Senior Machine Learning Engineer

HP•Spring, TX

10d•$147,050 - $230,850

About The Position

This role is responsible for leveraging expertise to design, develop, and implement cutting-edge machine learning models that solve complex challenges and enhance business processes. The role collaborates with cross-functional teams, to transform data into actionable insights by selecting, training, and optimizing machine learning algorithms. The role ensures that ML models are properly trained, validated, and optimized for performance.

Requirements

Four-year or Graduate Degree in Computer Science, Statistics, Mathematics, Data Science, or any other related discipline or commensurate work experience or demonstrated competence.
Typically has 7-10 years of work experience, preferably in computer programming languages, machine learning, algorithms, statistical methods, or a related field.
AWS Certified Machine Learning Specialty or equivalent
AI/ML Inference Infrastructure
Agile Methodology
Algorithms
Artificial Intelligence
Automation
Big Data
C++ (Programming Language)
Computer Science
CUDA
Data Science
Deep Learning
GenAI
Infrastructure Monitoring and Observability
Kubernetes
LLM Eval
LLMOps
Machine Learning
Model Quantization
Natural Language Processing
Python (Programming Language)
PyTorch (Machine Learning Library)
Retrieval-Augmented Generation (RAG)
Software Engineering
Vector Databases
vLLM
Effective Communication
Results Orientation
Learning Agility
Digital Fluency
Customer Centricity

Responsibilities

Architects, develops and programs integrated software solutions, especially in support of the development, deployment and life cycle of machine learning models.
Builds and maintains robust data pipelines and monitoring systems in distributed computing environments.
Defines collection protocols and analyzes data sources; develops, trains and evaluates models; creates visualizations of data properties and model performance.
Establishes and optimizes scalable processes for large-scale data operations to drive ML product improvements.
Engages with business and analytics teams to translate data requirements into technical solutions leveraging machine learning principles.
Collaborates with DevOps teams to integrate models into production systems and automate deployment processes.
Validates, communicates, and monitors the delivery of customer requirements for AI/ML solutions.
Participates in cutting-edge research in artificial intelligence and machine learning applications.
Stays up-to-date with the latest advancements in machine learning and related technologies.
Manages and maintains the compute cluster environment used to host and serve machine learning models, including capacity planning, performance monitoring, resource allocation, system reliability, and operational support.