Senior Staff Machine Learning Engineer

PowerSchool Group LLC • Dallas, TX

1d

About The Position

At PowerSchool, we are a dedicated team of innovators guided by our shared purpose of powering personalized education for students around the world. From the central office to the classroom to the home, PowerSchool supports the entire educational ecosystem as the global leader of cloud-based software for K-12 education. Our employees make it all possible, and a career with us means you’re joining a successful team committed to engaging, empowering, and improving the K-12 education experience everywhere.
Team Overview
Our Research & Development (R&D) team is the technical talent at the heart of our product suite, overseeing the product development lifecycle from concept to delivery. From engineering to quality assurance to data science, the R&D team ensures our customers seamlessly use our products and can depend on their consistency.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/Agents products in the areas of engineering, data, deployment and infrastructure.

Requirements

• You’re a highly technical research engineer with a strong understanding of the latest advancements in AI, especially GenAI - LLMs and Agents
• You have 5+ years of professional experience in software engineering, GenAI, machine learning, or applied research, with a proven ability to drive high-impact AI initiatives end to end.
• Strong working knowledge of deep learning, machine learning and statistics
• Some experience in complex SQLs and ETL transformations
• Experience related to AWS services such as SageMaker, Bedrock, EMR, S3, OpenSearch Service, Step Functions, Lambda, and EC2
• Hands on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer), machine learning, CV, GNN, or distributed training
• Strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts
• Demonstrated ability to design, implement, and scale machine learning workflows (ML OPs); including deployment and delivery of production-ready model APIs
• Proficiency with at least one machine learning lifecycle platform (Sagemaker, MLFlow, TensorFlow, etc.), orchestration platform (Airflow, Dagster, etc.) and data platform like SnowFlake/DataBricks
• You have a track record of implementing cutting-edge research into robust, scalable, and well-tested code.
• You bring a strong engineering mindset and write clean, efficient code that performs reliably in production.
• 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
• Master's degree in computer science, data science, mathematics, or a related field.

Responsibilities

• Uses Generative AI models (GPT4, Claude, Gemini), other LLMs, Agents and LangChains, CrewAI, Strands to build different AI, Agents driven intelligent solutions
• Experience in building GenAI based solution in auto-pilot or co-pilot mode which run in production at scale
• Experience in building Responsible AI guardrails and metrics around traditional AI or Gen AI models
• Familiar with latest Gen AI, Agent based products and AI coding tools in the market
• Fundamental understanding of NLP, transformer, embedding space and evaluation metrics
• Design and implement finetuning SLMs, Core Machine learning models and data ingestion pipelines
• Experience in dealing with "messy" enterprise data and building ETL transformations to facilitate more effective AI decision-making
• Experience in building software products used in production
• Create and maintain optimal data pipeline architecture by assembling large, complex data sets to meet functional and non-functional business requirements
• 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
• 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
• Establish standards and practices around MLOps, including governance, compliance, and data security
• Experience with AI or Agent driven complex ETL generation and data transformation preferred

Benefits

• Comprehensive Insurance Coverage (including Medical, Dental, Vision, Pharmacy benefits, Life Insurance and AD&D)
• Flexible Spending Accounts and Health Savings Accounts
• Short-Term Disability and Long-Term Disability
• Comprehensive 401(k) plan
• Generous Parental Leave
• Unrestricted paid time off (known as Discretionary Time Off - DTO)
• Wellness Program, including ClassPass & Employee Assistance Program
• Tuition Reimbursement
• Optional Benefits: Pet Insurance, Identity Theft Protection, Student Debt Repayment Program and Prepaid Legal coverage

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level