Machine Learning Engineer

Soul Ai; Chennai; In loco; INR 1.674.000 - 2.567.000; Tempo pieno

Descrizione del lavoro

Soul Ai is seeking India’s top-tier Machine Learning Engineers for a contract-based opportunity to design, deploy, and optimize AI models with industry leaders in Chennai and other major Indian cities.

You will work on end-to-end ML pipelines using TensorFlow/PyTorch, Docker, Kubernetes, and modern MLOps tools, solving complex AI challenges while ensuring security and scalability.

Competenze

• Strong foundation in ML/DL and data engineering
• Experience deploying models to production and monitoring
• Familiarity with MLOps tools and cloud platforms

Mansioni

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

Conoscenze

Machine learning

Deep learning

Data engineering

MLOps

Docker/Kubernetes

Strumenti

Docker

Kubernetes

Kubeflow

MLflow

TFX

Spark

Kafka

Descrizione del lavoro

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