

Company Description
Appiness Interactive Pvt. Ltd. is a Bangalore-based product development and UX firm that
specializes in digital services for startups to fortune-500s. We work closely with our clients to
create a comprehensive soul for their brand in the online world, engaged through multiple
platforms of digital media. Our team is young, passionate, and aggressive, not afraid to think
out of the box or tread the un-trodden path in order to deliver the best results for our clients.
We pride ourselves on Practical Creativity where the idea is only as good as the returns it
fetches for our clients.
Key Responsibilities:
- Design and implement advanced AI/ML models and algorithms to address real-world challenges.
- Analyze large and complex datasets to derive actionable insights and train predictive models.
- Build and deploy scalable, production-ready AI solutions on cloud platforms such as AWS, Azure, or GCP.
- Collaborate closely with cross-functional teams, including data engineers, product managers, and software developers, to integrate AI solutions into business workflows.
- Continuously monitor and optimize model performance, ensuring scalability, robustness, and reliability.
- Stay abreast of the latest advancements in AI, ML, and Generative AI technologies, and proactively apply them where applicable.
- Implement MLOps best practices using tools such as MLflow, Docker, and CI/CD pipelines.
- Work with Large Language Models (LLMs) like GPT and LLaMA, and develop Retrieval-Augmented Generation (RAG) pipelines when needed.
Required Skills:
- Strong programming skills in Python (preferred); experience with R or Java is also valuable.
- Proficiency with machine learning libraries and frameworks such as TensorFlow, PyTorch, and Scikit-learn.
- Hands-on experience with cloud platforms like AWS, Azure, or GCP.
- Solid foundation in data structures, algorithms, statistics, and machine learning principles.
- Familiarity with MLOps tools and practices, including MLflow, Docker, and Kubernetes.
- Proven experience in deploying and maintaining AI/ML models in production environments.
- Exposure to Large Language Models (LLMs), Generative AI, and vector databases is a strong plus.

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