Founding Engineer

We are looking for a Founding Engineer - ML Lead to build and lead our Machine Learning practice from 01This is a highly hands-on leadership role for an ML expert who can work across core ML, Reinforcement Learning, feedback-loop engineering, ML infrastructure, and production systems. You will define the technical direction for ML, build foundational ML capabilities, establish engineering practices, and work closely with product and engineering teams to take ML systems from research to production.
Responsibilities:
Own the 01 journey of the ML practice, including architecture, technology choices, processes, and engineering standards.
Design, develop, and deploy core ML models and algorithms for production use cases.
Build and improve Reinforcement Learning (RL), feedback-loop, and learning-from-interaction systems.
Design feedback mechanisms that continuously incorporate user/production signals into model evaluation, training, and decision-making.
Partner closely with ML Platform / MLOps / Infrastructure teams to build scalable ML systems and deployment pipelines.
Establish ML infrastructure, experimentation frameworks, model training pipelines, evaluation systems, monitoring, and observability.
Lead and mentor ML engineers/data scientists while remaining hands-on with implementation and architecture.
Translate research ideas and emerging ML techniques into reliable production systems.
Drive experimentation, benchmarking, model evaluation, and continuous improvement.
Collaborate with Product, Engineering, and leadership teams to define and execute the ML roadmap.
Establish best practices around model quality, reproducibility, experimentation, deployment, monitoring, and responsible AI.
Requirements:
6+ years of experience in Machine Learning, AI, or related engineering roles.
Strong hands-on expertise in core ML, including model development, training, evaluation, optimisation, and productionization.
Proven experience with Reinforcement Learning (RL) and/or feedback-loop engineering.
Experience building ML systems that learn from user interactions, behavioural signals, rewards, or production feedback.
Demonstrated experience working across the full ML lifecycle, from experimentation/research to production deployment.
Experience working closely with or leading teams responsible for ML Platform, MLOps, ML Infrastructure, or distributed ML systems.
Proven experience taking an ML function, platform, or practice through a 01 journey within a company.
Strong programming skills in Python and familiarity with modern ML frameworks such as PyTorch, TensorFlow, JAX, or equivalent.
Strong understanding of ML systems, experimentation, data pipelines, model serving, monitoring, and evaluation.
Ability to operate as a hands-on technical leader while building and mentoring a high-performing ML team.
Strong Signals / Preferred Qualifications:
Experience at a high-growth AI/ML company, AI-first startup, or strong technology organisation.
Strong academic background, particularly from top-tier institutions such as IITs, with strong academic performance.
Research publications or papers on arXiv, particularly in ML, RL, Generative AI, recommendation systems, optimisation, or related areas.
Contributions to open-source ML/AI projects.
Experience designing ML systems at significant production scale.
Experience building ML teams, hiring engineers/researchers, and establishing ML engineering practices from scratch.
Experience with distributed training, GPU infrastructure, model optimisation, or large-scale ML platforms.
Good to Have:
The ideal candidate is a builder and technical leader who combines:
Core ML expertise + RL / Feedback Loops + ML Infrastructure + 01 ML Leadership.
You should be comfortable going from we don't have an ML capability yet " to designing the architecture, writing the first models, establishing the ML platform, building the team, and taking the system into production.

Skills
JAX, ML, ML infrastructure, MLOps, PyTorch, Python, RL, TensorFlow, distributed ML, machine learning, reinforcement learning

Experience
4-8 yrs