Job Summary :

We are seeking a skilled and motivated AI/ML Engineer with a background in Natural Language Processing (NLP), speech technologies, and generative AI. The ideal candidate will have hands-on experience building AI projects from conception to deployment, including fine-tuning large language models (LLMs), developing conversational agents, and implementing machine learning pipelines. You will play a key role in building and enhancing our AI-powered products and services.

Key Responsibilities :

- Design, develop, and deploy advanced conversational AI systems, including customer onboarding agents and support chatbots for platforms like WhatsApp.

- Process, transcribe, and diarize audio conversations to create high-quality datasets for fine-tuning large language models (LLMs).

- Develop and maintain robust, scalable infrastructure for AI model serving, utilizing technologies like FastAPI, Docker, and cloud platforms (e.g., Google Cloud Platform).

- Integrate and leverage knowledge graphs and contextual information systems to create more personalized, empathetic, and goal-oriented dialogues.

- Engineer and implement retrieval-augmented generation (RAG) systems to enable natural language querying of internal company documents, optimizing for efficiency and informativeness.

- Fine-tune and deploy generative models like Stable Diffusion for custom asset creation, with a focus on improving precision and reducing generative artifacts (FID score).

- Collaborate with cross-functional teams, including product managers and designers, to build user-friendly interfaces and tools that enhance productivity and user experience.

- Contribute to the research and publication of novel AI systems and models.

Qualifications and Skills :

- Education : Bachelor of Engineering (B.E.) in Computer Science or a related field.

- Experience : 3+ years of relevant professional experience as a Machine Learning Engineer or in a similar role.

Programming Languages :

- Expertise in Python and a strong command of SQL, and JavaScript.

- Machine Learning Libraries : Hands-on experience with PyTorch, Scikit-learn, Hugging Face Transformers, Diffusers, Librosa, LangGraph, and the OpenAI API.

- Software and Tools : Proficiency with Docker and various databases including PostgreSQL, MongoDB, Redis, and Elasticsearch.

Core Competencies :

- Experience developing end-to-end AI pipelines, from data processing and model training to API deployment and integration.

- Familiarity with MLOps principles and tools for building and maintaining production-level machine learning systems.

- A portfolio of projects, publications, or open-source contributions in the fields of NLP, Computer Vision, or Speech Analysis is a plus.

- Excellent problem-solving skills and the ability to think strategically to deliver optimized and efficient solutions.