MLOps Engineer

Team Geek Solutions; Bengaluru; Hybrid; INR 1,200,000 - 2,000,000; Full time

Job summary

Team Geek Solutions is seeking a skilled MLOps Engineer to build and deploy scalable ML pipelines using Python, Docker, and cloud services. The role focuses on implementing MLOps practices, setting up monitoring, and collaborating with data scientists to productionize models.

The position is hybrid with priority for Bengaluru or Hyderabad locations, requires 4-7 years experience, and immediate joiner availability.

Qualifications

• 3+ years in MLOps or related field with model deployment at scale.
• Proficiency in Python, Java, or C++ for ML pipelines and tooling.
• Experience with Docker, Kubernetes, and cloud platforms (AWS/Azure/GCP).

Responsibilities

• Develop and maintain ML pipelines for training, testing, and deployment.
• Design infrastructure to monitor and manage ML models.
• Collaborate with data scientists to automate model training and testing.
• Integrate ML models into production systems with software engineers.
• Automate deployment and scaling of ML workloads in distributed environments.
• Monitor ML systems for availability and performance; troubleshoot issues.
• Document MLOps processes and best practices.

Skills

MLOps

Python

DevOps

Docker

AWS

Azure

GCP

TensorFlow

PyTorch

Kubernetes

Java

C++

Education

Bachelor's or Master's in CS/EE or related field

Tools

Docker

Kubernetes

TensorFlow

PyTorch

Keras

AWS Console

GCP

Job description

Experience : 4 to 7 Years

Location : Hyderabad (Priority)/Bengaluru locations only

Notice Period : Immediate Joiner

Job Summary

We are looking for a skilled and proactive ML Engineer with strong expertise in Python, Databricks, and Machine Learning model development. The ideal candidate should be proficient in building scalable data pipelines and deploying ML models, with a working knowledge of MLOps principles and tooling. This role offers an opportunity to work on impactful AI/ML initiatives in a collaborative environment.

Job Title : MLOps Engineer

Mode: Hybrid

Key Responsibilities

• Develop and maintain machine learning pipelines for training, testing, and deploying models
• Design and implement infrastructure for managing and monitoring machine learning models
• Work with data scientists to build scalable, efficient, and automated model training and testing processes
• Collaborate with software engineers to integrate machine learning models into production systems
• Automate and optimize the deployment and scaling of machine learning models in a distributed computing environment
• Monitor and troubleshoot machine learning systems and infrastructure to ensure high availability and performance
• Develop and maintain documentation and best practices for MLOps processes and procedures.

Experience

Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field

• 3+ years of experience in MLOps or related field, including building and deploying machine learning models at scale
• Proficiency in programming languages such as Python, Java, and C++
• Experience with machine learning frameworks such as TensorFlow, PyTorch, and Keras
• Experience with containerization technologies such as Docker and Kubernetes
• Strong understanding of DevOps principles and practices
• Experience with cloud computing platforms such as AWS, Azure, or Google Cloud

Skills

Skills: MLOps, Python, DevOps, Docker, Amazon Web Services (AWS), Windows Azure, Microsoft Windows Azure, Google Cloud Platform (GCP), TensorFlow, PyTorch, Kubernetes and Java