Machine Learning Engineer

ROLE PROFILE

Designs and develops scalable machine learning models and AI-driven solutions to address complex business challenges and enhance decision-making processes

KEY RESPONSIBILITIES

Work with large and complex data sets to solve challenging business problems

Efficient training and deployment of standard ML, NN, and Agentic models.

Develop, train, and optimize machine learning models using state-of-the-art algorithms and frameworks

Build production grade end-to-end ML pipelines, including data ingestion, transformation, model training, validation, and deployment

Automate workflows for model training, testing, and deployment using CI/CD pipelines and MLOps tools

Collaborate with cross-functional teams to integrate models into applications and deliver end-to-end solutions

Finetune SLMs/LLMs and build complex AI architectures

PROFESSIONAL EXPERIENCE/QUALIFICATIONS

(3-7) years of experience in building production grade, scalable AI systems.

Expert in supervised/unsupervised learning, deep learning, NLP, computer vision, or generative AI (e.g., LLMs).

Strong ML system architecture skills

Understanding of model serving, API development (FastAPI, Flask), and optimizing model performance for real-time or batch inference.

General Knowledge of Docker, Kubernetes, CI/CD pipelines, and tools like MLflow/Kubeflow for model lifecycle management (MLOps)

Comfortable with deploying models on AWS or Azure

Minimum Educational qualifications: Bachelor’s degree in Computer Science, Engineering, or related field required

Preferred Education qualifications: Master or PhD in Computer Science or a related field.

Skills: Machine Learning , AI-driven solutions , ML system architecture