饾棫饾椀饾椂饾榾 饾椏饾椉饾椆饾棽 饾椂饾榾 饾棾饾椉饾椏 饾椉饾椈饾棽 饾椉饾棾 饾榿饾椀饾棽 饾棯饾棽饾棽饾椄饾棻饾棶饾槅'饾榾 饾棸饾椆饾椂饾棽饾椈饾榿饾榾
饾棪饾棶饾椆饾棶饾椏饾槅 饾椏饾棶饾椈饾棿饾棽: 饾棩饾榾 饾煵饾煬饾煬饾煬饾煬饾煬饾煬 - 饾棩饾榾 饾煭饾煴饾煬饾煬饾煬饾煬饾煬饾煬 (饾椂饾棽 饾棞饾棥饾棩 饾煵饾煬-饾煭饾煴饾煬 饾棢饾棧饾棓)
Experience: 2+ yrs
Location: Bengaluru, Karnataka, India
Job Type: Full-time
We are looking for a highly capable and curious AI / Machine Learning Engineer to work on advanced AI systems designed to improve the capabilities, reliability, and performance of next-generation models.
The role will focus on building reinforcement learning environments, coding and agentic workflows, AI evaluation systems, and enterprise data solutions. You will work on challenging technical problems that contribute to the development and improvement of frontier AI models.
Requirements
Key Responsibilities
- Design and develop reinforcement learning environments for coding and agentic AI applications
- Build task environments, tools, workflows, and infrastructure that enable AI agents to perform complex real-world activities
- Develop AI/LLM evaluation frameworks, benchmarks, and testing systems to measure model capabilities and behaviour
- Create datasets, test scenarios, and evaluation pipelines for advanced AI models
- Analyse model performance and identify gaps, failure modes, and opportunities for improvement
- Work with enterprise data to support AI training, evaluation, experimentation, and model development
- Build scalable data-processing pipelines, APIs, tools, and supporting infrastructure for AI workflows
- Develop and experiment with agentic architectures, tool-use workflows, and emerging AI techniques
- Automate repetitive evaluation, data-processing, and experimentation workflows
- Collaborate with ML researchers and engineers to translate research ideas into robust software systems
- Troubleshoot complex issues across AI applications, data pipelines, evaluation systems, and infrastructure
- Conduct experiments, analyse results, and iterate rapidly based on findings
- Contribute to technical design discussions, documentation, testing, and engineering best practices
- Stay current with developments in frontier AI, LLMs, reinforcement learning, AI agents, and model evaluation
What Makes You a Great Fit
- 2+ years of professional experience in AI/ML engineering, software engineering, machine learning, data science, or a related technical field
- Strong programming skills in Python and experience building reliable, production-quality software
- Solid understanding of machine learning, LLMs, Generative AI, or reinforcement learning
- Hands-on experience with AI agents, agentic workflows, LLM applications, or tool-using systems is highly desirable
- Strong interest in AI evaluation, benchmarking, model behaviour, and performance improvement
- Experience working with datasets, data pipelines, APIs, or large-scale data-processing systems
- Strong software engineering fundamentals, including testing, debugging, Git, and scalable system design
- Ability to work effectively on ambiguous, research-oriented, and technically challenging problems
- Strong analytical and problem-solving abilities with a willingness to experiment, iterate, and learn quickly
- Ability to collaborate effectively with AI researchers, ML engineers, software engineers, and technical stakeholders
- Strong communication skills with the ability to explain technical approaches, findings, and trade-offs clearly
- Genuine curiosity about frontier AI, autonomous agents, coding agents, reinforcement learning, and next-generation AI systems