Senior Machine Learning Engineer
Artificial Intelligence
Data Analysis
Data Pipeline
Data Processing
Data Science
Data Science Ml
DevOps
Engineer
Generative AI
Generative Ai Engineer
Large Language Models
Machine Learning
Machine Learning Engineer
Machine Learning Evaluation
Machine Learning Infrastructure
Machine Learning Models
Machine Learning Pipelines
Ml Ops
Programming
Programming Language
Programming Languages
Job Description
Build and productionize machine learning solutions for customer and business outcomes in Spring, TX.
Responsibilities
- Architect, design, and implement integrated software solutions for the development, deployment, and lifecycle of machine learning models
- Build and maintain robust data pipelines and monitoring systems for distributed computing environments
- Define data collection protocols and analyze data sources
- Develop, train, evaluate, and optimize machine learning models
- Create visualizations of data properties and model performance
- Establish and optimize scalable processes for large-scale data operations to improve ML product outcomes
- Partner with business and analytics teams to translate data requirements into technical solutions using ML principles
- Collaborate with DevOps teams to integrate models into production systems and automate deployment workflows
- Validate, communicate, and monitor delivery of customer requirements for AI/ML solutions
- Contribute to cutting-edge research in artificial intelligence and machine learning applications
- Keep current with advancements in machine learning and related technologies
- Manage and maintain the compute cluster environment for hosting and serving ML models, including capacity planning, performance monitoring, resource allocation, system reliability, and operational support
Requirements
- Four-year or graduate degree in Computer Science, Statistics, Mathematics, Data Science, or a related discipline, or commensurate work experience/demonstrated competence
- Typically 7-10 years of work experience, preferably with computer programming languages, machine learning, algorithms, statistical methods, or a related field
Technologies
- AWS Certified Machine Learning Specialty
- C++
- CUDA
- Kubernetes
- Python
- PyTorch
- GenAI
- Retrieval-Augmented Generation (RAG)
- Vector Databases
- vLLM
- LLM Eval
- LLMOps
- Model Quantization
- Natural Language Processing
Knowledge & Skills
- AI/ML Inference Infrastructure
- Agile Methodology
- Algorithms
- Artificial Intelligence
- Automation
- Big Data
- Computer Science
- Deep Learning
- GenAI
- Infrastructure Monitoring and Observability
- LLM Eval
- LLMOps
- Machine Learning
- Model Quantization
- Natural Language Processing
- Retrieval-Augmented Generation (RAG)
- Software Engineering
- Vector Databases
- vLLM
Preferred Certifications
- AWS Certified Machine Learning Specialty or equivalent
Benefits
- Health insurance
- Dental insurance
- Vision insurance
- Long term/short term disability insurance
- Employee assistance program
- Flexible spending account
- Life insurance
- 4-12 weeks fully paid parental leave based on tenure
- 11 paid holidays
- Additional flexible paid vacation and sick leave
- US benefits overview: https://hpbenefits.ce.alight.com/
Impact & Scope
- Impacts function and leads and/or provides expertise to functional project teams
- May participate in cross-functional initiatives
Complexity
- Works on complex problems where analysis of situations or data requires an in-depth evaluation of multiple factors
Pay & Benefits
- Pay range: $147,050 to $230,850 USD annually
- Additional opportunities for pay via bonus and/or equity (United States of America candidates only)
- Pay varies by work location, job-related knowledge, skills, and experience
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