AI Engineer, MLOps, 3 to 5 yrs

Fractal

. Deploy and operate advanced analytics machine learning models in collaboration with Data Scientists and Data Engineers .

Posted 9/15/2026full-timeBengaluru • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in deploying and operating machine learning models, developing scalable ML pipelines, and automating model operations across cloud environments. Proficient in collaborating with technical teams to deliver MLOps projects and troubleshoot complex issues.

Highest-signal resume keywords

MLOps DevelopmentMachine Learning Model DeploymentCI/CD Pipeline DevelopmentCloud Computing (AWS, Azure, GCP)Database Programming (SQL)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonPySparkJavaC#C++DockerSQLGitMLFlowKubeflow

Soft Skills

Problem-SolvingProject ManagementCommunicationCreative ThinkingTeam Handling

Tools & Technologies

KubeflowDataRobotHopsWorksDataikuML E2E PaaS/SaaS

Certifications & Qualifications

B.E.B.TechM.Tech

Industry Keywords

MLOpsMachine LearningCloud ComputingSystem IntegrationApplication Development

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformJavaPySparkPythonSQLC++

About the role

Key responsibilities & impact

Deploy and operate advanced analytics machine learning models in collaboration with Data Scientists and Data Engineers
Automate and streamline model development and model operations
Build and maintain tools for deployment, monitoring, and operations
Troubleshoot and resolve issues in development, testing, and production environments
Enable model tracking, experimentation, and automation
Develop scalable ML pipelines
Develop MLOps components throughout the machine learning development lifecycle
Use model repositories such as MLFlow or Kubeflow Model Registry
Work with machine learning services such as Kubeflow, DataRobot, HopsWorks, Dataiku, or relevant ML E2E PaaS/SaaS
Build knowledge required to deliver increasingly complex MLOps projects on AWS, Azure, GCP, or on-premises environments
Contribute to client business development and delivery engagements across multiple domains

Requirements

What you’ll need

3-5 years of experience building production-quality software
Strong experience in system integration, application development, or data warehouse projects across enterprise technologies
Basic knowledge of MLOps, machine learning, and Docker
Proficiency in an object-oriented language such as Python, PySpark, Java, C#, or C++
Experience developing CI/CD components for production-ready ML pipelines
Database programming using SQL
Knowledge of Git for source code management
Foundational knowledge of cloud computing in AWS, Azure, or GCP
B.E., B.Tech, or M.Tech in Computer Science or a related technical degree, or equivalent
Ability to collaborate effectively with highly technical resources in a fast-paced environment
Ability to solve complex challenges and rapidly deliver innovative solutions
Team handling, problem-solving, project management, communication, and creative thinking skills
Hunger and passion for learning new skills

Benefits

Comp & perks

Full-time employment
Opportunity to build expertise in MLOps and AI solutions
Exposure to state-of-the-art AI solutions and client engagements
Opportunities to work with cloud technologies (AWS, Azure, GCP)
Career growth in a fast-growing company
Future job alerts and opportunity introductions