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Machine Learning Engineer - LLM & GenAI

Jobgether • India
Remote
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AI Summary

Design and develop production-grade LLM applications for conversational AI experiences. Build and optimize retrieval-augmented generation pipelines connecting structured and unstructured data sources. Implement frameworks like LangChain and LlamaIndex to improve AI performance and reliability.

Key Highlights
Production-grade LLM application development
Retrieval-augmented generation (RAG) pipeline optimization
Integration with existing product interfaces and backend services
Key Responsibilities
Design, develop, and maintain LLM-powered backend services using Python and FastAPI
Build and optimize retrieval-augmented generation (RAG) pipelines connecting structured and unstructured data sources
Implement frameworks such as LangChain, LlamaIndex, Haystack, or similar technologies to manage context retrieval, query routing, summarization, and response generation
Develop prompt engineering strategies, structured output generation workflows, and intent classification pipelines
Integrate conversational AI capabilities with existing product interfaces and backend services
Design, test, and validate AI solutions across diverse analytics use cases
Evaluate and improve retrieval accuracy, response quality, latency, and hallucination rates
Implement caching strategies, schema-based memory solutions, and automated evaluation pipelines
Maintain technical documentation covering system architecture, APIs, prompt strategies, deployment processes, and model lifecycle improvements
Technical Skills Required
Python FastAPI LLM application frameworks (LangChain, LlamaIndex, Haystack)
Benefits & Perks
Fully remote work opportunity
Opportunity to build cutting-edge AI and Generative AI solutions
Exposure to innovative applications in automotive technology and intelligent data analytics
Nice to Have
Experience with OpenAI, Anthropic, Ollama or other large language model platforms
Embedding optimization, hallucination reduction techniques, AI orchestration frameworks, or multi-agent systems
Knowledge of EV analytics, fleet management, IoT data, or automotive technology

Job Description


This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Machine Learning Engineer - LLM & GenAI based in India.

Join an innovative engineering team building advanced AI solutions that transform how businesses interact with complex operational data. In this role, you will design and develop production-grade Large Language Model (LLM) applications that enable users to access insights through natural language conversations. You will work on cutting-edge Generative AI technologies, retrieval-augmented generation systems, and intelligent data workflows that create real-world impact. This global opportunity offers the chance to shape AI-powered products from architecture to deployment while collaborating with multidisciplinary teams. If you are passionate about machine learning, conversational AI, and building scalable intelligent systems, this role provides an exciting opportunity to contribute to the future of AI-driven analytics.

Accountabilities

  • Design, develop, and maintain LLM-powered backend services using Python and FastAPI to support conversational AI experiences.
  • Build and optimize retrieval-augmented generation (RAG) pipelines that connect structured and unstructured data sources with intelligent language models.
  • Implement frameworks such as LangChain, LlamaIndex, Haystack, or similar technologies to manage context retrieval, query routing, summarization, and response generation.
  • Develop prompt engineering strategies, structured output generation workflows, and intent classification pipelines to improve AI performance and reliability.
  • Integrate conversational AI capabilities with existing product interfaces and backend services while ensuring secure and efficient data flows.
  • Design, test, and validate AI solutions across diverse analytics use cases, including data summaries, diagnostics, predictive insights, and performance analysis.
  • Evaluate and improve retrieval accuracy, response quality, latency, and hallucination rates through continuous testing and optimization.
  • Implement caching strategies, schema-based memory solutions, and automated evaluation pipelines to enhance system efficiency.
  • Maintain technical documentation covering system architecture, APIs, prompt strategies, deployment processes, and model lifecycle improvements.

Requirements

  • 4-6 years of hands-on experience in Machine Learning, with proven experience building production-grade LLM or Generative AI applications.
  • Strong proficiency in Python and experience developing backend services using FastAPI.
  • Practical experience with LLM application frameworks such as LangChain, LlamaIndex, Haystack, or similar technologies.
  • Experience designing retrieval pipelines and working with structured and unstructured data sources.
  • Knowledge of SQL databases and data platforms such as PostgreSQL, CrateDB, or similar technologies.
  • Understanding of vector databases including FAISS, Chroma, Pinecone, or comparable solutions.
  • Ability to design effective prompting strategies, improve retrieval workflows, and optimize AI-generated responses.
  • Experience evaluating AI systems through benchmarking, quality measurement, and performance optimization.
  • Familiarity with OpenAI, Anthropic, Ollama, or other large language model platforms is preferred.
  • Experience with embedding optimization, hallucination reduction techniques, AI orchestration frameworks, or multi-agent systems is a plus.
  • Knowledge of EV analytics, fleet management, IoT data, or automotive technology is considered an advantage.
  • Strong problem-solving skills, ownership mindset, and ability to work effectively in a remote global environment.

Benefits

  • Fully remote work opportunity with flexibility across locations.
  • Opportunity to build cutting-edge AI and Generative AI solutions with real-world business impact.
  • Direct influence on product architecture, technical decisions, and engineering practices.
  • Work on challenging projects combining artificial intelligence, IoT, automation, and modern web technologies.
  • Exposure to innovative applications in automotive technology and intelligent data analytics.
  • Opportunity to collaborate with global teams and contribute to the growth of an emerging technology ecosystem.
  • Continuous learning opportunities in rapidly evolving AI and machine learning fields.

How Jobgether Works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any 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.


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