Senior AI Systems Engineer — Distributed ML at Scale

analogai; Abu Dhabi; On-site; AED 420,000 - 780,000; Full time

Benefits offered by this job

Healthcare

Education support

Generous leave

Job summary

Analog is seeking a Sr. Research Engineer to build AI systems capable of previously improbable tasks and achieve unprecedented performance. You’ll design, implement, and improve massive-scale distributed machine learning systems, writing bug-free ML code and advancing the science behind the algorithms employed.

You will work closely with researchers to develop the next generation of models, evaluate tradeoffs, and deploy best ML practices across complex distributed environments.

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

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

Skills

Python

Software engineering

Distributed systems

ML knowledge

Job description

Analog is seeking a Sr. Research Engineer to build AI systems capable of previously improbable tasks and achieve unprecedented performance. You’ll design, implement, and improve massive-scale distributed machine learning systems, writing bug-free ML code and advancing the science behind the algorithms employed.

You will work closely with researchers to develop the next generation of models, evaluate tradeoffs, and deploy best ML practices across complex distributed environments.