Job
Description
We are looking for a highly skilled Generative AI Developer : Responsibilities We are looking for a highly skilled Generative AI Developer with expertise in Large Language Models (LLMs) to join our AI/ML innovation team. The ideal candidate will be responsible for building, fine-tuning, deploying, and optimizing generative AI models to solve complex real-world problems. You will collaborate with data scientists, machine learning engineers, product managers, and software developers to drive forward next-generation AI-powered Responsibilities : Design and develop AI-powered applications using large language models (LLMs) such as GPT, LLaMA, Mistral, Claude, or similar. Fine-tune pre-trained LLMs for specific tasks (e.g., text summarization, Q&A systems, chatbots, semantic search). Build and integrate LLM-based APIs into products and systems. Optimize inference performance, latency, and throughput of LLMs for deployment at scale. Conduct prompt engineering and design strategies for prompt optimization and output consistency. Develop evaluation frameworks to benchmark model quality, response accuracy, safety, and bias. Manage training data pipelines and ensure data privacy, compliance, and quality standards. Experiment with open-source LLM frameworks and contribute to internal libraries and tools. Collaborate with MLOps teams to automate deployment, CI/CD pipelines, and monitoring of LLM solutions. Stay up to date with state-of-the-art advancements in generative AI, NLP, and foundation Skills Required : LLMs & Transformers: Deep understanding of transformer-based architectures (e.g., GPT, BERT, T5, LLaMA, Falcon). Model Training/Fine-Tuning: Hands-on experience with training/fine-tuning large models using libraries such as Hugging Face Transformers, DeepSpeed, LoRA, PEFT. Prompt Engineering: Expertise in designing, testing, and refining prompts for specific tasks and outcomes. Python: Strong proficiency in Python with experience in ML and NLP libraries. Frameworks: Experience with PyTorch, TensorFlow, Hugging Face, LangChain, or similar frameworks. MLOps: Familiarity with tools like MLflow, Kubeflow, Airflow, or SageMaker for model lifecycle management. Data Handling: Experience with data pipelines, preprocessing, and working with structured and unstructured Desirable Skills : Deployment: Knowledge of deploying LLMs on cloud platforms like AWS, GCP, Azure, or edge devices. Vector Databases: Experience with FAISS, Pinecone, Weaviate, or ChromaDB for semantic search applications. LLM APIs: Experience integrating with APIs like OpenAI, Cohere, Anthropic, Mistral, etc. Containerization: Docker, Kubernetes, and cloud-native services for scalable model deployment. Security & Ethics: Understanding of LLM security, hallucination handling, and responsible AI : Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or related field. 2-4 years of experience in ML/NLP roles with at least 12 years specifically focused on generative AI and LLMs. Prior experience working in a research or product-driven AI team is a plus. Strong communication skills to explain technical concepts and findings Skills : Analytical thinker with a passion for solving complex problems. Team player who thrives in cross-functional settings. Self-driven, curious, and always eager to learn the latest advancements in AI. Ability to work independently and deliver high-quality solutions under tight deadlines. (ref:hirist.tech) Show more Show less
