While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
Location: India (Bangalore/Mumbai)
Experience: 5–6 years
Reports to: Senior Architect – Machine Learning
About the Role
We are looking for a strong software engineer who is excited to go deeper into Machine Learning and Generative AI engineering.
If you have solid backend development skills and bring an ML X-Factor—anything that shows genuine interest, initiative, or capability in ML/GenAI—this role is designed for you.
Your ML X-Factor could be:
self-initiated projects,
hackathon wins,
open-source contributions,
PoCs you built at work,
or any demonstrable evidence of curiosity and capability in ML/GenAI.
This is a 70% hands-on coding, 30% design role where you will learn, build, and shape internal GenAI solutions with guidance from the Senior Architect – ML.
Build and maintain RAG pipelines (we will guide you on best practices).
Develop agentic workflows using frameworks like Google Agent Development Kit.
Integrate GenAI functionality into backend services using Python/FastAPI.
Integrate LLMs with APIs, internal systems, and enterprise datasets.
Work on embedding pipelines, simple ETL workflows, and vector databases.
Help build evaluation, testing, and benchmarking workflows for GenAI outputs.
Translate product requirements into technical designs and implementation plans.
Participate in design discussions, code reviews, and best-practice engineering.
Work closely with product and engineering teams to deliver GenAI features end-to-end.
Deploy GenAI components using Docker, CI/CD, and GCP services.
Learn to optimize for performance, cost, reliability, and scalability.
This role is ideal if you are:
A Software Developer/Backend Engineer eager to transition into ML/GenAI.
Someone with an ML X-Factor—a spark in ML/GenAI that shows potential, not necessarily years of formal experience.
Excited about building systems end-to-end and growing into an architect-level path.
Open backgrounds include:
Backend Engineers (Python/Java/Node)
Full-stack developers
ML engineers with strong coding fundamentals
No research experience required.
Strong Python development experience (FastAPI is a plus).
Solid fundamentals in API design, clean architecture, debugging, testing.
Ability and eagerness to learn GenAI concepts and apply them in production.
You should bring at least one of the following:
Basic experience with LLMs, RAG, embeddings, or vector databases
Exposure to traditional ML solutions
Experience with any orchestrators/agent frameworks (we will train you on Google ADK)
Self-driven ML/GenAI projects, real-world PoCs, or hackathon achievements
Experience with Version Control and modern development workflows.
Any cloud exposure (GCP preferred but not mandatory).
Comfort working with Docker and CI/CD is a plus.
Ability to write clear technical documentation.
Strong ownership, problem-solving, and learning mindset.
Comfortable working in fast-paced, evolving environments.
Experience with Pinecone/Chroma/Weaviate.
Familiarity with Lang Chain/LlamaIndex.
Exposure to ML pipelines or classical ML.
Ideal opportunity for software engineers transitioning into GenAI.
Work directly with a Senior Architect – ML and grow toward an architect role.
Build real GenAI systems (RAG, agents, workflows) used across the organization.
Work with cutting-edge GenAI, agentic orchestration, and LLM deployment stacks.
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!