Senior GCP ML Engineer

OpenKyber LLC
United States
3 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Data Analysis Application Frameworks Artificial Neural Networks Cluster Analysis Python (Programming Language) Machine Learning Natural Language Processing Tensorflow Feature Engineering Pytorch Large Language Models
+4 more
Deep Learning Model Validation Scikit Learn Machine Learning Operations

Job description

Note: Due to client compliance requirements, we are unable to accept third-party or C2C (Corp-to-Corp) resumes for this role. Additionally, candidates requiring sponsorship now or in the future will not be considered Title:- Senior AI/ML Engineer Location:- Pittsburgh, PA (onsite) Duration:- 12+ Months Role Summary We are seeking a Senior AI/ML Engineer to design, build, and deploy scalable machine learning solutions that drive business outcomes. The role involves end-to-end ownership of ML models, collaboration with data, platform, and business teams, and mentoring junior engineers. Key Responsibilities Design, develop, and deploy machine learning and deep learning models for production use Translate business problems into AI/ML solutions with measurable impact Perform data analysis, feature engineering, model training, validation, and tuning Build and maintain ML pipelines (MLOps) for training, deployment, monitoring, and retraining Work with large-scale structured and unstructured

Requirements

datasets Collaborate with product, engineering, data, and cloud teams Ensure model performance, scalability, security, and compliance Mentor junior ML engineers and review technical designs and code Contribute to AI best practices, standards, and reusable frameworks Required Skills & Experience Experience in AI/ML, Data Science, or Advanced Analytics Strong hands-on experience with Python and ML libraries (TensorFlow, PyTorch, Scikit-learn) Solid understanding of ML algorithms: regression, classification, clustering, NLP, time series Experience with deep learning, neural networks, transformers, or LLM-based approaches

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