About the Role :

We are looking for a passionate and skilled AI / ML Engineer to join our innovative team. In this role, you will design, build, and optimize cutting-edge AI-powered features and solutions that drive the next generation of our products. You will work closely with data scientists, software engineers, and product teams to develop scalable machine learning models and pipelines, deploy large language models (LLMs), and ensure efficient, reliable operations in production environments.

If you have a deep understanding of modern LLM architectures, expertise in MLOps, and experience with cloud infrastructure and DevOps best practices, you will thrive in this role and make a significant impact.

Key Responsibilities :

- Design and implement AI-driven features that enhance user experience, automate workflows, and deliver actionable insights.

- Train, fine-tune, evaluate, and deploy machine learning models, including LLMs such as GPT, Llama, Gemini, and Claude, ensuring high accuracy and efficiency.

- Build robust ML pipelines for experiment tracking, model versioning, feature management, and deployment using tools like MLFlow, Langchain, and Langgraph.

- Implement A/B testing frameworks to evaluate model performance in production and develop scalable APIs for real-time model inference.

- Optimize GPU utilization, parallelize training workflows, and fine-tune models to maximize speed and minimize resource consumption.

- Deploy and customize large language model solutions tailored to specific business use cases, leveraging platforms like AWS Bedrock and Azure AI.

- Apply best practices in DevOps and LLMOps, including containerization with Docker, orchestration with Kubernetes, and continuous integration/continuous deployment (CI/CD) of ML workloads.

- Work closely with cross-functional teams including data engineers, product managers, and software developers to ensure smooth integration of AI solutions. Maintain thorough documentation of models, pipelines, and infrastructure.

Required Qualifications :

- Strong experience with Large Language Models (LLMs) and related open-source frameworks : Hugging Face OSS, GPT, Gemini, Claude, Mixtral, Llama.

- Hands-on expertise in LLMOps tools and frameworks including MLFlow, Langchain, Langgraph, LangFlow, Langfuse, LlamaIndex, and cloud services like AWS SageMaker, AWS Bedrock, Azure AI.

- Solid experience with databases such as MongoDB, PostgreSQL, and vector databases like Pinecone and ChromDB.

- Proficiency in cloud platforms : AWS and Azure.

- Strong knowledge of DevOps tools and practices, including containerization (Docker) and orchestration (Kubernetes).

- Programming skills in Python, SQL, and JavaScript.

- Familiarity with scalable API development, real-time data processing, and deployment automation.

- Strong analytical and problem-solving skills, with a focus on performance, scalability, and reliability.

- Excellent collaboration and communication skills to work effectively across teams.