Job Description
Experience Level
- 3–5 Years
Location
- Bengaluru, India
About the Role
We are seeking a Driven and Experienced Machine Learning Engineer to join our team and advance the capabilities of Large Language Models (LLMs) and intelligent agents. This hands-on role requires a strong background in:
- LLM tooling and evaluation
- Data engineering
- Building reusable, scalable, and open solutions
Responsibilities
- Design, build, and iterate on LLM-powered agents and tools, from prototypes to production.
- Develop evaluation frameworks, benchmark suites, and systematic testing tools for LLM behaviors.
- Construct synthetic and real-world evaluation datasets to validate model outputs at scale.
- Build scalable, production-grade data pipelines (e.g., using Apache Spark).
- Fine-tune and train workflows for open-source and proprietary LLMs.
- Integrate and optimize inference with platforms like vLLM, llama.cpp.
- Contribute to application development emphasizing modularity and traceability.
- Participate in and contribute to open-source projects within the LLM/agent ecosystem.
Requirements
Must-Have Skills
- 3–5 years of experience in machine learning focusing on LLMs, agent design, or tools.
- Experience in building LLM-based agents, including tool usage, planning, and memory systems.
- Designing and implementing evaluation frameworks, metrics, pipelines.
- Data engineering expertise with Apache Spark, Airflow or similar.
- Familiarity with inference systems such as vLLM, llama.cpp, TensorRT-LLM.
- Understanding of componentized ML systems.
Open-Source Contributions
- Proven track record in contributing to LLM-related open-source repositories.
- Experience maintaining open-source libraries or tooling.
- Strong Git/GitHub skills, including documentation and collaborative PR workflows.
- Ability to build tools, frameworks, or agents for community release.
Nice-to-Have Skills
- Familiarity with LLM orchestration frameworks: LangChain, CrewAI/AutoGen, Haystack, DSPy.
- Experience with LoRA, PEFT, or distributed training methods.
- Deployment experience in cloud environments (AWS, Kubernetes, Docker).
What We Offer
- Work on state-of-the-art LLM and agent tech.
- Support for open-source contributions.
- Fast-paced, collaborative, research environment.
- Influence over architectural decisions.
How to Apply
Please submit your resume, GitHub links, open-source projects, or technical writings to:
- nakul@rendernet.ai
- sriharsha@rendernet.ai
Job Highlights
[Insert key highlights here, e.g., "Opportunity to work on cutting-edge LLMs and open-source projects"]