Associate Software Engineer

Role Description
AI Engineer
Department
Studio
Location
Bangalore — Hybrid (4 days/week in office)
Experience Required
3–5 years (Mid-Level)
Employment Type
Full-time
Role Summary
We are looking for an AI Engineer to design, build, and deploy production-grade AI/ML and generative AI solutions. You will work at the intersection of software engineering and machine learning to bring intelligent applications to life.
Key Responsibilities
Design and implement machine learning and generative AI solutions to solve real-world business problems.
Build, fine-tune, and evaluate models, including integration with large language models (LLMs) and foundation models.
Develop scalable APIs and services to serve AI models in production environments.
Implement retrieval-augmented generation (RAG) pipelines, prompt engineering, and agentic workflows where applicable.
Collaborate with data engineers and data scientists to ensure high-quality data pipelines for training and inference.
Establish MLOps/LLMOps practices for model versioning, monitoring, and continuous improvement.
Optimize model performance, latency, and cost in production deployments.
Stay current with emerging AI/ML tools, frameworks, and research to drive innovation.
Required Skills & Qualifications
3–5 years of experience in AI/ML engineering or software engineering with a strong ML component.
Strong proficiency in Python and experience with ML/AI frameworks (PyTorch, TensorFlow, Hugging Face).
Hands-on experience building and deploying machine learning models in production.
Experience working with LLMs, embeddings, and vector databases (e.g., Pinecone, FAISS, Weaviate).
Solid understanding of software engineering principles: APIs, version control, testing, and CI/CD.
Experience with cloud AI/ML services (Azure OpenAI, AWS Bedrock/SageMaker, GCP Vertex AI).
Strong problem-solving skills and ability to work in a fast-paced, evolving environment.
Preferred Qualifications (Good To Have)
Experience with agentic frameworks (LangChain, LlamaIndex, or similar).
Exposure to fine-tuning and optimizing open-source LLMs.
Experience with containerization and orchestration (Docker, Kubernetes) for model deployment.
Contributions to open-source AI/ML projects or published research.
Education
Bachelor's or Master's degree in Computer Science, AI/ML, or a related field.

Work arrangement
No