Junior NLP & Generative AI Engineer

As an NLP & Generative AI Engineer at Gigaforce, you will play a crucial role in designing, developing, and deploying innovative AI/ML solutions for insurance claims processing and beyond. With 2-8 years of hands-on experience in traditional machine learning, natural language processing, and modern generative AI techniques, you will have the opportunity to lead the way in subrogation automation and claims optimization for the property and casualty insurance market. **Key Responsibilities:** - Build and deploy end-to-end NLP and GenAI-driven products focusing on document understanding, summarization, classification, and retrieval. - Design and implement models using LLMs (e.g., GPT, T5, BERT) with features like fine-tuning, instruction tuning, and prompt engineering. - Develop scalable, cloud-based pipelines for training, serving, and monitoring models. - Process unstructured data from insurance-related documents such as claims, legal texts, and contracts. - Collaborate with cross-functional teams including data scientists, ML engineers, product managers, and developers. - Utilize and contribute to open-source tools and frameworks in the ML ecosystem. - Deploy production-ready solutions following MLOps practices like Docker, Kubernetes, Airflow, MLflow, etc. - Utilize distributed/cloud systems (AWS, GCP, or Azure) with GPU-accelerated workflows. - Evaluate and experiment with open-source LLMs and embeddings models like LangChain, Haystack, LlamaIndex, and HuggingFace. - Promote best practices in model validation, reproducibility, and responsible AI. **Required Skills & Qualifications:** - 1-2 years of experience as a Data Scientist, NLP Engineer, or ML Engineer. - Strong understanding of traditional ML algorithms (SVMs, gradient boosting, etc.) and NLP fundamentals (word embeddings, topic modeling, text classification). - Expertise in modern NLP & GenAI models, including Transformer architectures (e.g., BERT, GPT, T5), generative tasks like summarization, QA, chatbots, fine-tuning & prompt engineering for LLMs, and experience with cloud platforms such as AWS SageMaker, GCP, or Azure ML. - Proficient coding skills in Python with libraries like Hugging Face, PyTorch, TensorFlow, Scikit-learn. - Experience with open-source frameworks like LangChain, LlamaIndex, Haystack is preferred. - Knowledge in document processing pipelines and understanding structured/unstructured insurance documents is advantageous. - Familiarity with MLOps tools such as MLflow, DVC, FastAPI, Docker, KubeFlow, Airflow. - Understanding of distributed computing and large-scale data processing using Spark, Hadoop, Databricks. **Preferred Qualifications:** - Experience in deploying GenAI models in production environments. - Contributions to open-source projects in the ML/NLP/LLM space. - Background in insurance, legal, or financial domain involving text-heavy workflows. - Strong comprehension of data privacy, ethical AI, and responsible model usage. Gigaforce is a California-based InsurTech company dedicated to revolutionizing the claims processing industry through cutting-edge technology and a commitment to innovation. Join us in our mission to transform the insurance landscape and make a difference in the Property and Casualty sector. As an NLP & Generative AI Engineer at Gigaforce, you will play a crucial role in designing, developing, and deploying innovative AI/ML solutions for insurance claims processing and beyond. With 2-8 years of hands-on experience in traditional machine learning, natural language processing, and modern generative AI techniques, you will have the opportunity to lead the way in subrogation automation and claims optimization for the property and casualty insurance market. **Key Responsibilities:** - Build and deploy end-to-end NLP and GenAI-driven products focusing on document understanding, summarization, classification, and retrieval. - Design and implement models using LLMs (e.g., GPT, T5, BERT) with features like fine-tuning, instruction tuning, and prompt engineering. - Develop scalable, cloud-based pipelines for training, serving, and monitoring models. - Process unstructured data from insurance-related documents such as claims, legal texts, and contracts. - Collaborate with cross-functional teams including data scientists, ML engineers, product managers, and developers. - Utilize and contribute to open-source tools and frameworks in the ML ecosystem. - Deploy production-ready solutions following MLOps practices like Docker, Kubernetes, Airflow, MLflow, etc. - Utilize distributed/cloud systems (AWS, GCP, or Azure) with GPU-accelerated workflows. - Evaluate and experiment with open-source LLMs and embeddings models like LangChain, Haystack, LlamaIndex, and HuggingFace. - Promote best practices in model validation, reproducibility, and responsible AI. **Required Skills & Qualifications:** - 1-2 years of experience as a Data Scientist, NLP Engineer, or ML Engineer. - Strong understanding of traditional ML al