About Prismforce Prismforce is a Vertical SaaS company revolutionizing the Talent Supply Chain for global Technology, R&D;/Engineering, and IT Services companies. Our AI-powered product suite enhances business performance by enabling operational flexibility, accelerating decision-making, and boosting profitability. Our mission is to become the leading industry cloud/SaaS platform for tech services and talent organizations worldwide. Data Scientist I / II | Prismforce | Bangalore (Hybrid) About Prismforce And The AI & ML Team Prismforce is a Sequoia-backed vertical SaaS company building the Talent Supply Chain platform for global technology, engineering and IT services firms, with clients across IT services, banking, healthcare and automotive. The AI & ML team builds the intelligence layer underneath every product.
That layer powers SkillPrism, SelectPrism and IntelliPrism, and our AI-readiness assessments for enterprise workforces. You will work on models that run in production for some of the largest employers in India and the US. What You’ll Do
• Fine-tune transformers and LLMs (LoRA/QLoRA) for entity extraction, classification and reranking.
• Extract entities from

job description
s and resumes, building prediction models, create knowledge graph and traversal models.
• Build retrieval, clustering and learning-to-rank pipelines over large taxonomies.
• Design evaluations, dig into errors, and ship models to production. Requirements
• Hands-on applied NLP or ML

experience:
1–3 years for Data Scientist I, 3–5 years for Data Scientist II.
• Strong Python, with PyTorch, Hugging Face Transformers, sentence-transformers, pandas and scikit-learn.
• Has fine-tuned transformer models on their own data, such as an encoder for NER or classification, or a decoder LLM with PEFT (LoRA/QLoRA).
• Solid grasp of embeddings, attention, contrastive training,



and retrieval with bi-encoders and cross-encoders.
• Working knowledge of classical ML: gradient boosting, logistic regression, clustering, and dimensionality reduction.
• Comfort with statistics and evaluation design: sampling, significance, calibration and metric choice.
• SQL, plus the ability to explore data at the scale of millions of records.
• Transparent written communication of experiments and results.
• Experience with learning-to-rank, knowledge graphs or large taxonomies in a real product.
• Experience with ML lifecycle tooling: experiment tracking, model versioning, Docker, and GPU training and serving on AWS. Nice to have
• Graph databases and graph ML: Neo4j and Cypher, pgvector, node embeddings, link prediction.
• Span-based or zero-shot NER (GLiNER, NuNER) and entity linking to a fixed ontology.
• Distilling LLM outputs into small models, and efficient serving with vLLM, quantisation or ONNX.
• Managed LLM platforms such as AWS Bedrock or SageMaker, and structured-output prompting at scale.
• Agent and workflow orchestration (LangGraph, n8n or similar) for multi-step curation pipelines.
• Ontology or taxonomy design, or prior work in HR tech, talent or skills data.
• Open-source contributions, Kaggle results or publications in NLP or IR. Why join
• Real scale: your models run on millions of enterprise data points.
• Breadth: you will touch extraction, graphs, ranking and LLMs, not one narrow slice.
• Ownership: a small, senior team where you ship and see the impact.
• Leadership from McKinsey, Deloitte, Amazon, Infosys, TCS and Uber, with an advisory board of former IT services CXOs. Perks And Benefits
• Competitive compensation
• Group medical cover for self, spouse, children and parents
• Hybrid work and flexible policies
• Retirement benefits
• A self-driven career progression framework Skills LORAQLORAllmllm trainingFine tuning

📌 Data Scientist-I/II (Bengaluru)
🏢 Prismforce
📍 Bengaluru