Sr. Software Engineer (AI/ML)
Blackpoint Cyber is seeking a highly skilled and motivated Sr. Software Engineer specializing in AI/ML to join our Innovation R&D team. This role is critical for developing next-generation intelligent systems that solve complex industry problems. You will be responsible for the entire ML lifecycle, from initial data ingestion and feature engineering to model deployment and maintenance at scale. Key responsibilities include designing robust deep learning architectures (NLP, Computer Vision), optimizing models for production efficiency, and collaborating with cross-functional teams to define product requirements. The ideal candidate possesses advanced expertise in Python and major ML frameworks like PyTorch or TensorFlow. This is a fully remote position based out of Canada, offering the opportunity to shape the future of cyber intelligence through machine learning innovation.
(تازہ ترین نوکریاں، سلیبس اور ٹیسٹ کی تیاری کی مکمل معلومات)
Preparing
1500
Question set
200
Duration
Permanent
Focus areas
People Also Ask (FAQs)
What is the last date to apply for Sr. Software Engineer (AI/ML)?
The closing date is listed in the official advertisement — apply as early as possible.
How do I apply for Sr. Software Engineer (AI/ML)?
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 Blackpoint Cyber 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 Sr. Software Engineer (AI/ML) 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: Python, Machine Learning, Deep Learning, NLP, TensorFlow, PyTorch.
Quick start
Review the job summary, then jump into prep with the same flow used for exam starts.