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Michael Schroter

PyTorch Engineer
Expert in data insights & visualizations, predictive analytics, & computer vision.
Michael Schroter is a data and business analyst who specializes in providing business analytics solutions, including data insights/descriptive analytics, data visualizations, text mining, interactive dashboards/business intelligence, predictive analytics, text analytics, and computer vision. He is highly proficient in tools such as Python Data Stack, AWS, Cython, Pytorch, Python SpaCy, RStudio, MySQL, OracleSQL, Arcpy, Geopanda, Linux (Ubuntu, Debian), SAS Enterprise Miner, Tableau, and more.

Patrick Schubert

PyTorch Engineer
Past clients include Google, Accenture & Cognizant.
Patrick Schubert is a digital marketing specialist and business and web analyst with over a decade of expertise in customer behavior, strategy, as well as web development. He has experience across different aspects of digital marketing, including SEO, SEM, social media marketing, Google Analytics, CRM, product management, and marketing strategy. His past clients include Google, SEMrush, Starmind, Elium, and FastStage, among others. IDENTIFY OPPORTUNITIES - Marketing is like art; some people play the piano or guitar, I play with brands and mindsets to get a thrilling marketing mix. CONSULTING BUSINESSES - The world and people are transforming, and your company should be agile to be still inspiring too, never mind whether, new technology, new mindsets of people; you can reach the right people every time. TECH SAVVY Besides my web projects, I'm a tech enthusiast and possess vast knowledge of new technology and usage in businesses. Major reached milestones: * Founding and organizing some music festivals from scratch. - Agile Project Management, Team Leading, Fund Rising, Calculating the marketing budget, Collaborating with various parties * Writing a German guide for Google Analytics beginners. - Customer Success, Work under Pressure, Find a Solution, translating technical knowledge to any customers * Created marketing strategy offline/online for the DACH market. - Multichannel Marketing, Influencer & competitor research, solution finding, POS, B2B, B2C, Business Analyze * I write various LinkedIn, Medium, Blog article about marketing. - Perseverance, Commitment, Self-Motivation, self-learning, teaching

Elena Sanina

PyTorch Engineer
Former data scientist at Sintelix.
Mathematical, programming, and financial backgrounds together with practical experience in projects across different departments allowed me to develop a highly adaptable mix of analytical, technical, and personal skills.

Gabriel Ortolaza

PyTorch Engineer
Frontend software engineer at Giftly.com.
Gabriel is a software engineer with 15 years of experience, specializing in front-end development with JavaScript, React, React Native, Vue.js, Angular, Node.js, and Express.js. He has developed applications and websites for many industries, including HR and staffing, fashion and social networking, healthcare, and eCommerce (including Walmart). Gabriel is passionate about simplifying processes, inventing solutions, and following best practices.

Yuen Hern Yu

PyTorch Engineer
Data Scientist / AI Research Engineer at Xpress AI Sdn Bhd
Yu Yuen Hern is a Data Scientist and research engineer at Xpress AI, He actively researches, develops and translates AI and Data Science methods into software products. Currently pursuing a Master of Data Science at the University of Malaya to gain a deeper understanding of Data Science methods. He occasionally consults and train teams to embrace data science, contributes to open-source projects on GitHub and answers questions on StackOverflow.

Holger Knust

PyTorch Engineer
Worked with Uheri, Wikimedia, and Dycom.
Creative software engineer with over 20 years of experience in building web and mobile app. Strong contributor with completion for 70+ projects. Seeking a challenging position that requires the combination of technical expertise and dedication to the outcome and also provides the satisfaction of making meaningful contributions to the company’s objectives.
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Most teams see matched candidates within 48 hours. Our pre-vetted network means we are not starting from scratch when you reach out. If we do not have the right person available, we will tell you upfront rather than scramble.
Practitioners vet practitioners. Your growth marketer candidate gets interviewed by someone who has run growth at similar companies, not a recruiter checking keywords. We combine technical assessments, portfolio reviews, and cultural fit screening before anyone reaches your inbox.
Contract talent works on defined projects with clear deliverables. Embedded talent integrates into your team for ongoing work, attending standups and using your tools. Both can transition to full-time if the fit is right. We help you choose based on scope, timeline, and budget.
If it is not working in the first few weeks, we will find you a replacement at no additional cost. We are not in the business of defending bad matches. Most clients never need this because we invest heavily in fit upfront.
We offer flexible engagement models: hourly for short-term projects, monthly retainers for ongoing work, or placement fees for full-time hires. No hidden fees, no long-term contracts unless you want them. Your account manager will walk through options on your discovery call.
Yes. Someone who thrived at Google with dedicated QA, DevOps, and product managers may flounder when they have to wear all three hats. We look for people who have operated at your stage, pace, and level of ambiguity.
Yes, and not just the flashy demo-building part. Our Agent Operations practice includes people who have run AI agents in production and dealt with the messy reality of keeping them reliable, cost-effective, and safe.
Most marketplaces optimize for volume. They send you 10 candidates hoping one sticks. We optimize for fit. We would rather say “we do not have the right person” than waste your time. Our 95% satisfaction rate comes from being selective, not fast.