Description

Sparklegend is an IT company of the Izertis group dedicated to providing specialized IT services. The Sparklegend structure was created by professionals with years of experience in the new technology sector, and we are growing. The quality standards and high complexity of the solutions require professionalism, so we have a group of technical specialists who help us to work in several areas of our portfolio.
The Izertis Group, headquartered in Gijon, Spain and has more than 20 years of experience in the IT sector, specializes in: technology design and digital transformation, digital services, IT profile search and selection, and development and support of startups with high technological component. The group currently has offices in Spain, Mexico, Peru, Colombia and Portugal; providing services through more than 600 professionals and reaching an annual turnover of more than 41 million euros.

It is to work at Porto

Position Summary:

·         Writes the back-end code for apps, web apps or mobile apps (the code responsible for database updates, event processing logic, various action triggers, etc.);

·         Helps design the infrastructure by specifying the code requirements it must serve;

·         Configures the CI part of software development to speed up the product delivery.

In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the forefront of deep learning technology, prototyping state-of-the-art neural net models and launching these models into production. We value hard workers who have no qualms working with terabyte-scale datasets, who are interested in learning new technologies at all levels of the machine learning stack, and who move fast and take ownership of their projects. Our ideal candidate has experience creating a working machine learning-powered project from the ground up, contributes innovative ideas and ingenious implementations to the team, and is capable of planning out scalable, maintainable data pipelines.

Responsibilities

• Everything involved in applying a ML model to a production use case, including, designing and coding up the neural network, gathering and refining data, training and tuning the model, deploying it at scale with high throughput and uptime, and analyzing the results in the wild in order to continuously update and improve accuracy and speed
• Interface closely with the DevOps team as well as with our internal data labeling services

The person we need

• Have an undergraduate or graduate degree in computer science or similar technical field
• have 1-2 years of machine learning experience
• have successfully trained and deployed a deep learning machine model (image, NLP, video, or audio) into production, with measurably improved performance over baseline, either in industry or as a personal project
• You have strong experience with a high-level machine learning frameworks such as Tensorflow, Keras, or Torch, and familiarity with the others
• You know the ins and outs of Python, especially as it applies to the above ML frameworks
• You are capable of quickly coding and prototyping data pipelines involving any combination of Python, Node, bash, and linux command-line tools, especially when applied to large datasets consisting of millions of files
• You have a working knowledge of the following technologies: C++, Scala/Spark, R, Matlab, SQL, Cassandra, Docker
• You are up-to-date on the latest deep neural net research and architectures, both in understanding the theory and motivations behind the techniques, as well as how to implement them in the ML framework of your choice
• You are comfortable with running and interpreting common statistical tests, and also with common data science techniques including dimensionality reduction and supervised and unsupervised learning
• You have great communication skills and ability to work with others
• You are a strong team player, with a do-whatever-it-takes attitude

please answer to [email protected] with the reference #B492