
Hire the Top 3% of Machine Learning Engineers in 48 Hours
Hire machine learning engineers, developers, consultants, experts, and specialists on demand. Top companies and startups choose machine learning engineers from Toptal for predictive modeling, deep learning, data preprocessing, algorithm development, and more.
The Toptal developer was instrumental in building the prototype and helped accelerate our time to raise funds by several weeks.
Vinod Kumar Ramachandran, Co-founder & CEO, Big Sur AI
Trusted by leading brands and startups
Meet Machine Learning Engineers in Our Exclusive Network
Featured Talent

Metti Paak
Machine Learning Engineer
Mehdi is a data scientist and machine learning/deep learning expert who has extensive experience in software development and mathematical/statistical modeling. He has worked in the aerospace, manufacturing, and healthcare industries developing custom, data-driven predictive software tools. He is proficient in translating business goals into data products and architecting the entire pipeline to the point of delivery. His work has led to multiple patents, publications, and successful fundraising.

Ishola Babatunde Isaac
Machine Learning Engineer
Isaac brings extensive experience in applying machine learning (ML), including Generative AI (GenAI), across diverse fields and complex challenges. He has worked on ML applications in ad security, supply chain management, business analytics, image tracking, healthcare technology, hardware, and failure prediction. Isaac has successfully led teams and managed projects from initial conception through full deployment in both startup and enterprise environments.

Matias Aiskovich
Machine Learning Engineer
Matias is a machine learning engineer who's delivered creative solutions for social impact projects. His past experience includes working at IBM Research as a machine learning engineer (collaborating with IBM's Yorktown Heights research lab), co-founding a startup that develops research-backed cognitive games for the elderly (which was a provider for a Uruguayan government program), and working on several projects that use machine learning to innovate in the healthcare sector.

David Dai
Machine Learning Engineer
David has extensive experience in building machine learning and deep learning (DL) solutions at top companies, including Apple, Google, and Facebook, unicorn startups, and academia, as he has a PhD from Carnegie Mellon U. He holds multiple patents in DL-based medical imaging tech and large-scale AI systems. David has grown an AI team to 60+ as the director and tech lead.

Lovro Iliassich
Machine Learning Engineer
Lovro is a machine learning engineer and data scientist, especially enthusiastic about deep learning applications. Combining his academic knowledge with practical experience in the industry, he can contribute to any part of an AI software development process. Lovro's work experience ranges from startups to corporations—he worked as an engineer at Amazon—and research in academic institutions and universities.

Timo Klock
Machine Learning Engineer
Timo is a full-stack data scientist with eight years of professional experience in data-heavy applications and a PhD in machine learning and statistics. He can work in different roles on the data lifecycle in industrial applications as a data engineer, data scientist, ML engineer, or data analyst. Timo is experienced with Python and SQL, and many modern data frameworks.

Pawel Kaplanski
Machine Learning Engineer
Pawel is an experienced data-scientists and machine learning professional. He has worked for Fortune 100 companies, and he has an academic background in the field. Before moving to data science, he was a former lead architect in Samsung R&D Center. Pawel holds a Ph.D. in knowledge representation and reasoning as well as a master's degree and a bachelor of science degree in computer science.

Peter Papai
Machine Learning Engineer
With a PhD in physics, Peter is a developer working in the field of data science. He has five years of full-time experience working on big data projects at a large internet company. Peter has formulated business goals and designed, prototyped, productized, and A/B-tested machine learning algorithms in several areas. His insights gleaned from data have helped stakeholders make impactful business decisions.

David Sainz
Machine Learning Engineer
David is an experienced data scientist and software and algorithm developer, passionate about new technologies. He started coding when he was eight and has never stopped evolving his tech skills. He has a solid background in .NET, Java, Python, R, and C++ and has proven expertise in machine learning and data analysis. Despite being a self-driven and autodidact professional, David believes the most significant achievements are made in collaborative environments.

Naoki Shibuya
Machine Learning Engineer
Naoki is a senior machine learning engineer with experience in PyTorch. He is passionate about deep learning training, and he worked on model quantization and neural architecture search for vision models. Naoki is also an experienced C++ programmer who has worked on real-time algorithmic trading systems.

Adrian Curic
Machine Learning Engineer
Adrian is a software engineer and data scientist working at the intersection of software engineering, computer vision, and machine learning. He has experience in research, multinational corporations, and startup environments and was awarded patents for real estate and financial modeling projects. Adrian also contributed to surveillance systems for Singapore's border security and participated in competitive coding and hackathons, consistently ranking in the top 1% on platforms like HackerRank.

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Our talent network is composed of thoroughly vetted professionals who ramp up quickly, function as essential team members, and deliver results.
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Our experienced talent matchers specialize in identifying talent that fits your needs. They work to understand your exact requirements and hand-select the best professionals for your project.
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We handle all aspects of billing, payments, and NDAs, streamlining the hiring process so you can focus on innovation, not overhead.
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We want to be sure your engagement is a total success, so we offer a no-risk trial period. Work with your new hire for up to two weeks and pay only if you’re satisfied.
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We help you scale your team up or down as needed, with quick and efficient hiring in under 48 hours.
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Our flexible engagement models allow you to choose the engagement type that suits your needs and adjust it anytime: hourly, part time, or full time.
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Why Organizations Choose Toptal®

Toptal gave us access to the best designers out there, saving us a lot of time and allowing us to build the best possible product.
Thierry JakircevicGeneral Manager, Digital Solutions, Bridgestone

Toptal’s talent is really excellent. They are able to work through large business problems and code incredibly efficiently.
Emily LemonSenior Director, Cleveland Cavaliers

The kind of people we looked for were hard to find. Toptal helped us achieve our goals by bringing high quality resources to bear on very short notice.
Elmar PlatzerDigital Transformation Leader, CSR

If you’ve tried working with other vendors, Toptal is going to be a different type of company to work with; they’re going to meet you where your needs are.
Matthew SchumacherSenior Product Manager, Alpha - Precision Drilling
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