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ninjatech.ai

Senior Applied Scientist

NinjaTech.ai is seeking a highly skilled Senior Applied Scientist to join our dynamic Science team. This pivotal role involves taking cutting-edge machine learning research and transforming it into robust, production-grade AI models that power our core products. Key responsibilities include designing novel ML architectures, conducting rigorous experiments, optimizing model performance at scale, and collaborating with engineering teams to ensure seamless deployment. The ideal candidate possesses a strong background in advanced statistics, deep learning frameworks (like PyTorch/TensorFlow), and large-scale data processing. You will play a crucial role in advancing our technical capabilities and solving complex, real-world business problems through advanced computation.

ninjatech.ai Sydney, NSW, Australia, Australia

(تازہ ترین نوکریاں، سلیبس اور ٹیسٹ کی تیاری کی مکمل معلومات)

Preparing

1850

Question set

200

Duration

Permanent

Focus areas

Applied ScienceMachine LearningArtificial IntelligenceDeep LearningPython

People Also Ask (FAQs)

What is the last date to apply for Senior Applied Scientist?

The closing date is listed in the official advertisement — apply as early as possible.

How do I apply for Senior Applied Scientist?

Use the official apply link on this page to submit your application. A step-by-step how-to-apply guide for this job is also linked below.

Is there negative marking in the ninjatech.ai test?

The marking rule is announced per test in the advertisement and roll-number-slip instructions. Many MCQ screening tests have no negative marking, but always verify it for your specific test.

What is the passing marks for this test?

The official passing marks are generally 50%, but merit is competitive — scoring above 75% is a safer target to secure an interview call.

How can I prepare for the Senior Applied Scientist test?

Prepare with the free subject-wise MCQs, past papers and timed mock tests on PrepPro Academy — every question includes the answer with an explanation. Focus areas: Applied Science, Machine Learning, Artificial Intelligence, Deep Learning, Python.

Quick start

Review the job summary, then jump into prep with the same flow used for exam starts.

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