Applied AI Engineer

Location: Bengaluru

Title :
Applied AI Engineer

Location:

Bengaluru

Experience:

4
-7 years

About the Role

We are looking for a hands-on AI/ML Engineer with strong Backend experience to help us build, scale, and product ionize intelligent systems. This role sits at the intersection of machine learning, data, and backend engineering, and is ideal for someone who enjoys taking models from experimentation all the way to reliable, scalable production systems.

You will work closely with product, data, and engineering teams to design AI-powered features that directly impact customers.

What You’ll Do

- Design, develop, and deploy ML models for real-world use cases (NLP, recommendation, prediction, automation, etc.)
- Build and maintain scalable backend services and APIs to serve ML models in production
- Own the end-to-end ML lifecycle: data preparation, training, evaluation, deployment, and monitoring
- Collaborate with product teams to translate business problems into AI-driven solutions
- Optimize model performance, latency, and reliability in production environments
- Set up ML pipelines, versioning, and monitoring for models and data drift
- Contribute to system architecture and technical decision-making in a fast-moving startup environment

What We’re Looking For

- 4+ years of experience in Backend Engineering and/or Machine Learning
- Strong proficiency in Python (mandatory)
- Solid backend experience with REST APIs, microservices, and system design
- Hands-on experience with ML frameworks (PyTorch, Tensor Flow, scikit-learn, etc.)
- Experience deploying ML models using Docker, cloud services (AWS/GCP/Azure)
- Strong understanding of data structures, algorithms, and databases (SQL/No

SQL)
- Ability to work in ambiguous environments and take ownership end-to-end

Nice to Have

- Experience with LLMs, NLP, or Generative AI (OpenAI, Hugging Face, Lang Chain, etc.)
- Familiarity with MLOps tools (MLflow, Airflow, Kubeflow, etc.)
- Experience in startup or high-growth environments
- Exposure to event-driven systems, message queues, or real-time data pipeline