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The 10 most in-demand tech jobs for 2023 — and how to hire for them

CIO

For some that means getting a head start in filling this year’s most in-demand roles, which range from data-focused to security-related positions, according to Robert Half Technology’s 2023 IT salary report. Recruiting in the tech industry remains strong, according to the report.

LAN 358
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PepsiCo transforms for the digital era

CIO

Tapped to guide the company’s digital journey, as she had for firms such as P&G and Adidas, Kanioura has roughly 1,000 data engineers, software engineers, and data scientists working on a “human-centered model” to transform PepsiCo into a next-generation company. But there is more room to go.

Analytics 352
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Hire Big Data Engineer: Salaries, Stack and Roles

Mobilunity

Technologies that have expanded Big Data possibilities even further are cloud computing and graph databases. The cloud offers excellent scalability, while graph databases offer the ability to display incredible amounts of data in a way that makes analytics efficient and effective. Who is Big Data Engineer?

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5 hot IT hiring trends — and 5 going cold

CIO

Recruiters are opening the door for so much talent of different genders, education, nationalities, and beliefs,” Barley says. More and more companies are now walking the walk when it comes to inclusivity, not only during recruiting but in focusing on retention and working with employees on their career pathways,” she says.

Trends 328
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Rethinking the IT talent pipeline

CIO

Fast-forward five years and Merola is now a senior software engineer, writing code, promoting agile practices, and working with business partners to advance The Hartford’s digital agenda. “The The HartCode Academy changed my life and my career path completely,” says Merola. “The John Hill, SVP and CDIO, MSC Industrial Supply Co.

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How to Hire AI Developers?

Existek

Besides, it requires expert knowledge of software engineering, programming, and data science. Monitoring and maintenance: After deployment, AI software developers monitor the performance of the AI system, address arising issues, and update the model as needed to adapt to changing data distributions or business requirements.

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What you need to know about product management for AI

O'Reilly Media - Ideas

This shift requires a fundamental change in your software engineering practice. The model outputs produced by the same code will vary with changes to things like the size of the training data (number of labeled examples), network training parameters, and training run time. If you can’t walk, you’re unlikely to run.