Al/ML Engineer

We are seeking a hands-on **AI/ML Engineer** to build and deploy intelligent AI solutions across a communication platform. The role involves developing **LLM-powered applications**, **voice AI** capabilities, **NLP pipelines**, and **production-grade ML systems** enabling automation and real-time decision-making.

Responsibilities

• Build and deploy AI/ML solutions using **Large Language Models (LLMs)**, **NLP**, **speech AI**, and **generative AI** technologies.
• Develop LLM-powered features including summarization, sentiment analysis, intent detection, auto-disposition, escalation tagging, and agent assistance.
• Build and implement **Agentic AI** workflows, prompt pipelines, and retrieval-based systems using frameworks like **LangChain**.
• Work with speech technologies including **STT**, **TTS**, **Whisper**, and voice intelligence solutions.
• Fine-tune, evaluate, and optimize AI models for accuracy, latency, and scalability.
• Build AI inference services and APIs using **Python**, **FastAPI**, **Docker**, and cloud-native technologies.
• Develop and maintain ML pipelines for data processing, model training, evaluation, and continuous improvement.
• Integrate AI models into product workflows such as communication platforms, CRM systems, dialers, and automation solutions.
• Optimize AI systems for high-volume production environments with focus on performance and reliability.
• Work with data technologies such as **PostgreSQL**, **Redis**, **Kafka**, and build scalable data workflows.
• Implement secure and compliant AI data handling, retrieval, and access control mechanisms.
• Collaborate with product, engineering, and business teams to deliver impactful AI-driven features as a hands-on builder.

Requirements

• **4–7 years** of experience in AI/ML engineering with production-grade AI applications.
• Strong hands-on experience with **LLMs**, **Generative AI**, **NLP**, and **conversational AI** systems.
• Experience building **Agentic AI** applications and voice bot solutions is highly preferred.
• Proficiency in **Python** and experience developing AI services using **FastAPI** or similar frameworks.
• Hands-on experience with frameworks/models such as **LangChain**, **HuggingFace**, **Whisper**, **GPT**, or equivalent.
• Strong understanding of NLP concepts including text classification, summarization, sentiment analysis, speech processing, and emotion detection.
• Experience deploying ML solutions using **Docker**, **Kubernetes**, **CI/CD** pipelines, and cloud platforms.
• Familiarity with databases and messaging systems such as **PostgreSQL**, **Redis**, **Kafka**, or **RabbitMQ**.
• Experience with multilingual AI models, especially Indian languages, is a plus.
• Exposure to **Rasa**, **Coqui TTS**, speech emotion recognition, or conversational intelligence platforms is an advantage.
• Prior experience in SaaS, contact center, CRM, dialer, or customer communication platforms is preferred.
• Strong individual ownership mindset with ability to work independently as a hands-on contributor in a fast-paced startup environment.

Who Should Apply: The ideal candidate is an experienced **AI/ML Engineer** with 4-7 years building production-grade AI applications. They possess strong expertise in **LLMs**, **Generative AI**, **NLP**, and **conversational AI**, along with hands-on experience using **LangChain**, **HuggingFace**, **Whisper**, and deploying with **Docker**, **Kubernetes**, and **CI/CD**. A self-starter with an individual ownership mindset, they thrive in a fast-paced startup environment and have prior experience in SaaS, contact center, or communication platforms.

Application Tip: Tailor your resume to emphasize hands-on projects where you built and deployed **LLM-powered features** (e.g., summarization, sentiment analysis, intent detection) using **LangChain** and **FastAPI** in production. Highlight any experience with **voice AI**, **Agentic AI workflows**, and multilingual models, especially Indian languages, to stand out.