Gigaforce - NLP/Generative AI Engineer - Python/LLM

Description :Please read :1. This is a WFO opportunity for our Noida based office. Do NOT apply if you are looking for a hybrid or WFH/remote opportunity.2. Preference will be given to candidates currently residing in NCR or have reason to relocate to NCR.3. We need a minimum of 4 years of current and relevant NLP & Generative AI experience. Freshers or junior employees do NOT apply.4. If you have applied in the last 6 months, do NOT apply again. About Gigaforce :Gigaforce is a California-based InsurTech company delivering a next-generation, SaaS-based claims platform purpose-built for the Property and Casualty industry. Our blockchain-optimized solution integrates artificial intelligence (AI)-powered predictive models with deep domain expertise to streamline and accelerate subrogation and claims processing. Whether for insurers, recovery vendors, or other ecosystem participants, Gigaforce transforms the traditionally fragmented claims lifecycle into an intelligent, end-to-end digital experience.Recognized as one of the most promising emerging players in the insurance technology space, Gigaforce has already achieved significant milestones. We were a finalist for InsurtechNY, a leading platform accelerating innovation in the insurance industry, and twice named a Top 50 company by the TiE Silicon Valley community. Additionally, Plug and Play Tech Center, the world's largest early-stage investor and innovation accelerator, selected Gigaforce to join its prestigious global accelerator headquartered in Sunnyvale, California.We're seeking an NLP & Generative AI Engineers with 2-8 years of hands-on experience in traditional machine learning, natural language processing, and modern generative AI techniques. If you have experience deploying GenAI solutions to production, working with open-source technologies, and handling document-centric pipelines, this is the role for you. You'll work in a high-impact role, leading the design, development, and deployment of innovative AI/ML solutions for insurance claims processing and beyond.In this agile environment, you'll work within structured sprints and leverage data-driven insights and user feedback to guide decision-making. You'll balance strategic vision with tactical execution to ensure we continue to lead the industry 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 focused on document understanding, summarization, classification, and retrieval.- Design and implement models leveraging LLMs (e.g., GPT, T5, BERT) with capabilities like fine-tuning, instruction tuning, and prompt engineering.- Work on scalable, cloud-based pipelines for training, serving, and monitoring models.- Handle unstructured data from insurance-related documents such as claims, legal texts, and contracts.- Collaborate cross-functionally with 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 using MLOps practices : Docker, Kubernetes, Airflow, MLflow, etc.- Work on distributed/cloud systems (AWS, GCP, or Azure) with GPU-accelerated workflows.- Evaluate and experiment with open-source LLMs and embeddings models (e.g., LangChain, Haystack, LlamaIndex, HuggingFace).- Champion best practices in model validation, reproducibility, and responsible AI.Required Skills & Qualifications :- 2 to 8 years of experience as a Data Scientist, NLP Engineer, or ML Engineer.- Strong grasp of traditional ML algorithms (SVMs, gradient boosting, etc.) and NLP fundamentals (word embeddings, topic modeling, text classification).- Proven expertise in modern NLP & GenAI models, including :o Transformer architectures (e.g., BERT, GPT, T5)o Generative tasks : summarization, QA, chatbots, etc.o Fine-tuning & prompt engineering for LLMs- Experience with cloud platforms (especially AWS SageMaker, GCP, or Azure ML).- Strong coding skills in Python, with libraries like Hugging Face, PyTorch, TensorFlow, Scikit-learn.- Experience with open-source frameworks (LangChain, LlamaIndex, Haystack) preferred.- Experience in document processing pipelines and understanding structured/unstructured insurance documents is a big plus.- Familiar with MLOps tools such as MLflow, DVC, FastAPI, Docker, KubeFlow, Airflow.- Familiarity with distributed computing and large-scale data processing (Spark, Hadoop, Databricks).Preferred Qualifications :- Experience deploying GenAI models in production environments.- Contributions to open-source projects in ML/NLP/LLM space.- Background in insurance, legal, or financial domain involving text-heavy workflows.- Strong understanding of data privacy, ethical AI, and responsible model usage. (ref:hirist.tech)