Data Scientist - Machine Learning/Artificial Intelligence (2-5 yrs)

Job Description :

At Maino.ai, we are seeking talented folks with 2-3 years of experience in AI/ML with a 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.

Responsibilities :

- Design, develop, and deploy chatbot solutions leveraging state-of-the-art LLMs (e. g., OpenAI GPT, Cohere, Anthropic Claude).

- Build RAG pipelines by integrating LLMs with retrieval systems such as vector databases (e. g., Pinecone, Weaviate, or FAISS).

- Fine-tune pre-trained LLMs on domain-specific datasets for improved task performance and alignment with business goals.

- 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 engineering teams to integrate chatbot and RAG systems into production environments.

- Conduct rigorous A/B testing, monitor key performance indicators (KPIs), and iteratively optimize 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 models and systems.

Requirements :

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

- Expertise in building retrieval systems, including vector search techniques using FAISS, Pinecone, or Elasticsearch.

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

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

Good-to-Have :

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

- Familiarity with knowledge graphs, ontologies, and other knowledge management systems.

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

- Knowledge of reinforcement learning techniques (e. g., RLHF) for chatbot optimization.

- Prior experience in developing multimodal conversational systems.