Careers
At Deeyook, we are committed to going the distance in the world of location solutions, refining and upgrading our offerings, providing a ubiquitous, scalable, and precise location to meet all current and future use cases.
Join a dynamic team dedicated to developing a breakthrough deep technology!
See if there’s a role for you in our team and send your CV to jobs@deeyook.com
We are looking for a highly motivated and “technologically passionate” hard worker and quick learner to join our team as a Signal Processing Team Candidate.
In this role, you’ll work in a fast-paced and agile development environment, following the industry’s best practices, methodologies and standards.
If this is of interest to you and you have good interpersonal skills and are a team player who is also able to work independently and take responsibility, then keep reading and be in touch!
Responsibilities: What You’ll Be Doing
In this role you will be responsible for meaningful building blocks in our algorithm. You will develop algorithmic solutions to complex signal processing challenges in order to meet our accuracy targets.
Requirements: What You’ll Bring to the Job
Academic degree with a major in communication, signal processing, electronics or systems, advanced degree is advantage.
At least 3 years of work experience in the fields of communication, semiconductors, radars, robotics, IoT or similar, preferably in startup environment. Excellent graduates with advanced degree and with extensive applied research experience in the relevant fields can be considered as well.
Good understanding of DSP algorithms, such as time/frequency synchronization, AGC, RF channel estimation, equalization, decoding, etc.
Previous experience in both algorithm development and implementation (from research and POC to official product release) is highly preferred.
Ability to extensive debug of HW and SW systems, rigorous analysis of experimental data, identification, and analysis of problems
Knowledge in statistical signal processing, estimation theory, statistics is big advantages.
Background and understanding of classical machine learning and statistical data analysis methods is advantage.
Experience with Python scientific stack, Jupyter notebook and Git. Additional experience with C/C++ in RT and embedded environment is advantage.
Highly motivated and “technologically passionate”, hard worker and quick learner, adept of hands-on approach
Good interpersonal skills, team player with good ability to work independently and take responsibility, good references – must.