Artificial Intelligence Engineer

Job Description

About AiSensy

AiSensy is a WhatsApp based Marketing & Engagement platform helping businesses like Adani, Delhi Transport Corporation, Yakult, Godrej, Aditya Birla Hindalco., Wipro, Asian Paints, India Today Group Skullcandy, Vivo, Physicswallah, Cosco grow their revenues via WhatsApp.

- Enabling 100,000+ Businesses with WhatsApp Engagement & Marketing
- 400Crores + WhatsApp Messages done between Businesses and Users via AiSensy per year
- Working with top brands like Delhi Transport Corporation, Vivo, Physicswallah & more
- High Impact as Businesses drive 25-80% Revenues using AiSensy Platform
- Mission-Driven and Growth Stage Startup backed by Marsshot.vc, Bluelotus.vc & 50+ Angel Investors

About the Role

We are seeking a highly skilled and innovative AI/ML Engineer to join our dynamic team. In this role, you will design, develop, and deploy cutting-edge artificial intelligence (AI) solutions, leveraging advanced machine learning (ML) techniques and AI frameworks to address complex business challenges. You will work closely with cross-functional teams to build intelligent systems and drive innovation, with a focus on implementing and optimizing modern AI technologies such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI Agents.

Key Responsibilities

AI Model Development

- Design, develop, and optimize AI solutions, including LLMs, RAG architectures, and Graph-based RAG systems, tailored to specific business needs.
- Develop and fine-tune models for tasks such as Natural Language Processing (NLP), Computer Vision, and Reinforcement Learning (RL).

Prompt Engineering and AI Agents

- Work with prompt optimization to enhance LLM-based responses for specific use cases.
- Develop autonomous AI agents capable of completing multi-step tasks with minimal human intervention.

Data Processing and Management

- Collect, clean, preprocess, and organize datasets for effective AI and ML model training and evaluation.
- Leverage graph databases and vector stores for efficient data retrieval in AI-driven systems.

Algorithm Selection and Optimization

- Choose and implement appropriate algorithms, considering constraints such as scalability, interpretability, and real-time deployment requirements.
- Conduct hyperparameter tuning and optimization experiments to maximize model efficiency and accuracy.

Deployment and Integration

- Deploy AI/ML models in production-grade environments, ensuring scalability, reliability, and seamless integration with existing systems.
- Implement model monitoring pipelines to ensure performance consistency over time.

Research and Development

- Stay abreast of the latest trends and advancements in AI and ML technologies, such as transformer architectures, diffusion models, and multi-modal AI.
- Experiment with emerging tools like LangChain, Hugging Face, and OpenAI APIs to innovate solutions.

Collaboration and Knowledge Sharing

- Work closely with data scientists, software engineers, and product managers to define project requirements and deliver impactful AI solutions.
- Document workflows, processes, and findings to enable knowledge sharing and continuity across teams.

Required Qualifications

Education

- Bachelor's or Master's degree in Computer Science, AI, Data Science, Engineering, Mathematics, or a related field.

Experience

- Minimum 3+ years in AI/ML roles with a proven track record in building and deploying AI-driven solutions.

Technical Proficiency

- Proficiency in Python and AI/ML frameworks like TensorFlow, PyTorch, scikit-learn, or Keras.
- Experience working with LLMs, transformers, and generative AI tools.
- Familiarity with cloud platforms such as AWS, Google Cloud, or Azure, including AI-focused services like SageMaker and Vertex AI.
- Knowledge of vector databases (e.g., Pinecone, Milvus, Weaviate) and graph databases for RAG systems.

Analytical Expertise

- Strong understanding of advanced statistical methods, mathematical concepts, and probabilistic models.
- Ability to analyze and interpret data for actionable insights and model improvements.

Soft Skills

- Exceptional problem-solving and critical-thinking abilities.
- Strong communication skills to effectively collaborate with cross-functional teams.
- Adaptability to a fast-paced, innovation-driven environment.

Preferred Qualifications

- Hands-on experience with LangChain, Hugging Face Transformers, or OpenAI API integrations.
- Expertise in specialized AI domains like multi-modal learning, conversational AI, and prompt engineering.
- Contributions to open-source AI projects or publications in recognized AI/ML conferences or journals.
- Familiarity with deploying AI Agents in production systems.