ML Engineer

This role is for one of Weekday’s clients
Salary range: Rs 5000000 - Rs 15000000 (ie INR 50 - 150 LPA)

Min Experience: 1+ years
Location: Bengaluru, Karnataka
JobType: full-time

We are looking for a talented Machine Learning Engineer with 1–8 years of experience to design, develop, and deploy intelligent machine learning systems, with a strong focus on Large Language Models (LLMs). You will work on building production-grade AI solutions, improving model performance, and integrating advanced language-model capabilities into scalable products.

The ideal candidate combines strong machine learning fundamentals with hands-on experience working with LLMs, model training or fine-tuning, inference, evaluation, and AI application development.

• Design, develop, and deploy machine learning models and AI-powered applications with a primary focus on LLM-based solutions.
• Work with pre-trained language models for tasks such as text generation, classification, summarization, information extraction, question answering, and conversational AI.
• Fine-tune and optimize LLMs using techniques such as supervised fine-tuning, parameter-efficient fine-tuning, LoRA, and related approaches.
• Develop robust data pipelines for collecting, cleaning, preprocessing, and preparing datasets for model training and evaluation.
• Experiment with model architectures, prompting strategies, embeddings, retrieval techniques, and inference approaches to improve system performance.
• Build and maintain evaluation frameworks to measure model quality, accuracy, relevance, latency, and reliability.
• Collaborate with product, engineering, and data teams to translate business requirements into scalable machine learning solutions.
• Optimize models for production environments, considering inference cost, latency, scalability, and resource utilization.
• Monitor deployed models and continuously improve their performance based on real-world feedback and evaluation results.
• Stay current with advances in LLMs, generative AI, machine learning research, and emerging AI engineering practices.

• 1–8 years of professional experience in Machine Learning, AI, Data Science, or a related field.
• Strong hands-on experience with Large Language Models (LLMs) and generative AI.
• Strong understanding of machine learning concepts, algorithms, model evaluation, and optimization.
• Experience with Python and commonly used machine learning frameworks and libraries.
• Understanding of NLP concepts, transformer architectures, embeddings, tokenization, and model inference.
• Experience working with LLM APIs, open-source language models, or enterprise AI platforms.
• Ability to design, experiment with, evaluate, and productionize ML/LLM solutions.
• Strong analytical, problem-solving, and debugging skills.

• Experience working with foundational models and open-source models such as Llama, Mistral, Gemma, or similar architectures.
• Experience with model fine-tuning, quantization, distillation, and parameter-efficient training techniques.
• Knowledge of RAG architectures, vector databases, semantic search, and embedding models.
• Familiarity with PyTorch, TensorFlow, Hugging Face Transformers, or similar frameworks.
• Experience with distributed training, GPU optimization, or high-performance inference.
• Knowledge of MLOps, model deployment, monitoring, and cloud-based ML infrastructure.
• Familiarity with prompt engineering, AI agents, multimodal models, or reinforcement learning from human feedback.