Machine Learning Engineer

Soul Ai; Dadri; On-site; INR 1,000,000 - 1,800,000; Part time

Job summary

Soul Ai in India seeks top-tier Machine Learning Engineers for a contract-based opportunity to design, deploy, and optimize AI models with industry leaders. Join an elite community of professionals tackling complex AI challenges; roles span 2-6 month projects with pay above market standards; experience with TensorFlow or PyTorch, MLOps, and multi-cloud deployments preferred.

Locations include major Indian tech hubs such as Mumbai, Delhi/NCR, Bengaluru, Kolkata, Chennai, Hyderabad, Ahmedabad,

Qualifications

• Experience in building, deploying, and optimizing AI models.
• Strong knowledge of ML frameworks and data pipelines.

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

Machine Learning

Deep Learning

Data Engineering

MLOps

Docker

Kubernetes

Kubeflow

MLflow

TFX

AWS

GCP

Azure

Tools

TensorFlow

PyTorch

Docker

Kubernetes

Kubeflow

MLflow

TFX

Spark

Kafka

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