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Senior ML Engineer

79% Flex
EXTRA HOLIDAYS - EXTRA PARENTAL LEAVE
Remote: 
Full Remote
Salary: 
25 - 125K yearly
Experience: 
Mid-level (2-5 years)
Work from: 

Offer summary

Qualifications:

Master’s degree or equivalent experience, 2+ years of full-time industry experience in machine learning, Strong background in machine learning and AI.

Key responsabilities:

  • Develop scalable machine learning algorithms using mainstream frameworks
  • Create and maintain reusable functional components in ML framework
  • Contribute to evaluation framework, benchmarking of models
  • Collaborate with Central Data to create data pipelines
  • Stay abreast of latest ML tools
Analog Devices  logo
Analog Devices Information Technology & Services Large https://www.analog.com/
10001 Employees
See more Analog Devices offers

Job description

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Your missions

Analog Devices, Inc. (NASDAQ: ADI) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, and software technologies into solutions that help drive advancements in digitized factories, mobility, and digital healthcare, combat climate change, and reliably connect humans and the world. With revenue of more than $12 billion in FY22 and approximately 25,000 people globally working alongside 125,000 global customers, ADI ensures today’s innovators stay Ahead of What’s Possible.

The AI Incubation team is looking for experienced Machine Learning Engineers to develop core AI technologies for Analog Devices’ future AI products. Our technologies range from generative AI for electronics to deeply embedded AI models in our silicon. We work across various markets and applications to solve problems beyond the reach of traditional algorithms and circuit innovations.

Responsibilities include:

  • Contribute to the development of scalable machine learning algorithms with mainstream frameworks.
  • Create and maintain reusable functional components in machine learning framework.
  • Contribute to the evaluation framework, benchmarking of models, and management of model lifecycle.
  • Collaborate with Central Data in Analog Devices to create data pipelines for large-scale multimodal datasets.
  • Stay abreast of the latest development of machine learning tools from reputable groups, and experiment and prototype with new machine learning libraries or practices

Qualifications:

  • Master’s degree or equivalent experience.
  • 2+ years of full-time industry experience in machine learning
  • Strong background in machine learning and AI, and experience in:
    • Training custom neural network models with PyTorch
    • Evaluation of neural network models with standard testbeds
    • Optimize data pipeline and data cleaning and standardization
    • Software development for deployable machine learning system

#LI-VD1

For positions requiring access to technical data, Analog Devices, Inc. may have to obtain export  licensing approval from the U.S. Department of Commerce - Bureau of Industry and Security and/or the U.S. Department of State - Directorate of Defense Trade Controls.  As such, applicants for this position – except US Citizens, US Permanent Residents, and protected individuals as defined by 8 U.S.C. 1324b(a)(3) – may have to go through an export licensing review process.

Analog Devices is an equal opportunity employer. We foster a culture where everyone has an opportunity to succeed regardless of their race, color, religion, age, ancestry, national origin, social or ethnic origin, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, parental status, disability, medical condition, genetic information, military or veteran status, union membership, and political affiliation, or any other legally protected group.

Job Req Type: Experienced

          

Required Travel: Yes, 10% of the time

          

Shift Type: 1st Shift/Days

Required profile

Experience

Level of experience: Mid-level (2-5 years)
Industry :
Information Technology & Services
Spoken language(s):
English
Check out the description to know which languages are mandatory.

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