MLOps represents a significant advancement in the management of AI and ML models, providing a systematic approach to streamline processes. By engaging MLOps teams through staffing agencies, businesses can effectively achieve their objectives. In this article, we will examine the leading MLOps staff outsourcing firms to partner with.
MLOps, short for Machine Learning Operations, is fundamental to the functionality of machine learning. It simplifies the lifecycle of developing ML models, ensuring their deployment across varying environments, monitoring performance, and maintaining them over time for optimal results. MLOps teams typically consist of data scientists, DevOps engineers, and IT professionals who collaborate to ensure efficient operation. These teams enhance the speed of developing and deploying AI models within organizations via continuous integration and deployment (CI/CD), along with validation and governance.
A recent survey of 200 ML decision-makers in the US revealed that 86% of respondents faced challenges in leveraging ML for boosting the commercial value of their organizations. Furthermore, 71% reported difficulties in generating value or revenue from large-scale ML models. Additionally, the study indicated that 85% of organizations had earmarked budgets specifically for MLOps in 2022.
These findings highlight a rising demand for MLOps teams in the global market. The absence of in-house expertise may lead to increased challenges and risks. Collaborating with MLOps staffing firms can mitigate these issues, either by hiring teams to work alongside your business or outsourcing projects to specialized professionals.
In this blog, we will delve deeper into MLOps staff outsourcing firms worth considering.
Is There a Growing Demand for MLOps?
A report from MarketsandMarkets projects that the MLOps market will grow to $5.9 billion by 2027, with a Compound Annual Growth Rate (CAGR) of 41%. The demand for MLOps has surged due to its scalability and monitoring capabilities, which simplify ML processes, save time, reduce error risks, and optimize resources.
Additionally, insights from Reportlinker.com suggest that the global MLOps market could reach $8.5 billion by 2028, achieving a CAGR of 38.9%. Both reports demonstrate a strong and increasing demand for MLOps that is likely to rise further in the coming years.
Top MLOps Staff Outsourcing Firms Worth Considering
Versich
Versich is a recognized data engineering firm that provides comprehensive MLOps staff outsourcing solutions for small to large enterprises globally. Their talent pool includes certified data analysts, data scientists, AI engineers, ML engineers, DevOps specialists, Power BI/Tableau developers, and more, aimed at delivering complete MLOps solutions.
The company also specializes in staff augmentation for MLOps development, big data analytics, business intelligence, AI, ML, natural language processing (NLP), and large language model (LLM) deployment tailored to client needs. Companies aiming to expand their MLOps workforce can partner with Versich to connect with skilled ML engineers. They help minimize expenses and optimize operations through flexible remote and temporary teams.
Clients can opt for dedicated development teams that seamlessly integrate with their existing workforce. Additionally, Versich delivers project-based staffing solutions to ensure timely results, along with a continuous communication loop to foster collaboration.
Unibrix
Unibrix provides a dedicated software development team to assist businesses in sourcing the best IT specialists for their needs. The company facilitates direct communication between experts and enterprises, eliminating intermediary requirements. It also offers customized packages tailored to the specific needs of different organizations.
Unibrix, based in Poland, has over 50 partnerships across various sectors. It covers backend web development, DevOps, MLOps platforms, front-end mobile and cross-platform development for businesses of all sizes across diverse continents. The company guarantees complete transparency and high flexibility in creating both short-term and long-term MLOps teams.
SofterMii
SofterMii, a US-based software development provider, holds numerous certifications from notable bodies like IBM, AWS, Microsoft, and Google. The firm primarily serves industries such as real estate, telecommunications, healthcare, and FinTech. They assure a maximum 15% variation for project delivery timelines and actively provide ongoing maintenance and support.
SofterMii presents flexible cooperation models, enabling companies to access MLOps teams throughout different project stages. Enterprises can either extend existing teams or engage with new ones for project delivery. They also handle project initiation activities, such as market analysis and strategy formation. Full-cycle software development, DevOps, cloud solutions, cybersecurity, and WebRTC development are among the services offered to keep enterprises competitive.
InfuseAI
InfuseAI focuses on creating MLOps tools that assist organizations in optimizing their ML initiatives. They have developed an open-source MLOps platform known as PrimeHub, allowing businesses to build, deploy, and scale ML models effectively. The company provides IT leaders and data scientists to aid clients in adopting and customizing new AI and ML frameworks tailored to their needs across various industries, such as healthcare, IT, and construction.
Offering AI-driven SaaS solutions, InfuseAI facilitates quick and cost-effective adoption of AI and machine learning applications, achieving cost savings of up to 30%. Their MLOps tool is designed for rapid online training and use, with a one-click installation feature to streamline processes and reduce error risks. The company focuses on optimizing data workflows and improving observability, allowing internal teams to concentrate on their primary tasks.
OpenGeeksLab
OpenGeeksLab is an innovative service provider comprising over 65 experts from various domains. This company supports businesses in scaling their software products, applications, and models for a competitive market advantage. With engineers and developers from multiple countries, they cater to a diverse clientele efficiently.
They serve clients in industries such as blockchain, healthcare, FinTech, and supply chain. OpenGeeksLab has extensive software development experience and effectively manages the MLOps pipeline to deliver the expected outcomes. The company offers dedicated teams and staff augmentation services to meet different business demands, along with software modernization and cloud engineering services.
Is MLOps Superior to DevOps?
MLOps can be viewed as a set of best practices, guidelines, and technologies formulated to deploy and manage ML models in production settings. A McKinsey & Company report indicates that MLOps can significantly reduce resource requirements and accelerate ML application production times by up to 80%.
DevOps, conversely, represents a software development approach that establishes a cycle of continuous iteration and improvement within an organization. It aims to eliminate barriers and glitches during product development.
Both MLOps and DevOps promote collaboration, continuous improvement, and ongoing monitoring while supporting experimentation and automation to save on time, costs, and resources. Nevertheless, they are not mutually exclusive. Many companies leverage both methodologies to achieve their objectives.
It cannot be stated definitively that MLOps is superior to DevOps; they serve different purposes despite their similarities. While DevOps enhances collaboration and communication, MLOps provides a simpler framework for managing and overcoming the challenges of building, deploying, and maintaining multiple machine learning models within an organization.
Which Companies Utilize MLOps?
Several leading organizations implement MLOps for various applications. Noteworthy examples include:
Netflix
Netflix employs an in-house open-source ML platform known as Metaflow to enhance and personalize streaming experiences for users.
Holiday Extras
This company utilizes a serverless MLOps implementation process to deliver tailored travel package recommendations to customers.
Uber
Uber relies on its in-house open-source ML platform, Michelangelo, to facilitate seamless interaction among drivers, riders, eaters, and restaurants, ultimately minimizing wait times.
Other notable businesses leveraging MLOps include LUSH, Carbon, Ocado Retail, DoorDash, and Revolut.
Is MLOps the Future of Business?
Recent reports indicate a notable increase in MLOps investment by organizations in 2023. A total of 42% of respondents reported raising their MLOps budgets by 11 to 25%, while 37% increased theirs by 26 to 50%. These figures suggest that MLOps adoption is gaining momentum and will remain essential in the future.
As AI technologies will increasingly fuel business processes, MLOps will become crucial. With an ever-growing number of organizations integrating AI and ML into their core operations, collaborating with MLOps teams can lead to improved decision-making, faster results, enhanced efficiency, and increased revenue for businesses.
Conclusion
Global enterprises have begun embracing MLOps by collaborating with staffing firms to recruit specialized teams for their projects. MLOps consulting companies deliver comprehensive solutions, from goal-setting to ongoing maintenance and monitoring after deployment.
The success of your strategies for adopting AI and ML, along with your digital transformation efforts, will hinge on the expertise of the MLOps staffing partner you select. It is important to carefully assess and compare the services provided by various staffing companies before making your choice. Engaging an MLOps staffing partner for the long term can help position your organization as a leader in the industry.
