Machine Learning Engineer

Soul Ai; New Delhi; On-site; INR 2,009,000 - 3,571,000; Part time

Job summary

Soul Ai in India invites top-tier Machine Learning Engineers to join a high-impact contract project with industry leaders. You will design, deploy, and optimize AI models across production environments.

This role focuses on advanced ML workflows, feature stores, and CI/CD pipelines. You will work with TensorFlow, PyTorch, Docker, and Kubernetes, ensuring scalable, secure deployments while collaborating with elite professionals.

Qualifications

• Experience building and deploying ML models
• Strong knowledge of MLOps and cloud platforms
• Proficiency in big data tooling is a plus

Responsibilities

• Design, optimize, and deploy machine learning models; implement feature engineering and scaling pipelines
• Use deep learning frameworks (TensorFlow, PyTorch) and manage models in production (Docker, Kubernetes)
• Automate workflows, ensure model versioning, logging, and real-time monitoring; comply with security and regulations
• Work with large-scale data, develop feature stores, and implement CI/CD pipelines for model retraining and performance tracking

Skills

MLOps

TensorFlow

Kubernetes

Tools

Docker

Kubeflow

MLflow

TFX

Job description

We are looking for Indias top 1% Machine Learning Engineers for a unique job opportunity to work with the industry leaders

Who can be a part of the community?

We are looking for top-tier Machine Learning Engineers with expertise in building, deploying, and optimizing AI models

If you have experience in this field then this is your chance to collaborate with industry leaders

Whats in it for you?

Pay above market standards

The role is going to be contract based with project timelines from 2-6 months, or freelancing

Be a part of Elite Community of professionals who can solve complex AI challenges

Responsibilities:

• Design, optimize, and deploy machine learning models; implement feature engineering and scaling pipelines
• Use deep learning frameworks (TensorFlow, PyTorch) and manage models in production (Docker, Kubernetes)
• Automate workflows, ensure model versioning, logging, and real-time monitoring; comply with security and regulations
• Work with large-scale data, develop feature stores, and implement CI/CD pipelines for model retraining and performance tracking

Required Skills:

• Proficiency in machine learning, deep learning, and data engineering (Spark, Kafka)
• Expertise in MLOps, automation tools (Docker, Kubernetes, Kubeflow, MLflow, TFX), and cloud platforms (AWS, GCP, Azure)
• Strong knowledge of model deployment, monitoring, security, compliance, and responsible AI practices

Nice to Have:

• Experience with A/B testing, Bayesian optimization, and hyperparameter tuning
• Familiarity with multi-cloud ML deployments and generative AI technologies (LLM fine-tuning, FAISS).

Locations : Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, India