Machine Learning Engineer

Soul Ai; Gurugram District; On-site; INR 900,000 - 1,500,000; Part time

Job summary

Soul Ai is seeking top-tier Machine Learning Engineers to design, deploy, and optimize AI models across multi-city projects in India. The role focuses on building scalable ML solutions, deploying them in production, and collaborating with industry leaders on cutting-edge AI challenges.

The position is contract-based with 2-6 month timelines, offering above-market compensation and opportunities to join an elite community of professionals.

Qualifications

• Proficiency in ML, DL, and data engineering (Spark, Kafka).
• Expertise in MLOps, automation tools and cloud platforms.
• Strong deployment, monitoring, security, and compliant AI practices.

Responsibilities

• Design, optimize, and deploy ML models and pipelines.
• Utilize TensorFlow, PyTorch; manage models in production (Docker, Kubernetes).
• Automate workflows; ensure versioning, logging and real-time monitoring.
• Work with large-scale data; develop feature stores; CI/CD for retraining.

Skills

ML

Deep Learning

Data Engineering

MLOps

Docker

Kubernetes

Kubeflow

MLflow

TFX

AWS

Tools

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