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Clera

AI/ML Engineer

Clera is seeking a talented AI/ML Engineer to join our core engineering team. You will be instrumental in designing, building, and deploying sophisticated machine learning models that power our key products. Key responsibilities include developing production-ready ML pipelines, optimizing model performance for scale, and collaborating with cross-functional teams to integrate AI solutions. Ideal candidates possess a strong academic background (MS/PhD preferred) and hands-on experience with major deep learning frameworks like PyTorch or TensorFlow. Proficiency in Python is mandatory, alongside knowledge of cloud platforms (AWS/GCP). This role requires meticulous attention to data integrity and an eagerness to tackle complex, ambiguous technical challenges that drive product innovation.

Clera San Francisco, CA, United States

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

Preparing

1800

Question set

250

Duration

Permanent

Focus areas

Machine LearningDeep LearningPythonTensorFlow/PyTorchModel Deployment

People Also Ask (FAQs)

What is the last date to apply for AI/ML Engineer?

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

How do I apply for AI/ML Engineer?

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 Clera 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 AI/ML Engineer 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: Machine Learning, Deep Learning, Python, TensorFlow/PyTorch, Model Deployment.

Quick start

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

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