Researcher Software Engineering

Company Description

Dusker AI specializes in evaluating and benchmarking advanced AI systems through rigorous, research-driven methodologies. We partner with organizations developing large language models, AI agents, and autonomous systems to measure performance across reasoning, reliability, adaptability, safety, and domain expertise.

Our evaluation frameworks are designed by subject matter experts and researchers, enabling deeper assessment than traditional benchmarks. By identifying strengths, uncovering failure modes, and testing real-world capabilities, Dusker AI helps organizations build AI systems that are robust, trustworthy, and deployment-ready.

We work across a wide range of domains including mathematics, physics, chemistry, biology, software engineering, and applied sciences, creating high-quality evaluation datasets and benchmark suites that drive the next generation of AI performance.

Role description

Researcher – Software Engineering

Compensation: $20–$25 per accepted task

Location: Remote

Education Requirement: Master's or PhD

Application Requirements

Applicants are strongly encouraged to include links to their Google Scholar profile, ResearchGate profile, ORCID profile, published papers, personal academic website, GitHub profile, or other verifiable research and technical contributions within their CV/Resume.

We are seeking a highly analytical Software Engineering Researcher with strong programming expertise to contribute to the design and evaluation of advanced AI systems. This remote position focuses on developing rigorous software engineering benchmarks, evaluating model reasoning capabilities, and conducting research at the intersection of software engineering, computer science, and artificial intelligence.

The successful candidate will formulate challenging software engineering tasks, develop reference implementations, analyze model behavior, and create evaluation methodologies that measure the accuracy, reliability, maintainability, efficiency, and reasoning abilities of advanced AI systems.

Key Responsibilities

• Design rigorous software engineering benchmark tasks and evaluation frameworks for AI systems

• Develop coding-based tasks involving algorithms, data structures, system design, debugging, testing, code optimization, and software architecture

• Create reference implementations, test suites, and evaluation criteria

• Analyze AI-generated code and identify strengths, weaknesses, reasoning errors, security issues, and failure patterns

• Evaluate model performance on real-world software engineering challenges

• Conduct quantitative research on code generation, software reasoning, and model reliability

• Collaborate with multidisciplinary teams to improve benchmark quality, coverage, and evaluation methodologies

• Document methodologies, findings, and evaluation results through technical reports and research summaries

• Contribute to benchmark datasets, evaluation frameworks, and internal research initiatives

• Stay informed about developments in software engineering, AI evaluation, AI safety, and machine learning

Role Qualifications

Required

• Master's or PhD in Computer Science, Software Engineering, Computer Engineering, Artificial Intelligence, Data Science, or a closely related technical discipline

• Strong foundation in software engineering principles, algorithms, data structures, software architecture, and system design

• Proficiency in one or more programming languages such as Python, Java, C++, JavaScript, Go, Rust, or similar languages

• Experience with software development, testing methodologies, debugging, version control, and code review practices

• Experience with experimental design, data analysis, and technical problem-solving

• Excellent written and verbal communication skills in English

• Ability to work independently in a remote research environment

Preferred

• PhD degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field

• Multiple peer-reviewed publications in recognized journals or conferences

• Experience evaluating AI systems, machine learning models, code generation models, or large language models

• Background in distributed systems, cloud computing, cybersecurity, databases, compilers, operating systems, or software architecture

• Experience developing benchmarks, datasets, evaluation frameworks, or testing platforms

• Familiarity with AI safety, model alignment, AI benchmarking methodologies, or software reliability research

• Experience with tools such as Git, Docker, Kubernetes, CI/CD pipelines, cloud platforms, and modern software engineering workflows

Candidates with strong academic research backgrounds, publication records, software development expertise, and demonstrated excellence in problem-solving, system design, and software engineering are especially encouraged to apply.