AI/ML Engineer – Classification & Retrieval Systems
Uplers
Bengaluru, Karnataka, IndiaENTRY
AIMachine LearningFintech
Job Description
Design and optimize classification systems for multiple clients.
Responsibilities
- We are looking for an AI/ML Engineer with a strong foundation in classification systems and a working understanding of modern LLM-based architectures. This role will focus on improving and fine-tuning our classification pipelines across clients, driving R&D on cost optimisation for LLM usage, and identifying opportunities to evolve our current systems into more intelligent, retrieval-augmented (RAG) architectures.
- Fine-tune and improve classification systems deployed across multiple clients.
- Lead R&D efforts focused on optimising the cost of LLM usage in production workflows.
- Evaluate current systems to identify areas where Retrieval-Augmented Generation (RAG) can be meaningfully employed.
- Drive the transition from standard LLM API usage (e.g., typical Gemini-style calls) to a more intelligent, context-aware RAG-based system.
- Collaborate closely with the engineering team to deploy models and endpoints into production.
Qualifications
- Salary: Confidential (based on experience)
- Shift: (GMT+05:30) Asia/Kolkata (IST)
- Opportunity Type: Office ()
- Placement Type: Full time Permanent Position
- (*Note: This is a requirement for one of Uplers' client - GenAI-native enterprise SaaS company)
- What do you need for this opportunity?
- rag, Retrieval-Augmented Generation, embeddings, LLM deployment, OpenAI API, Gemini api, Anthropic API, Ml classification pipelines
- GenAI-native enterprise SaaS company is Looking for:
- Job Description:
- NEUROFIN AI TECHNOLOGIES HSR Layout, Bengaluru, Karnataka
- Job Description: AI/ML Engineer – Classification & Retrieval Systems
- Location: HSR Layout, Bengaluru | Employment Type: Full-Time | Experience: 2+ Years
- About Neurofin
- 2+ years of relevant experience in AI/ML engineering.
- Strong foundations in coding logic and the mathematics behind machine learning.
- Hands-on, practical experience working with embeddings and RAG (Retrieval-Augmented Generation) systems — this is a mandatory requirement.
- Solid working knowledge of prompt engineering.
- Demonstrated experience deploying LLMs in production — either deploying an actual model (including smaller/open-source LLMs) or integrating and deploying via an API endpoint (Gemini, Anthropic, or OpenAI).
- Working knowledge of linear algebra as it applies to ML (bonus).
- Prior experience in the Fintech domain.
Nice to have
- Prior experience in Fintech
Benefits
- The opportunity to build foundational AI/ML systems from the ground up at an early-stage, high-growth AI FinTech startup.
- Direct exposure to real-world production LLM systems solving problems for the BFSI sector.
- A collaborative, fast-paced environment with high ownership and visibility into company outcomes.
- Competitive compensation, aligned with experience and market standards.
- Step 1: Click On Apply! And Register or Login on our portal.
- Step 2: Complete the Screening Form & Upload updated Resume
- Step 3: Increase your chances to get shortlisted & meet the client for the Interview!