Location
In office (Bengaluru)
Employment
Full-Time
Overview
Company
Impact
Profile match
Weekday is an Indian recruitment company that sources software engineers through referrals from other engineers rather than through job advertisements or agency databases. Its model pays working engineers to vouch for former colleagues they rate, turning informal knowledge about who is genuinely good into a searchable candidate pool that companies can hire from. Based in Bengaluru and backed by Y Combinator, the platform has layered AI screening and outbound sourcing on top of that referral network, and sells to startups and technology companies hiring in the Indian market.
'
: - ( - )
Experience: 2+ yrs
Location: Bengaluru
Job Type: Full-time
We are looking for an innovative and technically strong AI / Machine Learning Engineer to contribute to the development of advanced AI systems and applications in collaboration with frontier AI research teams.
The role will focus on building reinforcement learning environments, agentic AI systems, evaluation frameworks, and enterprise data solutions that help improve the capabilities, reliability, and real-world performance of next-generation AI models.
Requirements
Key Responsibilities
- Design and develop reinforcement learning (RL) environments for coding and agentic AI applications.
- Build tools, workflows, and infrastructure that enable AI agents to perform and learn from complex tasks.
- Develop robust LLM and AI evaluation frameworks to assess model capabilities, quality, reliability, and behaviour.
- Create benchmarks, test scenarios, datasets, and evaluation pipelines for advanced AI systems.
- Work with enterprise and domain-specific data to support AI model development and evaluation.
- Develop scalable software systems and APIs to support AI experimentation and production workflows.
- Analyse model outputs, identify performance gaps, and develop approaches to improve AI system behaviour.
- Experiment with agentic architectures, tool use, reasoning workflows, and emerging AI techniques.
- Collaborate closely with ML researchers and engineers to translate research concepts into working systems.
- Build automation and data-processing pipelines to improve the efficiency and scalability of AI workflows.
- Troubleshoot complex technical issues across data, models, evaluation systems, and application infrastructure.
- Contribute to technical design, experimentation, documentation, 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 software engineering, machine learning, AI engineering, or a closely related technical field.
- Strong programming skills in Python and experience building production-quality software.
- Solid understanding of machine learning, LLMs, generative AI, or reinforcement learning.
- Experience working with AI agents, agentic workflows, LLM applications, or tool-using systems is highly desirable.
- Strong interest in AI evaluation, benchmarking, model behaviour, and improving AI system performance.
- Experience working with datasets, data pipelines, APIs, or large-scale data-processing systems.
- Strong software engineering fundamentals, including testing, debugging, version control, and scalable system design.
- Ability to work effectively on ambiguous, research-oriented, and technically complex problems.
- Strong analytical and problem-solving skills with a willingness to experiment and iterate quickly.
- Ability to collaborate closely with researchers, engineers, and cross-functional technical teams.
- Strong communication skills and the ability to clearly explain technical approaches, findings, and trade-offs.
- A strong curiosity about frontier AI, autonomous agents, coding agents, reinforcement learning, and next-generation AI systems.
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