<p><p><b>Position : </b> AI Engineer (Python + Generative AI)<br/><br/><b>Experience : </b> 7 - 11 years<br/><br/><b>Location : </b> Work From Home</p><p><b><br/></b></p><p><p><b>Job Summary :</b></p><br/></p><p>We are seeking a highly skilled and experienced AI Engineer with a strong background in Python and Generative AI.
The ideal candidate will be an expert in the end-to-end development of AI systems, from prototyping and model training to deployment and optimization.
This role requires a hands-on engineer who can design and build robust, scalable applications using Large Language Models (LLMs) and other generative technologies to drive business Responsibilities AI Model Development & Engineering : </b></p><p><br/></p>- Design, build, and train Generative AI models, focusing on architectures like Transformers, GANs, and VAEs.<br/><br/></p><p>- Implement and fine-tune Large Language Models (LLMs) using techniques such as Retrieval-Augmented Generation (RAG) and prompt engineering.<br/><br/></p><p>- Develop and optimize data pipelines for ingesting, cleaning, and transforming large datasets to be used in model Design & Architecture : </b></p><p><br/></p>- Architect and implement production-grade, scalable AI applications using Python and modern frameworks.<br/><br/></p><p>- Integrate Generative AI models into enterprise systems using RESTful APIs, microservices, and event-driven architectures.<br/><br/></p><p>- Design and build robust data retrieval systems, including leveraging vector databases for semantic & Deployment : </b></p><p><br/></p>- Implement MLOps principles to automate the entire machine learning lifecycle, from development to deployment.<br/><br/></p><p>- Build and manage CI/CD pipelines for continuous integration and deployment of AI models and applications.<br/><br/></p><p>- Monitor model performance, latency, and resource utilization in production & Innovation : </b></p><p><br/></p>- Stay current with the latest advancements in Generative AI, machine learning, and natural language processing (NLP).<br/><br/></p><p>- Conduct research and experimentation to evaluate new models, frameworks, and techniques for potential business & Leadership : </b></p><p><br/></p>- Collaborate with cross-functional teams, including product managers, data scientists, and DevOps engineers, to deliver end-to-end solutions.<br/><br/></p><p>- Provide technical leadership and mentorship to junior team Skills & Core Engineering : </b></p><p><br/></p>- Expert-level proficiency in Python.<br/><br/></p><p>- Strong background in software engineering, including object-oriented programming, data structures, and AI & LLMs : </b></p><p><br/></p>- 7-11 years of experience in AI/ML engineering, with a strong focus on Generative AI.<br/><br/></p><p>- Proven hands-on experience with LLMs, including fine-tuning and RAG.<br/><br/></p><p>- Deep understanding of deep learning frameworks such as PyTorch or & Cloud Platforms : </b></p><p><br/></p>- Experience with cloud platforms for AI/ML (AWS, Azure, or GCP).<br/><br/></p><p>- Hands-on experience with MLOps tools (e.g., MLflow, Kubeflow) and containerization technologies & APIs : </b></p><p><br/></p>- Experience with vector databases (e.g., Pinecone, ChromaDB).<br/><br/></p><p>- Proficiency in SQL and experience with building and consuming RESTful & Frameworks : </b></p><p><br/></p>- Expertise with key libraries like Hugging Face Transformers, LangChain, or Skills :</b></p><p><br/></p>- Experience with Kubernetes for orchestrating containerized applications.<br/><br/></p><p>- Knowledge of specific cloud AI services (AWS Bedrock, Azure OpenAI Service, GCP Vertex AI).<br/><br/></p><p>- Experience with real-time data streaming technologies such as Kafka.<br/><br/></p><p>- Relevant professional certifications in AI/ML or cloud computing.<br/><br/></p><p>- Contributions to open-source AI projects.</p><br/></p> (ref:hirist.tech)