Remote opportunity at
HackerRankDeep Learning Research Engineer
This research-heavy position at HackerRank is full-time and remote, based in the US. HackerRank helps employers assess and grow technical talent using skills rather than credentials,…
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About This Role
This research-heavy position at HackerRank is full-time and remote, based in the US. HackerRank helps employers assess and grow technical talent using skills rather than credentials, and its machine learning systems form the core of its product. The engineer will tackle unsolved problems across hiring technology, such as an autonomous AI interviewer that runs and grades technical interviews, detecting cheating and suspicious activity in assessments, and new ways to measure…
Job Description
This research-heavy position at HackerRank is full-time and remote, based in the US. HackerRank helps employers assess and grow technical talent using skills rather than credentials, and its machine learning systems form the core of its product. The engineer will tackle unsolved problems across hiring technology, such as an autonomous AI interviewer that runs and grades technical interviews, detecting cheating and suspicious activity in assessments, and new ways to measure coding ability when AI can generate code.
Day to day, the engineer builds and studies advanced deep learning architectures. The posting looks past standard Transformers toward state space models, liquid neural networks and hybrid approaches. Other work includes creating agentic AI systems and tool-using architectures, adapting large models through parameter-efficient techniques such as LoRA and QLoRA, applying knowledge distillation, improving speed and memory footprint at inference time, designing experiments and benchmarks to test ideas, and converting research into production-ready AI systems.
This role suits an engineer who enjoys open-ended research and questioning accepted assumptions. The posting favors first-principles reasoning and careful experimentation over applying off-the-shelf models. Candidates should hold a graduate degree in AI, machine learning or a related field and have roughly two to three years of applied deep learning or research experience. No salary is stated in the posting.
Responsibilities
- Invent and develop cutting-edge deep learning models and new neural network designs
- Investigate model families that go past Transformers, such as state space models and liquid networks
- Build agentic systems and reasoning pipelines that call external tools
- Adapt models through parameter-efficient fine-tuning and knowledge distillation
- Tune models for performance, inference speed, latency and memory consumption
- Set up rigorous evaluation methods, experiments and benchmarks to test hypotheses
- Move promising research into scalable systems that run in production
Requirements
- Graduate degree (M.Tech., M.S. or Ph.D.) in AI, machine learning or a closely related field, ideally from a top-tier research university
- Around two to three years of applied work in deep learning or related research
- Solid grounding in math and theory: linear algebra, probability, statistics and optimization, plus the principles of deep learning
- Hands-on experience building models in PyTorch or JAX
- Able to reimplement and extend published papers, including constructing neural architectures from the ground up
- Know-how in distributed systems, GPU speedups and large-scale ML infrastructure
- Track record of research output through publications or open-source work, plus careful experiment design and statistical validation
Qualifications
- Papers at premier venues such as NeurIPS, ICML, ICLR or ACL, or noteworthy open-source contributions to architectures or agent systems
- Familiarity with LLM assessment, fraud or anomaly detection, or domains where the reference standard has not been settled
- Experience moving models into low-latency serving via quantization, distillation or inference-serving tuning
Core Skills
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
Is this role remote?
Yes. The posting lists the position as remote and based in the United States.
What experience is required?
The posting asks for a graduate degree in AI, machine learning or a related field and two to three years of deep learning or applied AI research experience.
What is the salary?
The posting does not specify a salary.
What is the employment type?
The position is listed as full-time.
Which technical skills does the role emphasize?
The posting highlights PyTorch or JAX, parameter-efficient fine-tuning methods such as LoRA and QLoRA, and experimental design for model evaluation.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.