By Natalia Cohn

So, we are a machine learning company and therefore we write a lot about technical stuff. Still, there is much more to say besides that. 

In this article, you will get a glimpse of what Marvik is, what we work at, how we approach problems as a team, and the way in which we grow our partnerships with clients and allies. When you’re done, we hope you’ll have a better sense of who we are and how we could help you achieve your business goals.


Who we are: Marvik in a Nutshell

For those who don’t know us, at Marvik we are a hands-on machine learning consulting firm. This means we love to roll up our sleeves to fully deliver end-to-end projects, mainly those involving Computer Vision, Natural Language Processing and Predictive Analytics. 

We help organizations identify opportunities, leverage their information and make data-driven decisions that will ultimately transform their business. In some cases, they reach us to develop a new machine learning powered product, introducing innovative features that turn out to be a source of competitive edge. In others, the client has an internal IT team and looks to introduce specific expertise in terms of machine learning. Alternatively, they might be needing to speed up an existing AI development with an external team. In any case, we are always dealing with state-of-the-art projects that involve tons (tons!) of research.


What we do: Experience & Use Cases 

It may sound pretentious, but we aim to solve problems that no one else has solved before. This is because the clients we work with have highly specific needs, related to their particular data and processes. 

As we’ve just mentioned, we focus on projects that involve:

  • Computer vision: we use deep learning and other state-of-the-art algorithms to gain valuable insights from images and videos as well as to manipulate and generate new data using GAN networks. We’ve worked with architectures such as StyleGAN, AlphaPose and Pix2pix.
  • Natural Language Processing (NLP): By leveraging the latest technologies in Machine and Deep Learning and state-of-the-art algorithms like Transformers, we’re able to improve search results, analyze opinions and comments on social media, structure information from natural text and more. We’ve worked with architectures such as Transformers & BERT, GPT-2 & GPT-3 and Pegasus. 
  • Predictive analytics: using tools such as SageMaker, Neo4j and Shapash, we help organizations identify underlying patterns not visible to the human eye to solve prediction and classification problems, as well as key business metrics. 

To give you an idea of the type of projects we work on, we have listed some of them below:

  • autonomous vehicles
  • virtual clothing try-on and size recommending solutions for retail
  • deepfakes and automatic translation for education
  • failure detection & preventive maintenance for industry 4.0
  • 3D avatar creation & facial ageing system
  • electronic health record in healthcare
  • candidate to job recommendation engine

Who we partner with: Clients & Allies

Our clients belong to a wide range of industries, including retail, technology, logistics, heavy industry, education and health. We have worked with large enterprises as well as startups still in stealth mode. This experience has allowed us to learn what works and what doesn’t in different real-life scenarios and has prepared the ground for us to help any new client.

For any project we get involved in, we always like to set achievable near term milestones without neglecting the long term. This means that we look to add immediate business value, while also aiming to build long-term partnerships that help our clients discover and implement their AI-related vision.  

This customer-centric approach requires not only a high degree of technical expertise but also the ability to understand our client’s business and concerns, so we can quickly identify how to build the right solution. 

To that end, we have built a network of allies that support us in our day-to-day operations. We are proud members of Google Developer Expert, NVIDIA Inception, AWS Activate, Microsoft for Startups and 500 Startups programs

Who we work with: The Team

By now, you surely have a better sense of who we are. However, in order to understand how we manage to overcome all the aforementioned, we need to talk about our people. 

We have a fast-growing, world class team that is ready to tackle high complexity problems at an incredibly fast pace. A group of machine learning specialists, data scientists, data engineers and full stack developers that is constantly learning in order to deliver state-of-the-art solutions built upon a wide range of disruptive technologies. MLOps, neural networks optimization, transformer networks and edge computing are just a few of the things the team is working on right now.

We not only set out to hire the best talent out there, but also look to train professionals transitioning from other positions or who have never worked in this field. In this regard, we recently launched the Machine Learning School, an initiative aimed at students and professionals looking to enter the field in a practical and experience-based way. Those who take part embark on a journey to learn concepts of Computer Vision, Natural Language Processing, Predictive Analysis and MLOps -among others-, in a part-time or full-time internship modality. You can read more about this initiative here.

We put a lot of effort into building a culture that promotes autonomy, initiative, diversity and collaboration. We know this is the only way we can build a high-performance team. Click here to know what we look for in a candidate. 

Final thoughts 

We hope this overview has given you some highlights of our experience and how we can help you achieve your business goals.

If you have an idea but are not sure about the next steps, reach out to [email protected] and we can help you with an AI product discovery to kick off the project. On the other hand, if you already know what you need and have access to the right data, we can help you transform that into a reality, building an MVP, getting that to production and then scaling it up. 

It’s an exciting time to be working with AI. Don’t miss out!


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