Description :

Job Title : Machine Learning Engineer

Experience : 4-12 Years

Location : Bangalore / Mumbai

Notice Period : Immediate Joiners Only

Role Overview :

We are hiring a Machine Learning Engineer (Mid-Level) to support the development and optimization of Small Language Models (SLMs) for enterprise applications. This role involves hands-on model fine-tuning, experimentation, evaluation, and RAG pipeline implementation.

You will work closely with senior ML engineers and MLOps teams to deliver scalable, high-performance AI solutions across multiple client engagements.

Key Responsibilities :

- Execute model fine-tuning and experimentation pipelines for Small Language Models (1B13B parameters) using frameworks such as Hugging Face Transformers, PyTorch, and techniques like PEFT/LoRA.

- Conduct model evaluation and benchmarking to measure performance metrics including accuracy, latency, throughput, and task-specific quality scores.

- Assist in building Retrieval-Augmented Generation (RAG) pipelines by implementing embedding generation, vector database integration, and retrieval mechanisms.

- Experiment with different hyperparameters, model configurations, and quantization approaches (FP16, INT8, INT4) to optimize performance.

- Prepare and preprocess training datasets, including cleaning, formatting, and validation for fine-tuning workflows.

- Support synthetic data generation and data augmentation efforts under senior engineer guidance.

- Document experiment results, configurations, and findings to ensure reproducibility and internal knowledge sharing.

- Collaborate with MLOps teams to test and deploy models on Amazon Web Services GPU instances (g5.xlarge, g5.2xlarge) and troubleshoot inference issues.

- Stay updated on emerging SLM research, new model releases, and fine-tuning best practices.

- Contribute to client deliverables by preparing performance reports, benchmarking summaries, and technical documentation.

Required Qualifications :

- Bachelors degree in Computer Science, Data Science, Engineering, or a related field.

- 4+ years of experience in machine learning, model training, or applied AI.

- Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or Hugging Face Transformers.

- Solid understanding of model evaluation metrics, experimentation practices, and MLOps workflows.

- Familiarity with cloud-based ML environments (AWS, GCP, or Azure) and version control tools like Git.

- Strong analytical thinking and problem-solving skills, with a proactive approach to experimentation and learning.