Description :

As an R&D Engineer at MediaMint AI Platform, you'll be at the bleeding edge of AI/ML innovation.

Your mission is to explore, prototype, and validate the next generation of AI capabilities that will power our platform.

You'll work at the intersection of research and product development, turning cutting-edge AI research into practical, production-ready features.

This role is perfect for those who love experimentation, stay current with the latest AI advancements, and want to shape the future of AI automation.

Responsibilities :

- Explore and evaluate new AI models, techniques, and frameworks to identify opportunities for platform enhancement.

- Build rapid proofs-of-concept to validate feasibility of new AI capabilities before full-scale development.

- Prototype novel agent capabilities leveraging LLMs, GenAI, and emerging AI technologies.

- Conduct deep-dive evaluations of AI frameworks and tools (LangChain, LlamaIndex, Hugging Face, etc.

- Experiment with fine-tuning, prompt engineering, RAG architectures, and agent orchestration patterns.

- Collaborate closely with product teams to assess technical feasibility and guide feature roadmaps.

- Document research findings, experimental results, and technical recommendations for engineering teams.

- Stay current with latest AI/ML research papers, frameworks, and industry trends.

Must-Have Requirements:

- 4-7 years of experience in AI/ML engineering or research roles.

- Strong Python programming skills with experience in ML libraries (PyTorch, TensorFlow, scikit-learn).

- Solid AI/ML foundation with hands-on experience in model training, evaluation, and deployment.

- Proven experience working with LLMs and GenAI technologies (GPT, Claude, Llama, etc.

- Research-oriented mindset with ability to read and apply findings from academic papers.

- Strong prototyping skills ability to quickly build and iterate on experimental systems.

- Excellent communication skills to translate complex technical concepts to non-technical stakeholders.

Nice-to-Have Requirements:

- Published research papers or conference presentations in AI/ML domains.

- Active open-source contributions to AI/ML projects or frameworks.

- Advanced degree (Ph.D. or M.S.) in AI/ML, Computer Science, or related field.

- Hands-on experience with LangChain, LlamaIndex, or similar agent frameworks.

- Experience with vector databases and RAG (Retrieval-Augmented Generation) architectures.

- Knowledge of MLOps practices and experiment tracking tools (MLflow, Weights & Biases).

- Familiarity with cloud ML platforms (AWS SageMaker, Google AI Platform, Azure ML).