Senior Deep Learning Research Engineer
HackerRank (company site, opens in a new tab)3–7 yrsBengaluruHybridDirect career pageEst. 30–45 LPA
Posted 3h ago
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Job description
Structured overview of role & requirements
About This Role
- Research and build deep-learning models and neural architectures, including approaches beyond Transformers, plus agentic and tool-augmented reasoning systems.
- Own rigorous experiments, evaluation frameworks, and benchmarks for AI-driven interviewing, fraud detection, and technical-skill evaluation.
- Take research into production-grade systems, optimizing inference latency, efficiency, and memory use.
Minimum Requirements
- Work Experience Required: 3–7 years in Deep Learning, Machine Learning, or Applied AI Research.
- M.Tech., M.S., or Ph.D. in AI/ML or a related discipline.
- Strong foundations in mathematics and deep learning; hands-on PyTorch or JAX model development, including implementing and extending research papers or building neural architectures from scratch.
- Experience with experimental design, model evaluation, benchmarking, and statistical validation; familiarity with distributed computing, GPU acceleration, and scalable ML infrastructure.
Ideal Candidate Profile
- Has research depth beyond applying established models, with evidence such as publications or notable open-source contributions; top-venue publications are a plus.
- Can explore newer architectures and agentic systems, and work on ambiguous problems such as LLM evaluation, fraud detection, or defining new measures of technical skill.
- Has taken models from research to efficient, low-latency production inference, including optimization techniques such as quantization or distillation.