Deep Learning Research Engineer

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Deep Learning Research Engineer in Others new

HackerRank
Full time
Email

Others
10/30/2026
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Bengaluru, India

Responsibilities

Research, design, and develop advanced deep learning models and novel neural architectures.
Explore architectures beyond Transformers, including State Space Models, Liquid Neural Networks, and hybrid approaches.
Design and implement agentic AI systems, recursive reasoning engines, and tool-augmented architectures.
Fine-tune models using PEFT methods such as LoRA and QLoRA, and apply knowledge distillation.
Optimize model performance, inference efficiency, latency, and memory utilization.
Design experiments, evaluation frameworks, and benchmarks to validate research hypotheses.
Translate cutting-edge research into scalable, production-grade AI systems.

Requirements

M.Tech., M.S., or Ph.D. in AI/ML or a related discipline, preferably from a premier research institution.
2–3 years of experience in deep learning, machine learning, or applied AI research.
Strong foundations in linear algebra, probability, statistics, optimization, and deep learning algorithms.
Proficiency with frameworks such as PyTorch or JAX and hands-on model development experience.
Ability to implement, reproduce, and extend research papers, including building neural architectures from scratch.
Familiarity with distributed computing, GPU acceleration, and scalable machine learning infrastructure.
Understanding of experimental design, model evaluation, benchmarking, and statistical validation.
Demonstrated research aptitude through publications or open-source contributions.
Preferred experience includes publications at venues such as NeurIPS, ICML, ICLR, or ACL; LLM evaluation; fraud or anomaly detection; and taking models into low-latency production inference through quantization, distillation, or serving optimization.

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