Challenging Opportunities For You To Learn And Grow Professionally Jobs in Atlanta, GA
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Looking for Challenging Opportunities For You To Learn And Grow Professionally jobs in Atlanta, GA? Browse our curated listings with transparent salary information to find the perfect Challenging Opportunities For You To Learn And Grow Professionally position in the Atlanta, GA area.
Procurement Tendering Manager - 60 Hz MSD
Company: GE Vernova
Location: Atlanta, GA / Remote
Posted Feb 07, 2025
Frequently Asked Questions
What are typical salary ranges by seniority in these challenging roles?
Junior AI/ML Engineers earn $90k–$110k, mid‑level $120k–$150k, senior $160k–$200k. Cloud Architects start at $110k–$140k, rise to $170k–$210k for senior architects, and can exceed $250k for principal roles. DevOps and Cybersecurity positions follow similar tiered ranges, with senior analysts earning $140k–$180k and experts over $200k.
Which skills and certifications are most demanded?
Core skills include Python, SQL, and version control. AI roles require TensorFlow, PyTorch, and Jupyter. Cloud positions demand AWS Certified Solutions Architect, GCP Professional Cloud Architect, or Azure Solutions Architect Expert, plus Terraform and Kubernetes. Cybersecurity roles favor CISSP, CISM, or CompTIA Security+ and hands‑on experience with SIEM tools like Splunk.
Is remote work available in these positions?
Approximately 70% of the listed roles support full‑remote or hybrid arrangements. Cloud and DevOps offers often allow work-from‑anywhere, while on‑site requirements are rare for AI/ML and data engineering, especially in companies emphasizing agility.
What career progression paths exist?
Typical ladders start at junior engineer → mid‑level → senior → tech lead → principal engineer → engineering manager or VP of Engineering. For cybersecurity, the path is analyst → senior analyst → lead analyst → security manager. Continuous learning and certifications accelerate movement up these tracks.
What industry trends shape these challenging opportunities?
Key trends include AI democratization through AutoML platforms, edge computing for low‑latency inference, cloud‑native security models, and data privacy regulations (GDPR, CCPA). Companies invest heavily in building resilient, scalable infrastructures that integrate AI, data, and security, driving demand for multi‑disciplinary talent.
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