Data Scientist/ML Engineer
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.
Here's what you would be doing at UiPath:
Build, Improve and extend deep learning/reinforcement capabilities for computer vision, NLP and workflows. Research and evaluate new/different AI approaches to business problems. Help the team to build powerful and scalable models along with the right infrastructure choices to take these models from research to production. We are one of the few companies in the world working on real AI problems, have teams interfacing directly with the customers and have the customers ready to use the things we build. As an ML expert you would have a rare opportunity to make real-world impact and not just work on notional/synthetic problems.
Role & Responsibilities:
You will work with our team of experts in machine learning and software engineering to do the following:
- Use machine learning & deep learning techniques to create new, scalable solutions for business problems.
- Develop NLP, NLU, NLG, NER, computer vision models and technologies for acquiring, parsing, interpreting and visualizing structured and unstructured data
- Running regular benchmarking tests and perform statistical analysis, draw conclusions on the impact of your research-based optimizations to provide thought leadership to the team
- Analyze and extract relevant information from large amounts data to help in automating the workflows and optimizing key processes.
- Help the team in building large scale online learning system.
- Help the team to build research to production pipeline.
- Stay current with the latest research and technology and communicate your knowledge throughout the enterprise
- Come up with patentable ideas to provide us competitive advantage.
Qualifications & Education Requirements
- Post Graduate / Graduate in computer science or a related field and a strong math background.
- Overall 8+ years of experience in IT industry with 2-4 years working on Machine Learning & Statistics projects.
- Experience working with Machine Learning pipelines - data ingestion, feature engineering, modeling, predicting, explaining, deploying and monitoring ML models.
- Strong knowledge and 3-5 years of hands on experience with Java, Python, R, C / C++ or similar scripting languages and general software development skills (source code management, debugging, testing, deployment, etc.)
- Experience with one or more open-source toolkits such as CoreNLP, OpenNLP, NLTK, OpenCV etc.
- Experience with one or more Deep Learning frameworks like TensorFlow, PyTorch, CNTK, Caffe, Keras, DeepLearning4J etc.
- Experience with GIT, REST APIs, containerization/container management.
- Experience with Azure, GCP and/or AWS.
- PhD in Computer science or related field with focus on Deep Learning.
- Experience building Neural Networks for object detection/recognition, image classification, image segmentation, handwriting recognition.
- Experience with continuous learning & transfer learning.
- Experience with big data frameworks like Cloudera, Spark, Bigquery, & Kafka.
- Familiarity with large data sets, cloud-based development and deployment, open source practices and frameworks and experience in putting AI applications in production.
- Publications in top conferences such as NIPS, CVPR, ICLR, ICML
We are offering the possibility to work from home or flexible working hours in a nice office plus free daily premium catering. Healthcare plan.
Competitive salary, a Stock Options Plan and the unique opportunity of working with us to develop state-of-the-art robotics technology are just a few of the pluses.
We must have caught your attention by now if you've read so far, so we must connect.