AI Product Manager

Weekday AI; Bengaluru; On-site; INR 5,000,000 - 150,000,000; Full time

Job summary

Weekday AI is seeking an AI/ Machine Learning Engineer in Bengaluru to advance frontier AI models. You will design RL environments for coding and reasoning, build evaluation tooling, and contribute to datasets and pipelines for enterprise data.

The role emphasizes experimentation, depth, and collaboration with researchers and engineers.

Qualifications

• 1+ years of experience in software engineering, machine learning, AI research, data science, or related technical field.
• Strong programming skills in Python and the ability to build reliable, maintainable software.
• Bachelor's or Master's degree preferred in Computer Science, AI, ML, Mathematics, Engineering, or related discipline.

Responsibilities

• Design and develop reinforcement learning environments for coding, reasoning, and agentic AI applications.
• Build tools, workflows, and infrastructure to evaluate the capabilities and limitations of advanced AI models.
• Develop and maintain LLM evaluation frameworks, benchmarks, and test environments.

Skills

Python

Generative AI

LLMs

Reinforcement learning

AI agents

Data processing

APIs & cloud

Git

Education

Bachelor's/Master's degree in CS/AI/ML/Math/Engineering

Tools

Git

APIs

Databases

Cloud platforms

Python

Job description

This role is for one of the Weekday's clients

Salary range: Rs 5000000 - Rs 150000000 (ie INR 50-1500 LPA)

Experience: 1+ yrs

Location: Bengaluru, Karnataka, India

Job Type: Full-time

We are looking for a highly motivated AI / Machine Learning Engineer to work on advanced AI initiatives focused on improving the capabilities, reliability, and performance of frontier AI models. The role involves building and evaluating sophisticated AI systems across areas such as reinforcement learning, coding environments, agentic workflows, model evaluations, and high-quality enterprise data.

The ideal candidate will be excited by rapidly evolving AI technologies and comfortable working on complex, open-ended problems where experimentation, technical depth, and strong problem-solving skills are essential.

Requirements

Key Responsibilities

• Design and develop reinforcement learning environments for coding, reasoning, and agentic AI applications.
• Build tools, workflows, and infrastructure to evaluate the capabilities and limitations of advanced AI models.
• Develop and maintain LLM evaluation frameworks, benchmarks, and test environments.
• Work on coding agents and agentic systems involving multi-step reasoning, tool use, planning, and task execution.
• Develop high-quality datasets and enterprise data pipelines for AI training, evaluation, and model improvement.
• Analyse model outputs and identify failure modes, behavioural patterns, and opportunities for improvement.
• Design experiments to measure model performance across accuracy, reasoning, reliability, safety, and task completion.
• Build prototypes and proof-of-concepts using modern AI and machine learning techniques.
• Develop Python-based tools, services, and automation to support AI research and engineering workflows.
• Collaborate with AI researchers, software engineers, data specialists, and product teams on complex technical problems.
• Translate research ideas and experimental findings into scalable engineering solutions.
• Improve the quality, reliability, and efficiency of AI evaluation and data-generation processes.
• Contribute to technical documentation, experiment design, analysis, and knowledge sharing.
• Stay current with developments in LLMs, reinforcement learning, AI agents, model evaluation, and generative AI.

What Makes You a Great Fit

• 1+ years of experience in software engineering, machine learning, AI research, data science, or a related technical field.
• Strong programming skills in Python and the ability to build reliable, maintainable software.
• Strong interest in Generative AI, LLMs, AI agents, and frontier model development.
• Understanding of machine learning fundamentals, model training, evaluation, and experimentation.
• Familiarity with reinforcement learning concepts and environments is highly desirable.
• Experience with LLM evaluation, benchmarking, prompt engineering, or AI application development is an advantage.
• Exposure to agentic AI systems, tool calling, multi-step workflows, or autonomous task execution is desirable.
• Strong analytical and problem-solving skills with the ability to investigate complex model behaviours.
• Ability to work with structured and unstructured datasets and develop data-processing workflows.
• Experience with APIs, Git, databases, cloud platforms, or modern software development practices is a plus.
• Strong curiosity and willingness to work with rapidly evolving AI technologies.
• Comfortable working on ambiguous problems and iterating quickly through experimentation.
• Excellent communication and collaboration skills with the ability to work effectively across research and engineering teams.
• A Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Mathematics, Engineering, or a related discipline is preferred.