Software engineer and manager with 8 years of experience. Employee #2 at Air Space Intelligence, an aerospace and defense startup, which saved Alaska Airlines 5 min on every flight and evaluated the safety, weather, and performance of all flights worldwide. Member of Amazon TTS Research Team who built deep learning speech synthesis called Neural TTS. Proven track record of owning mission-critical data processing infrastructure and people management in complex domains.Main expertise: distributed systems, software architecture, deep learning.Main tech stack: GCP, Kubernetes, Terraform, Python, Django, Postgres, Google Dataflow, Big Query.
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Founding Software EngineerMakoGdańsk, Pl -
Domain ArchitectAir Space Intelligence Apr 2023 - Present- Designed and built flight data processing regression tests on Google Dataflow running on 1000 CPUs. Led a team of three. Integrated with CI/CD using Argo Workflows, and GitHub webhooks- Created a 1) metrics-as-code framework for 4 SLO flight data metric archetypes that covered 80% of the ~60 SLOs needed by product teams 2) core abstractions for managing ~30 data source deconfliction rules- Created a 2-year roadmap for flight information domain development in alignment with managers of all product teams and technical executives -
Foundation Engineering Team Lead | Senior Expert Software EngineerAir Space Intelligence Jan 2023 - May 2023 -
Foundation Engineering Team Lead | Engineering Manager IiAirspace Intelligence Jul 2021 - Jan 2023- Initiated and led the development of data pipelines reprocessing multi-year historical data with flight deconfliction logic. The solution off-loaded the traffic generated by the ML team to the infrastructure not dependent on the production database- Introduced core abstractions to manage over 30 business rules for flight data source deconfliction -
Foundation Engineering Team LeadAirspace Intelligence Nov 2020 - Jul 2021- As the company grew to ~20 people, I took over the leadership of the Foundation Team with 10 team members, reporting directly to the CTO- Owning 5 most critical backend services- Responsible for plannings, 1-1s, and perf review -
Software EngineerAirspace Intelligence Mar 2019 - Nov 2020Palo Alto- Joined as employee #2 after founders- Participated in a 3-week onboarding of Alaska Airlines in Seattle, our first customer. The deployment later turned out to save 5 min avg flight time, 480k gallons of fuel, and 4.6k tons of CO2 emissions in 2021- Redesigned the architecture of cost model storage for the routing algorithm with the CTO- Created the first version of the flight evaluation service- Build the routing algorithm benchmarking suite to evaluate the potential fuel savings -
MentorAi Games - Hackathon Ai Nov 2021 - Nov 2022- Passed the know-how to the next team from Gradient AI science club- Supported the second edition as a mentor and judge -
FounderAi Games - Hackathon Ai Jun 2019 - Nov 2022 -
Main CoordinatorAi Games - Hackathon Ai Jun 2019 - Feb 2020Gdańsk, Woj. Pomorskie, Polska- Organized an AI hackathon for ~140 participants with no prior event organizing experience- Recruited and oversaw 10 core team members directly and ~40 volunteers indirectly- Closed partnerships with 1) Gdansk Science and Technology Park for a free venue 2) SKALP robotics association for giving formal legal entity 3) Air Space Intelligence which became the main sponsor -
Lecturer, Bedataanalyst Path CoordinatorKonferencja Inżynierii Oprogramowania Beit Dec 2018 - Apr 2019Gdańsk, Woj. Pomorskie, Polska -
Lead Scientific Computing EngineerJagan Solutions Jun 2018 - Mar 2019- Came up with the initiative of the internal deep learning project called JAGAN to help the CEO showcase the company’s credibility in the deep learning space- Led a team of 3 people in building GANs and creating training datasets with Flickr API resulting in article published on the website- The company was renamed from JAG Business Computing to JAGAN after the project -
Junior Machine Learning EngineerJag Business Computing (Jag Bc) Jul 2017 - Jun 2018Gdynia, Woj. Pomorskie, Polska- Built an optimization engine for loan parameters for motorcycles with 2 colleagues- Proved that a multi-variable optimization based on a complex Excel spreadsheet suggested by the client can be reduced to a couple of linear equations and implemented in Sympy -
Software Engineer InternAmazon Aug 2017 - Jan 2019- Helped the TTS Research team productionize Neural TTS used in Alexa- Conducted experiments for using Transformer and emotional tones for modeling prosody in speech synthesis- Wrote the Python wrapper for an internal custom CUDA kernel for quick speech synthesis- Migrated the main research repo to Python 3. Refactored legacy speech processing scripts to Python- Onboarded the first member of the RVD (Rapid Voice Development) Team to the new neural architecture to transfer the knowledge before productionization
Paweł Kopeć Skills
Paweł Kopeć Education Details
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Politechnika GdańskaComputer Science -
Wyższa Szkoła Biznesu I Przedsiębiorczości W Ostrowcu ŚwiętokrzyskimGeopolityka I Geostrategia
Frequently Asked Questions about Paweł Kopeć
What company does Paweł Kopeć work for?
Paweł Kopeć works for Mako
What is Paweł Kopeć's role at the current company?
Paweł Kopeć's current role is Founding Software Engineer.
What schools did Paweł Kopeć attend?
Paweł Kopeć attended Politechnika Gdańska, Wyższa Szkoła Biznesu I Przedsiębiorczości W Ostrowcu Świętokrzyskim.
What skills is Paweł Kopeć known for?
Paweł Kopeć has skills like Machine Learning, Python, Algorytmy, Programowanie, Tworzenie Oprogramowania, Git, Linux, Obliczenia Naukowe, Speech Synthesis, Artificial Neural Networks, Convolutional Neural Networks, Deep Learning.
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Pawel Kopec
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Warsaw
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