Deep Learning Research Engineer

Hybrid in Bangalore · Hybrid in Bengaluru · 2-3 years experience · Hybrid · Posted Oct 14, 2026

At a glance

HackerRank is seeking a Deep Learning Research Engineer to reinvent technical hiring for the agentic era where AI/ML systems form the core product.
The role involves solving open problems across autonomous AI interviewing, integrity and fraud detection, and technical skill evaluation.
Your focus will shift across high-leverage areas, translating cutting-edge research into scalable, production-grade AI systems.

Research, Design, and Develop advanced Deep Learning models and novel Neural architectures.
Explore architectures beyond Transformers, including State Space Models (SSMs), Liquid Neural Networks (LNNs), and Hybrid approaches.
Design and implement Agentic AI systems, Recursive Reasoning Engines, and tool-augmented architectures.
Fine-tuning of models using PEFT (e.g. LoRA, QLoRA etc.), and Knowledge Distillation.
Optimize model Performance, Inference Efficiency, Latency, and Memory utilization.
Design rigorous experiments, evaluation frameworks, and benchmarks to validate research hypotheses.
Translate cutting-edge research into scalable, production-grade AI systems.

M.Tech./M.S./Ph.D. in AI/ML or related disciplines, preferably from a Tier 1 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.
Proficient in frameworks like PyTorch/JAX, with hands-on model development experience.
Demonstrated ability to implement, reproduce, and extend research papers, including building neural architectures from scratch.
Familiarity with distributed computing, GPU acceleration, and scalable ML infrastructure.
Strong understanding of experimental design, model evaluation, benchmarking, and statistical validation.
Demonstrated research aptitude through publications, open-source contributions etc.

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