AI and Full Stack Engineer

AI and Full Stack Engineer

Company: Anvaya Labs Location: Bengaluru (in-person)

About Anvaya Labs

Anvaya Labs is a young, research-oriented startup building technology for critical infrastructure, focused on turning research into systems that work in the field.

About the Role

You'll work across AI, computer vision, and software development, taking ideas from experiments to usable, deployed products. This role sits at the intersection of applied research and engineering — you'll run experiments, build models, and also build the real backend/API/interface layer needed to turn that model into something usable in production, then work with the infrastructure team to deploy and harden it in real-world conditions.

What You Will Do

1. Explore approaches, run experiments, and build AI and computer vision features for real-world problems.
2. Prepare data, train or fine-tune small models, evaluate results, and improve them when they fall short.
3. Build the APIs, backend services, and interfaces needed to turn a model or prototype into a useful application.
4. Deploy your work with the infrastructure team, test it in real field conditions, and improve its reliability and performance.
5. Travel to field sites as needed to test and validate deployments in real conditions.

What We're Looking For

1. Strong programming fundamentals with solid comfort in Python, and some experience building applications across both frontend and backend.
2. A working understanding of core ML concepts — training and evaluation, overfitting, data quality, and choosing the right metrics.
3. A grounding in computer vision with practical, hands-on experience training, adapting, or deploying models — you should be able to explain what you tried and how you validated the results.
4. A basic understanding of how software systems work — processes, memory, networking, databases, and CPU/GPU workloads — enough to debug an issue beyond the model itself.
5. Hands-on exposure to cloud platforms (GCP, AWS, or Azure), Docker, Kubernetes, and experience working with NVIDIA GPUs.
6. Around 2–6 years of relevant experience; strong candidates with personal projects, research, or open-source contributions in lieu of formal experience are welcome. Any educational background/field is fine.
7. Indian citizenship required.