Özer Özdal worked for?

Özer Özdal has worked for Caylent, Canadian Red Cross, Als Goldspot Discoveries Ltd., Goldspot Discoveries Corp., and Breathe Biomedical (Formerly Picomole).

Who are Özer Özdal's colleagues at Caylent?

Özer Özdal's colleagues at Caylent include Guilherme Lauxen Persici, Steve Langston, Steven Connolly, Matt Sollie, and Gaganpreet Singh.

How can I contact Özer Özdal?

You can use AeroLeads to view verified contact signals for Özer Özdal at Caylent, including work email, phone, and LinkedIn data when available.

What schools did Özer Özdal attend?

Özer Özdal holds Doctor Of Philosophy - Phd, Physics, 3.57/4.0 from Concordia University.

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