Data Scientist

Weekday (YC W21); Bengaluru; On-site; INR 1,000,000 - 1,800,000; Full time

Job summary

Weekday in Bengaluru is seeking a talented Data Scientist I/II to develop and deploy production-grade ML/NLP/LLM solutions. You will work on entity extraction, classification, semantic retrieval, and knowledge graphs across large enterprise datasets.

The role emphasizes hands-on Python, transformer models, and model evaluation, with production deployment and scalable AI challenges in a fast-growing environment.

Qualifications

• 1+ years of applied ML/NLP experience.
• Proficiency in Python, PyTorch, Transformers, Pandas, and Scikit-learn.
• Experience fine-tuning models on custom datasets (NER/classification).
• Familiarity with PEFT techniques like LoRA/QLoRA.
• Understanding embeddings, semantic search, and information retrieval.
• Knowledge of ML deployment, experiment tracking, and Docker.

Responsibilities

• Fine-tune transformer models using LoRA/QLoRA for extraction and ranking.
• Develop NLP models to extract and link entities from resumes and job descriptions.
• Build knowledge graphs and graph traversal for skills and roles.
• Design semantic retrieval and learning-to-rank pipelines across large datasets.
• Develop embedding-based search with bi-encoders and cross-encoders.
• Deploy, monitor, and improve models in production environments.

Skills

Python

PyTorch

HuggingFace

Transformers

Sentence Transformers

Pandas

Scikit-learn

LoRA

QLoRA

NLP

Embeddings

Graph knowledge

Docker

SQL

AWS

Tools

Neo4j

Cypher

Docker

Git

SQL

AWS

Job description

This role is for one of our clients

• Industry: Software Development
• Seniority level: Associate level
• Experience: 1+ yrs
• Location: Bangalore
• Job Type: Full-time

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

We are looking for a talented and technically strong Data Scientist I / II to develop and deploy production-grade machine learning, Natural Language Processing (NLP), and Large Language Model (LLM) solutions. The role focuses on building intelligent systems for entity extraction, classification, semantic retrieval, ranking, and knowledge graph applications using large-scale enterprise datasets.

The ideal candidate will have hands‑on experience with Python, transformer models, applied NLP, and machine learning, along with a strong understanding of model evaluation and production deployment. This is an opportunity to work on complex AI challenges involving millions of records while building scalable solutions that deliver measurable business value.

Requirements

• Fine‑tune transformer models and LLMs using techniques such as LoRA and QLoRA for entity extraction, classification, and reranking
• Develop NLP models to extract, classify, and link entities from resumes, job descriptions, and other unstructured enterprise data
• Build prediction models, knowledge graphs, and graph traversal solutions to represent relationships between skills, roles, and competencies
• Design and implement semantic retrieval, clustering, and learning‑to‑rank pipelines across large taxonomies and datasets
• Develop embedding‑based search solutions using bi‑encoders, cross‑encoders, and related retrieval techniques
• Apply classical machine learning methods, including gradient boosting, logistic regression, clustering, and dimensionality reduction
• Design evaluation frameworks, select appropriate metrics, analyse model errors, and validate performance through systematic experiments
• Explore datasets containing millions of records using Python, SQL, and data‑processing tools
• Deploy, monitor, and improve machine learning models in production environments
• Use experiment tracking, model versioning, Docker, and cloud infrastructure to support reproducible ML workflows
• Collaborate with product, data, and engineering teams to translate business problems into effective AI solutions
• Document experiments, communicate findings, and continuously improve model accuracy, efficiency, and reliability

What Makes You a Great Fit

• 1+ years of relevant experience in applied machine learning, NLP, or data science; experience expectations may vary between Data Scientist I and II
• Strong proficiency in Python, with hands‑on experience using PyTorch, Hugging Face Transformers, sentence-transformers, pandas, and scikit-learn
• Practical experience fine‑tuning transformer models on custom datasets for named entity recognition, classification, or related NLP tasks
• Experience with LLM fine‑tuning and parameter‑efficient techniques such as PEFT, LoRA, or QLoRA
• Strong understanding of embeddings, attention mechanisms, contrastive learning, semantic search, and information retrieval
• Working knowledge of classical machine learning algorithms and statistical evaluation methods
• Experience with SQL and the ability to analyse large-scale datasets
• Understanding of model evaluation, sampling, statistical significance, calibration, and metric selection
• Familiarity with ML deployment practices, experiment tracking, model versioning, Docker, and GPU‑based training or serving on AWS
• Experience with learning‑to‑rank, knowledge graphs, entity linking, or large‑scale taxonomies is an advantage
• Familiarity with Neo4j, Cypher, pgvector, graph ML, GLiNER, NuNER, vLLM, ONNX, AWS Bedrock, or SageMaker is a plus
• Strong analytical thinking, problem‑solving, and written communication skills
• Ability to work collaboratively, take ownership of experiments, and translate research into production‑ready solutions
• A strong interest in applied AI, modern NLP, LLM systems, and continuous experimentation