AI Algorithms Engineer – Qualcomm, Hod HaSharon, Israel Full Time NEW

Qualcomm Israel Ltd.

Job Area

Engineering Group, Engineering Group > Modem Technologies

General Summary

Role Overview

We are looking for a Senior/Staff AI Algorithms Engineer to join our research and engineering team, focusing on the development, training, and optimization of large-scale language models (LLMs) on distributed networks. The ideal candidate combines deep theoretical understanding with hands-on engineering excellence.

Must-Have Requirements

Education & Experience

• M.Sc. or Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, or a related field
• 5+ years of industry or research experience in machine learning / deep learning
• Demonstrated track record of delivering production-quality ML systems or publishing in top-tier venues (NeurIPS, ICML, ICLR, TMLR, etc.)

Core AI/ML Expertise

• Deep understanding of transformer architectures (encoder-only, decoder-only, encoder-decoder), attention mechanisms, positional encodings (RoPE, ALiBi, etc.), and normalization strategies
• Hands-on experience training large-scale models (1B–70B+ parameters) from scratch
• Familiarity with pre-training, instruction tuning, RLHF, DPO, and related alignment techniques
• Knowledge of model evaluation: perplexity, downstream benchmarks (MMLU, HellaSwag, etc.), and ablation methodology

Distributed Training & Systems

• Strong practical experience with distributed training paradigms:
• Data Parallelism (DDP, FSDP)
• Tensor Parallelism (Megatron-style)
• Pipeline Parallelism
• ZeRO (Stage 1/2/3 with optimizer/gradient/parameter sharding)
• Proficiency with modern training frameworks: PyTorch, DeepSpeed, Megatron-LM, Hugging Face Accelerate / Transformers
• Experience managing large-scale GPU clusters (A100/H100/B200 or equivalent), including job scheduling, multi-node communication (NCCL), and GPU utilization monitoring

Engineering Skills

• Expert-level Python programming; clean, testable, modular code
• Proficiency with data pipelines for LLM pre-training
• Solid understanding of profiling and debugging training runs: loss spikes, gradient norms, throughput bottlenecks (MFU), dead nodes

Strong Advantage (Nice-to-Have)

Research & Innovation

• First/co-author publications in LLM training, efficient transformers, or distributed ML at top venues
• Experience with novel architecture exploration: SSMs (Mamba), MoE, hybrid architectures
• Familiarity with continual learning or domain adaptation
• Experience with federated learning or layer-wise / alternative training strategies

Minimum Qualifications

• Bachelor’s degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 4+ years of Software Engineering, Hardware Engineering, Electrical Engineering, Systems Engineering, or related work experience.

OR

Master’s degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 3+ years of Software Engineering, Hardware Engineering, Electrical Engineering, Systems Engineering, or related work experience.

OR

PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field and 2+ years of Software Engineering, Hardware Engineering, Electrical Engineering, Systems Engineering, or related work experience.

• References to a particular number of years experience are for indicative purposes only. Applications from candidates with equivalent experience will be considered, provided that the candidate can demonstrate an ability to fulfill the principal duties of the role and possesses the required competencies.

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