Research Engineer: Machine Learning

Job Title: Research Engineer: Machine Learning

Duration: Longterm Contract

Location: Burlingame, CA

Pay Range: $70-$80/hr

Intelliswift Software Inc. conceptualizes, builds, and supports the world's most amazing technology products and solutions. Our team of rich experts from diverse backgrounds contributes to making Intelliswift one of the most reliable partners in IT and Talent solutions. We specialize in delivering world-class Digital Product Engineering, Data Management and Analytics, and Staffing Solutions services to Fortune companies, SMBs, ISVs, and fast-growing startups.

: (contingent worker) Job title: Research Engineer: Machine Learning

OnSite Burlingame, CA

Description:

We are looking for a skilled and motivated machine learning research engineer, to develop and

apply state-of-the-art machine learning techniques for wristband/hand-based gesture inputs to

deliver seamless experiences for humans — specifically, to develop online learning and

reinforcement learning techniques that improve gesture recognition models in real time to

achieve all-day high performance.

Responsibilities:

• Develop or apply state-of-the-art reinforcement learning and online

learning algorithms that improve model accuracy in real-time for everyday usage.

• Collaborate with research engineers and scientists in building software

platforms, for both data analysis and real-time experience of human-system interactions;

deploy and evaluate the online algorithms in real usage.

Minimum qualifications:

• Has a BS with 4+ years of experience or MS with 2+ years of experience

or PhD with 1+ years of experience in Machine Learning, Robotics, Statistics,

Biomedical Engineering, Neuroscience, Computer Science, Signal processing or a related

area.

• Has 2+ years experience coding in Python, Pytorch, with proven track

record of implementing and deploy Machine Learning algorithms

• Has 1+ years experience with deep learning

Preferred qualifications:

• Has 1+ years of experience in any of the following domains: (deep)

reinforcement learning, online learning, bayesian optimization (active learning) or semisupervised learning