Weekday AI

Member of Technical Staff - ML

Weekday AI Bengaluru, Karnataka, India Today
engineering

This role is for one of the Weekday's clients

Salary range: Rs 2500000 - Rs 4000000 (ie INR 25-40 LPA)

Min Experience: 2 years

Location: Bengaluru

JobType: full-time

We are looking for a driven Member of Technical Staff – Machine Learning with 2–3 years of hands-on experience in Python development, API engineering, and working with Large Language Models (LLMs). This role focuses on building and scaling ML-powered features, integrating AI capabilities into production systems, and contributing to the development of AI-first products.

Requirements

Key Responsibilities

  • Design, build, and maintain Python-based machine learning pipelines and services.
  • Develop, implement, and maintain RESTful APIs and integrations with internal and external systems.
  • Integrate and operationalize LLM models (e.g., OpenAI, Anthropic, Gemini) within production applications.
  • Create and optimize prompts, prompt templates, and prompt chains for various LLM-driven use cases.
  • Collaborate closely with product and engineering teams to translate business requirements into ML solutions.
  • Monitor model performance and optimize inference, latency, and reliability.
  • Follow best practices for code quality, testing, scalability, and maintainability.
  • Contribute to system design and architecture discussions for AI-driven platforms and products.

Required Skills & Experience

  • Strong proficiency in Python, with experience using FastAPI or Flask.
  • Solid experience in API development and integration, including REST standards, authentication, versioning, and documentation.
  • Hands-on experience with LLM integration, embeddings, and vector-based retrieval workflows.
  • Good understanding of prompt engineering, including system prompts, RAG workflows, and evaluation techniques.
  • Experience handling JSON schemas, logging, asynchronous programming, and error handling.
  • Foundational knowledge of machine learning concepts such as preprocessing, evaluation, and deployment.
  • Exposure to cloud platforms (AWS, GCP, or Azure) is an advantage.

Nice-to-Have

  • Experience with vector databases such as Pinecone, Weaviate, or FAISS.
  • Familiarity with frameworks like LangChain, LlamaIndex, or similar tools.
  • Understanding of CI/CD pipelines and modern DevOps practices.
  • Exposure to monitoring, observability, and model performance tracking tools.
  • Basic knowledge of Docker and containerized deployments.

Qualifications

  • Bachelor’s degree in Computer Science, Engineering, or a related field.
  • 2–3 years of professional experience in software or machine learning engineering roles, preferably in a product-based environment.

Skills

Python, LLMs, REST APIs, FastAPI, Flask, Machine Learning, Prompt Engineering

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