Senior Research Engineer

About Analog

Analog is a catalyst for change across various industries - from global enterprises to the public sector, from healthcare to ecology. Analog's approach to AI ensures that technological advancements are not just about efficiency and convenience, but about enriching human experiences and fostering a more connected and mixed world. Analog is not just building technology; we are crafting a world where technology is an invisible yet indispensable part of our lives. Join us on our journey as we work to build solutions that will empower people to stop living behind the digital world and start remembering how to live in our rainbow-filled analog world.

What Working At Analog Offers

Culture: An open, diverse and inclusive environment with a global vision that encourages personal growth and focuses on ground-breaking, industry-first innovations.

Career: Outstanding learning, development & growth opportunities via structured training programs and innovative, high-tech projects.

Rewards: A competitive remuneration package with a host of perks including healthcare, education support, leave benefits and more.

As a Sr. Research Engineer, you will be responsible for building AI systems that can perform previously improbable tasks or achieve unprecedented levels of performance. We're looking for people with solid engineering skills (for example designing, implementing, and improving a massive-scale distributed machine learning system), writing bug-free machine learning code, and building the science behind the algorithms employed. The most outstanding deep learning results are increasingly attained at a massive scale, and these results require engineers who are comfortable working in large distributed systems.

Responsibilities

• Past experience in creating high-performance implementations of deep learning algorithms
• Have experience working in large distributed systems
• Provide technical perspective to develop ML best practices and influence engineering culture in the team
• Have in depth knowledge of how the machine learning system interacts with systems around it
• Evaluate the tradeoffs of different ML models/systems and deploy best ML practices
• Experience with Data/Feature Engineering, Training, Evaluation and Deployment of ML models
  
  

Qualifications

• Have run at least small-scale ML experiments
• Love figuring out how systems work and continuously come up with ideas for how to make them faster while minimizing complexity and maintenance burden
• Have strong software engineering skills and are proficient in Python
• Comfortable working with researchers to enable them to develop the next generation of models
  
  

If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible.

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