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Description

What if you could shape the future of work and be part of the team that creates the digital workforce of tomorrow, by means of Robotic Process Automation?
In the beginning of the 20th century, Henry Ford had a vision of creating assembly lines and facilitating mass production.
100 years later, UiPath has a grand vision of liberating the human workforce from tedious, boring, repetitive tasks, by means of software robots, artificial intelligence and machine learning.

We’re building cutting-edge process discovery technology capable of understand a company’s workflows through simple observation, radically improving their organizational understanding. Our work encompasses the fields of enterprise software, cloud computing, computer vision, automation and AI.

You will be intricately involved in running analytical experiments methodically, and will regularly evaluate alternate models via theoretical approaches. You’ll be responsible for building and applying the latest in data-mining & ML methodologies in the field, and building and extending the algorithms, developed by you or our data scientists.

You will be working on a cross-functional team of product managers, devops engineers, machine learning engineers, and software engineers for high impact shipping. Being a part of hyper growth startup, you are not afraid of getting your hands dirty and are expected to be a jack of all trades for all steps in the data-mining lifecycle, from featurization, training and benchmarking to experimentation, monitoring and analytics.

Qualification & Educational Requirements
  • Post Graduate / Graduate in computer science or a related field.
  • Overall 5+ years of experience in IT industry with 1+ years working on products built to analyze and identify patterns in data.
  • Able to understand various data structures and common methods in data transformation
  • Good pattern recognition and predictive modeling skills
  • Experience in Python, R or Go.
  • Excited to experiment with new technologies and approaches

Preferred Skills
  • Experience in offline batch processing and/or online real-time stream processing systems.
  • Experience in Anomaly and Cycle detection
  • Knowledge of Machine Learning and interested in working across our entire data science stack including model building, data pipelining, and performance/scale analysis.
Nivel de vechime

Începător

Tip de angajare

Full-time

Ocupație

Inginerie

Sectoare de activitate

Tehnologia informației și servicii informatice

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