Career Opportunity: Machine Learning Engineer – AI Consulting Firm (India)

Hiring: Machine Learning Engineer for AI-Powered Transformation (India)

A leading technology consulting firm is expanding its AI division in India. We are driving AI-powered transformationacross the finance, healthcare, retail, and manufacturing sectors. We deliver high-impact, scalable machine learning solutions—from predictive analytics to computer vision—for global enterprise clients.

We are looking for a Machine Learning Engineer to architect, build, and deploy end-to-end ML pipelines on-site. If you are passionate about model development and scalable deployments, this is your chance to accelerate global data-driven strategies.

 About the Role: End-to-End ML Pipeline Architecture

As an ML Engineer, you will bridge the gap between business requirements and technical execution. Your role is central to developing robust AI models that solve real-world industry challenges.

Key Responsibilities:

• Model Development: Build, train, and validate supervised and unsupervised models using Python, TensorFlow, and PyTorch.

• Pipeline Engineering: Design scalable data preprocessing and feature engineering workflows to maintain high data quality.

• Scalable Deployment: Deploy models as RESTful services utilising Docker, Kubernetes, and cloud-native stacks (AWS, GCP, or Azure).

• Performance Monitoring: Oversee production models, implement A/B testing, and manage automated retraining pipelines.

• Cross-Functional Collaboration: Partner with Data Engineers and DevOps to integrate ML components into enterprise applications.

 Skills & Qualifications: What We’re Looking For

The ideal candidate combines a deep understanding of mathematical modelling with modern software engineering best practices.

Must-Have Skills:

• Education: Bachelor’s or Master’s in Computer Science, Engineering, or a related field.

• Coding: Proficiency in Python and core libraries like scikit-learn.

• Deep Learning: Hands-on experience with TensorFlow and PyTorch.

• Cloud & DevOps: Expertise in Docker, Kubernetes, and cloud platforms. Solid understanding of Git, CI/CD, and unit testing.

Preferred (Bonus) Skills:

• MLOps Mastery: Experience with Kubeflow, MLflow, or SageMaker.

• Domain Expertise: Familiarity with NLP, computer vision, or time-series forecasting.

• Big Data: Knowledge of Spark, Hadoop, or Airflow.

• Certifications: AWS Certified ML Specialty or Azure AI Engineer certifications.

Benefits & Company Culture

Join a team that values innovation and continuous professional growth.

• Compensation: Competitive salary, comprehensive health insurance, and performance bonuses.

• Learning: Continuous mentorship, access to cutting-edge AI tools, and support for industry conferences.

• Environment: A collaborative on-site culture focused on knowledge sharing.

How to Apply

Ready to lead the AI revolution? Submit your application through our portal below.

1. Prepare your Resume: Highlight your experience in TensorFlow, PyTorch, and MLOps.

2. Submit Details: Fill in the application form and upload your documents.

Apply Now