Job Description

Make more Creative Job Post Content< Sr AI/ML R&D Scientist - Speech Technology Development

 - Responsibilities:

Location: Phoenix, AZ, 85004-3903
Company: APS

Are you passionate about turning data into actionable insights and solving complex problems with machine learning? Join APS as a Machine Learning Engineer and play a key role in driving innovation across our energy solutions. Your work will shape the future of sustainable energy through cutting-edge analytics, scalable architectures, and advanced ML models.

What You'll Do

As a Machine Learning Engineer at APS, your day-to-day will include:

MLOps & Deployment

• Design, build, deploy, and monitor ML models that improve business operations.
• Implement scalable solutions for processing and analyzing large data sets.
• Build CI/CD pipelines, containerized solutions, and robust monitoring systems.

Data Science Collaboration

• Partner with data scientists, architects, and cross-functional teams to design impactful solutions.
• Create innovative models, algorithms, and visualizations that uncover actionable insights.

Technical Leadership

• Mentor junior team members and conduct code reviews to ensure best practices.
• Develop comprehensive documentation and architecture diagrams for scalable solutions.

End-to-End Analytics

• Consult with stakeholders to understand business needs and translate them into data-driven solutions.
• Perform advanced data modeling, analysis, and prediction to address real-world challenges.

What We’re Looking For

Basic Qualifications:

• Education: Bachelor’s in Data Science, Computer Science, Engineering, Mathematics, or a related field.
• Experience:
  • 6+ years in data analytics, data science, predictive modeling, and ML solutions (or 4+ years with an advanced degree).
  • Proficiency in Python, SQL, and cloud-based ML tools (Azure, AWS, etc.).
  • Hands-on experience with MLOps practices, deployment pipelines, and cloud technologies.

Preferred Skills:

• Master’s or Doctorate in a relevant field.
• Expertise in PyTorch, TensorFlow, or other ML frameworks.
• Experience with generative AI and integrating ML inferences with web services.
• Familiarity with tools like Kubernetes, Docker, and PySpark for scaling infrastructure.
• Strong problem-solving, analytical, and communication skills.