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Weekday AI

Proactive software engineer recruitment via referrals

Data Scientist

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, Indiaโ‚น2M - โ‚น7MIn-person

About the Job

Requirements

  • Data Scientist I candidates need 1โ€“3 years of experience in applied natural language processing, machine learning, or a related field; Data Scientist II candidates need 3โ€“5 years.
  • Strong proficiency in Python and practical experience with PyTorch, Hugging Face Transformers, sentence-transformers, pandas, and scikit-learn.
  • Hands-on experience fine-tuning transformer models on custom datasets for named entity recognition, classification, or large language model tasks using parameter-efficient fine-tuning techniques such as LoRA or QLoRA.
  • Strong understanding of embeddings, attention mechanisms, contrastive learning, semantic retrieval, bi-encoders, and cross-encoders.
  • Working knowledge of classical machine-learning algorithms and statistical evaluation methods.
  • Experience with SQL and analyzing large-scale datasets.
  • Understanding of learning-to-rank systems, knowledge graphs, entity linking, or large taxonomies.
  • Familiarity with machine-learning lifecycle practices, including experiment tracking, model versioning, Docker, and cloud-based model deployment.

Responsibilities

  • Fine-tune transformer models and large language models using techniques such as LoRA and QLoRA for entity extraction, classification, and reranking.
  • Develop natural language processing pipelines to extract structured entities, skills, and relevant information from resumes, job descriptions, and other unstructured datasets.
  • Build predictive models for entity classification, entity linking, and skills intelligence.
  • Design and implement knowledge graphs, graph traversal methods, and relationships across large skills taxonomies.
  • Develop retrieval, clustering, semantic search, and learning-to-rank pipelines using embeddings, bi-encoders, and cross-encoders.
  • Apply classical machine-learning techniques, including gradient boosting, logistic regression, clustering, and dimensionality reduction.
  • Design robust evaluation frameworks, analyze model errors, select appropriate metrics, and validate improvements through statistical analysis.
  • Process and analyze large datasets containing millions of records using Python, SQL, and relevant data-processing tools.
  • Deploy and optimize machine-learning models for production environments, ensuring scalability, reliability, and performance.
  • Use experiment tracking, model versioning, Docker, and AWS-based GPU training and serving workflows.
  • Collaborate with engineering and product teams to integrate artificial intelligence capabilities into enterprise applications.
  • Document experiments, communicate findings, and continuously improve model quality, efficiency, and business impact.

About the Company

Weekday AI

Proactive software engineer recruitment via referrals

Weekday.works helps companies hire software engineers through proactive outreach and peer-recommended candidates. Its platform automates tracking, pipeline management, and provides weekly updates, while it actively identifies engineers via peer networks, reaches out, shortlists, checks references, and schedules interviews. Differentiators include peer-backed vetting instead of traditional job boards, proactive outreach, and a passive-income reference feature that monetizes referrals. The goal is to reduce the time and effort of hiring by connecting companies with pre-vetted engineers who are open to new opportunities through a network-driven approach.

Company size
201-500
Company stage
Seed
Total funding
$2.3M
Headquarters
Bengaluru, India
Founded
2021

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