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Machine Learning Hardware Engineer Job Opening In Bengaluru – Now Hiring Zobility


Job description

Job Description

We are seeking a Staff LLM–RAG Engineer (Contract) to lead the development and optimization of enterprise-grade retrieval-augmented generation systems.

You will architect scalable AI solutions, integrate large language models with advanced retrieval pipelines, and ensure production readiness.

This role combines deep technical expertise with the ability to guide teams and deliver results on aggressive timelines.


Most Important Skills/Responsibilities:

  • Lead RAG Architecture Design – Define and implement best practices for retrieval-augmented generation systems, ensuring reliability, scalability, and low-latency performance.

  • Full-Stack AI Development – Build and optimize multi-stage pipelines using LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex, or custom).

  • Programming & Integration – Develop services and APIs in Python and Golang to support AI workflows, document ingestion, and retrieval processes.

  • Search & Retrieval Optimization – Implement hybrid search, vector embeddings, and semantic ranking strategies to improve contextual accuracy.

  • Prompt Engineering – Design and iterate on few-shot, chain-of-thought, and tool-augmented prompts for domain-specific applications.

  • -Bachelors degree required.

  • Strong proficiency in Python and Golang or RUST, with experience building high-performance services and APIs.
  • -Need experience in developing end-to-end projects -> backend software(RAG/GenAI, text/image, model improvement, scoring) -> AWS/databricks(deployment) -> endpoint -> chatbot

Key Responsibilities

  • Lead RAG Architecture Design – Define and implement best practices for retrieval-augmented generation systems, ensuring reliability, scalability, and low-latency performance.

  • Full-Stack AI Development – Build and optimize multi-stage pipelines using LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex, or custom).

  • Programming & Integration – Develop services and APIs in Python and Golang to support AI workflows, document ingestion, and retrieval processes.

  • Search & Retrieval Optimization – Implement hybrid search, vector embeddings, and semantic ranking strategies to improve contextual accuracy.

  • Prompt Engineering – Design and iterate on few-shot, chain-of-thought, and tool-augmented prompts for domain-specific applications.

  • Mentorship & Collaboration – Partner with cross-functional teams and guide engineers on RAG and LLM best practices.

  • Performance Monitoring – Establish KPIs and evaluation metrics for RAG pipeline quality and model performance.

Qualifications

Must Have:

  • 8+ years in software engineering or applied AI/ML, with at least 2+ years focused on LLMs and retrieval systems.

  • Strong proficiency in Python and Golang or RUST, with experience building high-performance services and APIs.
  • Expertise in RAG frameworks (LangChain, LangGraph, LlamaIndex) and embedding models.

  • Hands-on experience with vector databases (Databricks Vector Store, Pinecone, Weaviate, Milvus, Chroma).

  • Strong understanding of hybrid search (semantic + keyword) and embedding optimization.

  • -Bachelors degree required

Preferred:

  • LLM fine-tuning experience (LoRA, PEFT).

  • Knowledge graph integration with LLMs.
  • Familiarity with cloud ML deployment (AWS (preferred), Databricks, Azure).

  • - Masters or PHD degree in CS

Soft Skills

  • Strong problem-solving and decision-making skills under tight timelines.

  • Excellent communication for cross-functional collaboration.

  • Ability to work independently while aligning with strategic goals.

Required Skill Profession

Computer Occupations


  • Job Details

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Unlock Your Machine Learning Potential: Insight & Career Growth Guide


Real-time Machine Learning Jobs Trends (Graphical Representation)

Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph here. Uncover the dynamic job market trends for Machine Learning in Bengaluru, India, highlighting market share and opportunities for professionals in Machine Learning roles.

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Are You Looking for Machine Learning Hardware Engineer Job?

Great news! is currently hiring and seeking a Machine Learning Hardware Engineer to join their team. Feel free to download the job details.

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The Work Culture

An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Zobility adheres to the cultural norms as outlined by Expertini.

The fundamental ethical values are:

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2. Loyalty

3. Impartiapty

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6. Respect for human rights

7. Obeying India laws and regulations

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The average salary range for a varies, but the pay scale is rated "Standard" in Bengaluru. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

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Interview Tips for Machine Learning Hardware Engineer Job Success

Zobility interview tips for Machine Learning Hardware Engineer

Here are some tips to help you prepare for and ace your Machine Learning Hardware Engineer job interview:

Before the Interview:

Research: Learn about the Zobility's mission, values, products, and the specific job requirements and get further information about

Other Openings

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Be Punctual: Arrive on time to demonstrate professionalism and respect.

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