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Engaged Employer

PowerSchool India

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3.8

based on 255 Reviews

48 PowerSchool India Jobs

Machine Learning Engineer 2

PowerSchool

3.8

based on 255 Reviews

5-9 years

Bangalore / Bengaluru

1 vacancy

Machine Learning Engineer 2

PowerSchool India

posted 1mon ago

Job Role Insights

Flexible timing

Key skills for the job

Medical Coding Automation Testing Machine Learning CCTV Monitoring Data Security Production Operations

+ 3 more

Job Description

This position, under the general direction of the Lead and/or Manager, Machine Learning Engineering, will be responsible for technical and development support for our award-winning K-12 software. This role will help in all AI/generative AI products in the areas of engineering, data, deployment and infrastructure .

Responsibilities

Design and implement Machine learning models and data ingestion pipelines
Develop and support a platform that enables data scientists to rapidly develop, train, and experiment with machine learning models
Expand and optimize data pipelines, data flow, and collection for cross functional teams
Create and maintain optimal data pipeline architecture by assembling large, complex data sets to meet functional and non-functional business requirements
Identify and implement internal process improvements including automating manual processes, optimizing data delivery, and redesigning infrastructure for greater scalability
Support the building of machine learning, data platforms, and infrastructure required for optimal data extraction, transformations, and loading of data from a wide variety of data sources
Work with architecture, data, and design teams to assist with data related technical issues and support data infrastructure needs
Deploy ML models in AWS environment specifically in AWS Sage Maker environment
Implement Model Monitoring, Data Quality Checks, Data Drifts in Inference Pipelines
Support ML teams in the delivery of continuous integration, continuous deployment, providing templates and patterns
Perform root cause analysis for production issues where the root cause is in infrastructure, environment, configuration, or deployment routines; understand when to escalate to product development teams; remediate root causes and implement preventative actions
Own the AWS stack which comprises all ML resources and collaborate on managing ML infrastructure costs
Establish standards and practices around MLOps , including governance, compliance, and data security
Uses Generative AI models (GPT4, Claude, Llama), other LLMs, Agents and LangChains to build different smart solutions
Uses customer management system to provide status on open customer issues and properly verifies when an issue can be closed
Participate in afterhours maintenance, when necessary, respond to emergencies, participate in customer calls when called upon in support of initiatives and incident response

Qualifications include:

At least 5+ years of experience within the full software development lifecycle from planning through deployment and maintenance
Demonstrated ability to design, implement, and scale machine learning workflows (ML OPs); including deployment and delivery of production-ready model APIs
Demonstrated proficiency with version control systems and automated software testing and delivery
Proficiency with at least one machine learning lifecycle platform ( Sagemaker , MLFlow , TensorFlow, etc.), orchestration platform (Airflow, Dagster , etc.) and data platform like SnowFlake / DataBricks
5+ years of experience with ML infrastructure and ML DevOps
5+ years of overall engineering experience in distributed systems and data infrastructure
3+ years experience coding in Python (preferred) or other languages like Java, C#, etc.
Experience working with ML engineers to build tooling and automation to support the entire ML engineering lifecycle, from experimentation to production operations
Experience with Kubernetes and ML CI/CD workflows
3+ years experience with AWS or other public cloud platforms (GCP, Azure, etc.)
Excellent verbal and written communication skills.
Experience with Infrastructure-as-Code tools and frameworks
Bachelors degree in computer science, data science, mathematics, or a related field. Master s degree preferred