Data Scientist - Artificial Intelligence/Machine Learning (5-8 yrs)

About Maino.ai :

Maino.ai is at the forefront of revolutionising marketing automation through its end-to-end automated, intelligent, and ROI-driven martech platform. Leveraging cutting-edge Machine Learning (ML) and Generative AI technologies, we are committed to providing a one-stop solution that addresses all the marketing needs of organisations. Our mission is to build the world's most reliable and innovative technology platform, transforming the digital marketing sector into a cost-efficient and accessible domain for everyone.

Job Description :

At Maino.ai, we are seeking talented folks with 5+ years of experience in AI/ML with comprehensive understanding of the ML models ecosystem. This role offers a unique opportunity for someone passionate about pushing the boundaries of technology and thriving in a dynamic environment.

Qualifications :

Must-Have :

- Proficiency in Python and libraries like TensorFlow, PyTorch, Transformers, and LangChain.

- Solid understanding of NLP techniques, including tokenization, embeddings, and model

fine-tuning.

- Hands-on experience with designing APIs and integrating AI models into production
systems.

- Strong knowledge of machine learning fundamentals and evaluation metrics for conversational AI.

- Excellent problem-solving skills with a focus on delivering scalable and maintainable
solutions.

- Strong experience with Large Language Models (LLMs) and frameworks such as OpenAI
APIs, Hugging Face, or similar tools. (At least 1 year development experience)

Good-to-Have :

- Experience in deploying ML models in cloud environments (AWS, Azure, GCP).

- Exposure to tools like Docker, Kubernetes, or other container orchestration systems.

- Prior experience in developing multimodal conversational systems.

Responsibilities :

- Implement scalable data pipelines for processing and indexing large corpora of
documents for retrieval systems.

- Research and apply advanced techniques in prompt engineering, few-shot learning, and
knowledge integration to improve conversational and retrieval quality.

- Collaborate with other engineering teams.

- Conduct rigorous A/B testing, monitor key performance indicators (KPIs), and iteratively
optimise system performance.

- Stay updated with the latest advancements in natural language processing (NLP) and
machine learning to continuously innovate solutions.

- Ensure data privacy, ethical AI principles, and compliance with security standards in all model and systems.