Machine Learning Engineer
Location:
San Jose , California
Posted:
January 06, 2017
Reference:
R1024670
Additional Location(s) or Information:
Job Category: Engineer - Software
Level of Experience: Experienced - Non Manager
Requisition #: R1024670

Description:

Machine Learning Engineer
Locations: Paris, France - Lausanne, Switzerland - Zurich, Switzerland - San Francisco Bay Area

Team
Our team is made of highly talented engineers with passion for innovation who turn wildly disruptive ideas into products that impact industry at large. We have built one of Cisco's next generation advanced threat detection system by combining cutting-edge machine learning algorithms and architectures with best-in-class networking technologies (with dozens of patents). Now, we are tackling our next challenge and we are looking for agile, pragmatic and talented engineers with deep expertise and hands-on experience in machine learning, software engineering and data science. If technology and innovation is your passion, Cisco is the place for you.

Role and responsibilities :
You will have a multi-faceted role: starting from real use cases, you will cover the full product development cycle from first investigation to the development of novel and scalable prototypes based on machine learning algorithms until the release of the product, interfacing with a wide range of experts in the field. You thrive in a fast-paced, dynamic environment requires a unique blend of innovation and speed of execution.
The role is for highly technical machine learning engineers who combine outstanding oral and written communication skills, an ability to quickly code up prototypes using a large range of tools, algorithms and languages and, most importantly, an ability to autonomously plan and organize their work assignments based on high-level team goals.

Our technology stack includes Python, Scala, Haskell, C++ as well as a wide range of internal tools built on top of Docker, Kubernetes, Cassandra, Kafka, Spark, Hadoop, Pandas and a variety of front-end visualization technologies (D3.js, WebGL, HTML5).

Desired qualifications
• PhD in Engineering degree (computer science, robotics, mathematics, statistics, machine learning)
• Strong background in classical machine learning and graphical models is a must, preferably with 3 to 15 years of industrial experience .
• Knowledge of deep learning, reinforcement learning and natural language processing is a plus.
• Hands-on experience of Linux and Shell scripting, ability to manipulate large-scale structured datasets.
• Outstanding programming skills. Experience in functional programming, reactive and service-oriented architectures is a plus.
• Experience with GPU computing (CUDA) and deep learning libraries (TensorFlow, Caffe, Theano, etc.) is a plus.
• Excellent English spoken and written skills (C1 level) is a must.

About Cisco
The Internet of Everything is a phenomenon driving new opportunities for Cisco and it's transforming our customers' businesses worldwide. We are pioneers and have been since the early days of connectivity. Today, we are building teams that are expanding our technology solutions in the mobile, cloud, security, IT, and big data spaces, including software and consulting services. As Cisco delivers the network that powers the Internet, we are connecting the unconnected. Imagine creating unprecedented disruption. Your revolutionary ideas will impact everything from retail, healthcare, and entertainment, to public and private sectors, and far beyond. Collaborate with like-minded innovators in a fun and flexible culture that has earned Cisco global recognition as a Great Place To Work. With roughly 10 billion connected things in the world now and over 50 billion estimated in the future, your career has exponential possibilities at Cisco.

@CiscoCareers is #hiring #machinelearning
#GD2015
*LI-CB1

Job Type: Experienced
Opportunity Category: Internet of Everything

A little about us:
We are one, big, techie, employee tribe that changes the world while having fun.

Know someone who would be interested in this job? Share it with your network.