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Virtual Aws Machine Learning Jobs in Arizona (NOW HIRING)

AI ML Engineer

Phoenix, AZ · On-site

$113K - $136K/yr

Statistical Modeling Machine Learning Regression Classification Clustering Time Series Forecasting ... Cloud Platforms Azure or AWS especially for data pipelines and model deployment * Data Engineering ...

AI Engineer

Phoenix, AZ · On-site

$55K - $187K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials - Utilizing ...

... AWS, Azure, or GCP) for AI model deployment and scaling Experience with MLOps practices and tools ... AI/ML (Artificial Intelligence & Machine Learning) Algorithms PRIMARY SKILL PERCENTAGE : 60 ...

Sr. Java Engineer

Scottsdale, AZ

$124K - $164K/yr

Experience with Big Data technologies (Spark, Hadoop, Hive) and Machine Learning frameworks is a ... Build and deploy cloud-native applications on AWS, Azure, and/or GCP. * Develop and optimize CI/CD ...

Data Architect

Chandler, AZ

$61.50 - $79/hr

Implement and support machine learning workflows in SageMaker for model training, deployment, and monitoring. * Leverage AWS Bedrock to build and deploy conversational AI solutions. * Ensure data ...

Develops, evaluates, and refines statistical, machine learning, and AI models using appropriate ... Experience working with cloud-based data platforms and infrastructure, such as Snowflake and AWS ...

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials ...

Showing results 41-60

Virtual Aws Machine Learning information

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Principal Data Scientist - Factory Intelligence (Tucson)

Prattwhitney

Tucson, AZ • On-site

$107K - $204K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 25 days ago


Job description

Principal Data Scientist – Factory Intelligence

Location: Tucson, Arizona. Work type: Hybrid. U.S. citizens only. Security clearance: Secret (required prior to start, interim clearance available).

What you will do
  • Transform factory data into actionable intelligence that improves production performance.
  • Collaborate with Engineering, Operations, and Quality teams to build and deploy predictive analytics solutions.
  • Develop models that directly impact yield, reduce variation, and support smarter decision‑making.
  • Design, deploy, and maintain production‑grade machine learning solutions.
  • Build intuitive data visualization tools and statistical analysis applications.
  • Partner with stakeholders to translate complex data into clear, practical insights.
  • Provide technical leadership and mentor junior data scientists and engineers.
  • Establish best practices in applied data science across the organization.
  • Become a subject‑matter expert in factory test data and uncover opportunities for improvement.
  • Solve challenging, data‑driven manufacturing problems and deliver measurable production enhancements.
  • Work directly with customers to ensure data is fully leveraged to improve performance.
  • Contribute to scalable, production‑ready data science solutions and help advance the organization’s analytics standards.
  • Operate effectively in a fast‑paced, multi‑tasking environment.
Qualifications You Must Have
  • University degree or equivalent experience and a minimum of 8 years of relevant experience, or an advanced degree and a minimum of 5 years of experience.
  • Experience developing in Python (NumPy, SciPy, scikit‑learn, scikit‑image) for production‑grade statistical or machine learning applications.
  • Demonstrated experience deploying, maintaining, and scaling machine learning models in production environments.
  • Experience with relational database management and SQL development.
  • U.S. citizen. Active and transferable U.S. government‑issued security clearance required prior to start; U.S. citizenship required as only citizens are eligible for a clearance.
Preferred Qualifications
  • Experience with statistical tools such as Minitab, R, JMP, or SAS.
  • Strong knowledge of machine learning pipelines and MLOps practices (e.g., MLflow), including versioning, monitoring, and lifecycle management.
  • Strong experience applying quantitative techniques (normalization, standardization, applied statistics) to analyze large, complex datasets and build deployable machine learning models, including in cloud environments such as AWS or Azure.
  • Experience designing, training, fine‑tuning, and deploying deep learning models using frameworks such as PyTorch or TensorFlow.
  • Experience working with large language models (LLMs), including fine‑tuning, evaluation, and deployment; or demonstrated deep knowledge of LLM concepts and architectures.
  • Experience operating in a technical leadership or mentoring role.

Salary range: $107,500 - $204,500 USD.

Benefits are available to Hired applicants, including medical, dental, vision, life insurance, short‑term and long‑term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits depend on the business unit and collective‑bargaining agreement.

RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans’ Readjustment Assistance Act.

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