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Weekday helps companies hire engineers who are vouched by other software engineers, enabling passive income for engineers. They offer services like drafting outreach messages, shortlisting candidates, and conducting reference checks. Backed by Y Combin...

Construction & Engineering
11-50
Founded 2020

Description

  • Design, develop, and deploy applications powered by large language models for generation, summarization, classification, semantic search, and conversational AI.
  • Fine-tune, prompt-engineer, and optimize LLMs to improve accuracy, latency, and cost efficiency.
  • Build and maintain end-to-end machine learning pipelines from data preprocessing through training, evaluation, and deployment.
  • Integrate LLM-based solutions into production systems using APIs and microservices.
  • Implement retrieval-augmented generation systems using vector databases and embeddings.
  • Collaborate with stakeholders to translate business problems into AI-driven solutions.
  • Monitor model performance in production and drive continuous improvement.
  • Stay current with advancements in LLMs, generative AI, and NLP research and apply best practices.
  • Ensure responsible AI practices, including bias mitigation, explainability, and data privacy compliance.

Requirements

  • 3–8 years of experience in AI/ML engineering with hands-on NLP and LLM experience.
  • Strong programming skills in Python.
  • Experience with PyTorch, TensorFlow, or JAX.
  • Practical experience with GPT-style or open-source LLMs, including fine-tuning and prompt engineering.
  • Familiarity with Hugging Face Transformers, LangChain, or similar libraries.
  • Experience with vector databases such as FAISS, Pinecone, or Weaviate and embedding techniques.
  • Solid understanding of machine learning fundamentals, deep learning architectures, and NLP concepts.
  • Experience with AWS, GCP, or Azure and deploying scalable ML systems.
  • Knowledge of REST APIs, microservices architecture, and containerization tools such as Docker and Kubernetes.
  • Preferred: Experience with retrieval-augmented generation and knowledge-grounded AI systems.
  • Preferred: Exposure to reinforcement learning from human feedback or model alignment techniques.
  • Preferred: Familiarity with MLOps tools and practices such as CI/CD for ML, monitoring, and versioning.
  • Preferred: Contributions to open-source AI/ML projects or research publications in NLP/AI.

Benefits

  • Salary range of Rs 20,00,000 to Rs 1,00,00,000 per year.
  • Full-time position.
  • Location: India.

Interested in this position?

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