About this AI Engineer role at Weekday AI
๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐
๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ฒ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ญ๐ฑ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ฒ๐ฌ-๐ญ๐ฑ๐ฌ ๐๐ฃ๐)
Experience: 2+ yrs
Location: Bengaluru, Karnataka, India
Job Type: Full-time
We are looking for a highly capable and curiousย AI / Machine Learning Engineerย to work on advanced AI systems designed to improve the capabilities, reliability, and performance of next-generation models.
The role will focus on buildingย 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 developย reinforcement learning environmentsย for coding and agentic AI applications.
- Build task environments, tools, workflows, and infrastructure that enable AI agents to perform complex real-world activities.
- Developย AI/LLM evaluation frameworks, benchmarks, and testing systemsย 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 withย enterprise dataย 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 inย frontier AI, LLMs, reinforcement learning, AI agents, and model evaluation.
What Makes You a Great Fit
- 2+ years of professional experienceย in AI/ML engineering, software engineering, machine learning, data science, or a related technical field.
- Strong programming skills inย Pythonย and experience building reliable, production-quality software.
- Solid understanding ofย 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 inย 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 withย 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 aboutย frontier AI, autonomous agents, coding agents, reinforcement learning, and next-generation AI systems.