Machine Learning Development Services – Build and Scale Intelligent Systems
Transform your data into actionable insights with Toptal’s Machine Learning Development Services. Our ML development teams build machine learning solutions that support automation, prediction, and long-term business scalability.
How We Deliver Machine Learning Development Services
Our machine learning development experts, with experience at leading companies, develop and deploy tailored solutions to meet your business needs and unique industry demands for sustainable results and long-term success.
1
Discover
A leader from our team works with you to understand your business challenges, pain points, and strategic goals to uncover new opportunities and identify the options to reach your objectives.
2
Define
Toptal leaders collaborate with your team to define your specific goals and service needs, evaluating multiple approaches and aligning requirements with your strategic objectives to define the best solution.
3
Develop
We will create your unique project timeline, process, and first drafts, whether your goal is scaling machine learning capabilities, improving operational intelligence, or accelerating AI-driven innovation.
4
Deploy
Toptal will get to work, tracking quality assurance, handling project management, and maintaining the delivery schedule.
As Toptal’s CEO of Technology Services, Robert leads strategy and operations across our technical services portfolio, spanning AI, automation, and operations. He previously served as Deloitte’s Managing Director & Chief Commercial Officer, transforming its Cloud Operate and Engineering business into a multibillion-dollar operation. He held senior roles at IBM, Velocity, co-founded Corio, and was CIO for two Fortune 500 companies.As Toptal’s CEO of Technology Services, Robert leads strategy and operations across our technical services portfolio, spanning AI, automation, and operations. He previously served as Deloitte’s Managing Director & Chief Commercial Officer, transforming its Cloud Operate and Engineering business into a multibillion-dollar operation. He held senior roles at IBM, Velocity, co-founded Corio, and was CIO for two Fortune 500 companies.
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CUSTOMIZED SOLUTIONS
Machine Learning Development Services That Deliver Value
Toptal delivers leading AI development services through its diverse talent network and flexible delivery models. We implement the right skills at each project phase, blending expertise from various roles for seamless execution.
End-to-End Delivery by Toptal
On-demand Talent & Teams
End-to-End Delivery by Toptal
Comprehensive project delivery, tailored to your specific requirements.
As Toptal’s CEO of Technology Services, Robert leads strategy and operations across our technical services portfolio, spanning AI, automation, and operations. He previously served as Deloitte’s Managing Director & Chief Commercial Officer, transforming its Cloud Operate and Engineering business into a multibillion-dollar operation. He held senior roles at IBM, Velocity, co-founded Corio, and was CIO for two Fortune 500 companies.
Rachael serves as a Delivery Manager at Toptal with a focus on leading diverse global teams in developing innovative solutions for our clients. She works across multiple disciplines, including technology, marketing, and management consulting. Rachael specializes in managing people and client relationships, process optimization, and driving teams toward optimal business outcomes.
With an engineering degree, two master's degrees, including an MBA, and the ability to speak four languages, Adrian has delivered as a product manager in North America, Latin America, and Europe on multiple innovation initiatives, including software development, AI strategy, project delivery, blockchain, geolocation, and Agile implementation. Adrian has extensive experience in technical and business roles and has worked in several industries: telecom, cloud native, supply chain, retail, fintech, and IT.
Joao is an AI/ML engineer with more than 14 years of experience at Fortune 100 companies, like Procter & Gamble and Hearst, and startups in the healthcare, energy, and finance industries. Joao holds a master's degree in computer engineering from the University of Porto and has multiple certifications in ML and deep learning.
With over 20 data science and AI projects delivered for startups, enterprises, and academia, Sam offers a unique expertise blend as a senior AI consultant skilled in both hands-on engineering work and leadership roles with a special focus on team leading, project management, and thought leadership. By exploring the AI field from diverse perspectives and through varied projects, Sam is interested and committed to developing AI initiatives where growth, impact, and kindness are all at the center.
Nicolas is an expert data scientist with over 26 years of experience using programming languages, including R and Python, to design and develop AI/ML data products, combined with strong practice leadership and people management skills. Nicolas is a published author and thought leader with a vast track record of success in implementing new and innovative ways of achieving the most scalable, data-centric outcomes to drive new business while promoting a consultative and collaborative environment.
Mohab is a data scientist and machine learning developer who specializes in natural language processing (NLP) and computer vision. He has more than nine years of professional experience, and recent projects have focused on machine learning in the areas of natural language understanding (NLU), cheminformatics, and self-driving cars. Mohab stays current with cutting-edge advancements in deep learning.
Hafiz is a full-stack developer with more than eight years of experience developing robust applications for high-volume businesses in an agile environment. He is a problem-solving team player with a can-do attitude and phenomenal communication skills. Hafiz has been working as a remote independent contractor with companies all over the globe.
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On-demand Talent & Teams
30,000+ vetted professionals, ready to deploy individually or in teams.
Denis is a senior full-stack AI engineer and data scientist, highly skilled in modern generative tech (GPT-4, Midjourney, and more), machine learning, ETL pipelines, data analysis, mathematical modeling, big data, and MLOps. He has a PhD in mathematics, and his data science expertise includes probabilistic risk modeling, revenue forecasting, geospatial data analysis, handwriting recognition, anomaly detection in time series, data engineering, and team leading.
Cristian holds a PhD in computer science, specializing in deep learning for natural language processing. He has experience in both academia and industry, having worked as a research scientist, research engineer, data and machine learning engineer, and full-stack developer for different clients, universities, and companies around the world.
Filip is a machine learning engineer with many years of professional experience. He has worked on large-scale problems at Amazon Web Services as a software developer, and built natural language processing models as a research associate at the University of Zagreb. Filip’s main interests are machine learning and natural language processing, with an emphasis on building text classification models.
With a PhD in physics, a background in mathematics, and more than 13 years of experience modeling real-world data, Teresa has the skills to fulfill any data science role. Teresa enjoys working on the whole pipeline, from data cleaning and analytics to a final predictive model, and she especially enjoys using machine learning models.
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.
Simone is a machine learning scientist and engineer with experience in academia and enterprises, including Microsoft and Huawei. He likes to work at the intersection of deep machine learning, natural language processing, and information retrieval. Simone also loves to work on exploration analysis and building theoretically sound machine learning pipelines ready for production. He especially enjoys building web products.
Lovro is a machine learning engineer and data scientist with a strong enthusiasm for deep learning applications. By combining his academic knowledge with practical industry experience, he is able to contribute to every stage of the AI software development process. Lovro’s professional background spans startups, large corporations such as his engineering role at Amazon, and research positions in academic institutions and universities.
Along with earning a doctorate in computer science and engineering, Dilip has decades of experience in the industry. Since 2015, he's been focusing on projects related to machine learning and deep learning. Dilip has an eye for detail, which helps in working closely with domain scientists and improving the accuracy and reliability of models for fine-grained image classification, object detection and segmentation, natural language processing, time-series forecasting, and generative AI.
Alejandro is an SRE/DevOps/MLOps engineer and expert in cloud technologies with experience in Azure and AWS on large production environments. He can automate anything from code deployment to infrastructure while ensuring best practices and proper monitoring. He has always been curious about how things work to make them more efficient and enjoys learning new technologies. Alejandro thrives in Agile environments where he can put his problem-solving skills to work.
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Toptal in Action
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Fortune 500 CPG company partners with Toptal to pivot to machine learning-assisted marketing engagement management.
Challenge: A leading food and beverage brand was working with multiple costly third-party marketing vendors. The client sought expert advice to create in-house software solutions for multiple high-cost functions, including media mix strategization and engagement tracking.
Solution: Toptal’s team developed a proprietary, in-house marketing intelligence software platform powered by machine learning. The team also introduced a standardized tech stack and change management system, streamlining processes by merging teams previously siloed by geography and tool sets.
Outcome: Using Al tools developed by Toptal’s team, the client has saved millions in third-party spending. It can now determine ideal channel mix, select prospects, and access detailed conversion and engagement data across up to eight markets. Toptal’s team negotiated new partnerships with other media companies the client worked with, giving the client access to additional data above and beyond what the competition sees. Armed with new data and redirected savings, the client has expanded its marketing software product development initiatives.
Working with [the client] was not just about addressing their immediate challenge but reshaping their entire media engagement strategy to be more autonomous and efficient.
Horia Mărgărit
Toptal Machine Learning Developer
Toptal Ranked #1 Most Reliable Professional Services Company in America
Newsweek and Statista’s rankings were based on an independent survey of more than 2,400 decision-makers at Fortune 500s.
Newsweek's Most Reliable Companies in America 2026 ranking. Toptal is ranked #11, the highest-ranked professional services firm.
Explore Insights From the Machine Learning Development Field
Read the latest articles and resources to stay current on emerging trends in machine learning development, predictive analytics, generative AI, MLOps, and enterprise AI strategy.
Machine learning models are trained on massive datasets in which each data point is labeled to give it context and meaning. This deep dive describes how to build a data labeling architecture from scratch, with a focus on workflow, security, and data quality.
Reza is a machine learning engineer specializing in natural language processing and computer vision. At IBM, he developed machine learning algorithms designed to improve text classification and automate model training, innovations that resulted in six patents. Reza has a master’s degree in engineering from the University of Toronto.
CEO, Technology Services
