Artificial intelligence (AI) and machine learning (ML) are transforming the world, and with Oracle promising to push their potential even further with AI infrastructure, AI agents, and the AI-powered 23ai database, we’re at the forefront of this revolution. From transforming healthcare and the customer experience to helping organizations better interact with and understand their data, our AI solutions are solving major enterprise challenges everywhere. And with a wide range of AI-related careers across various disciplines, there have never been more unique opportunities for professionals to make a meaningful impact in this field.
Here, we’ll look at the world of AI careers at Oracle with three talent advisors: Cherish, Diana, and Nate. With their help, we’ll explore your career options, dig into key skills, and show you the experience that can help you succeed in this exciting new industry.
Opportunities for PhDs
AI may seem like a single field on the outside, but the supporting technologies that make it possible and the apps powered by it are everywhere.
Oracle’s AI solutions run layers deep, from superclusters and networking to high-performance computing and storage. And each layer contains lots of jobs in need of people with diverse skills and experience.
Our applied scientists are at the forefront of creating what’s possible with generative AI (GenAI). These specialists come to Oracle to define not only how this technology works but also how to make it relevant to business.
“For applied scientists, we generally look for candidates with PhD backgrounds with heavy research or project experience in building AI models to solve real-world problems. They’re usually contributing and submitting research papers in their area of expertise,” explains Principal Talent Advisor, Nate Wallace.
Programming the future
Research matters, but so does execution through engineering. Experienced programmers are well-placed to transition into AI with some key skills. Cherish Thomas, a senior member of our talent acquisition team, suggests that if you’re already a Java or C# programmer, then diving into AI-relevant languages like Python, R, Julia, Scala, and Go, as well as libraries and frameworks like Scikit-learn, TensorFlow, PyTorch, and Keras, will reap results.
Pivoting programmers can achieve this through courses and training on platforms like Oracle University, Coursera, Udacity, LeetCode, HackerRank, or Kaggle. Oracle certifications will also accelerate the process along with others like Google Professional ML Engineer, AWS Certified ML or TensorFlow Developer certification.
It’s important to examine your specializations and understand where you fit in the AI landscape. Nate notes that distributed systems backend engineers can find opportunities by learning more about ML Ops, data engineering, managing clusters, and building new model features.
Nate also highlights growing opportunities in AI services, deploying services, ML engineering, data engineering, solutions architecture, cognitive services engineering, robotics, and ethical AI engineering.
Cherish adds that employers are looking for a broad blend of qualities, including technical, analytical, and problem-solving skills, programming and software development, data analytics, cloud computing, and cybersecurity. Any combination of these can put you on track for AI opportunities.
Sales and solutions
Career paths in AI are just as varied as routes into the discipline. It’s natural to think that only purely technical roles are available, but sales and solution engineering roles are also critical. These professionals work closely with customers to understand their needs and develop tailored solutions.
In many ways, they’re the tip of the spear when it comes to spreading AI solutions, growing their application, and evangelizing to markets that might be unaware of their potential. After all, showing the value of Oracle Cloud Infrastructure and highlighting the impact that leveraging AI, ML, and GPUs can have on businesses is a crucial part of transforming industries and improving lives.
Product managers and business strategy experts are also finding fresh opportunities for their know-how on complex, fast-moving projects.
Technical careers that make AI possible
It’s important to remember that AI roles don’t always deal directly with AI itself. Oracle is building hundreds of new data centers to meet the growing demand for our AI and cloud services, and technical support positions like data center technicians ensure they run smoothly.
The infrastructure that supports LLMs and AI workloads relies on specialists like network engineers and technical support. These roles are generally responsible for managing and optimizing computer networks and ensuring efficient data transmission.
They also play a crucial role in accelerating the AI revolution through network management, including design, implementation, and maintenance.
Entry-level opportunities
So far, we’ve only spoken about opportunities for seasoned professionals, but early career prospects in AI are growing fast. Diana Nguyen works directly with campus candidates and understands that industry newcomers promise to be the future of AI—with the right fundamentals.
“To break into AI careers, students can start by focusing on building a strong foundation in mathematics, programming, and AI concepts,” she explains. “Developing proficiency in ML, deep learning, natural language processing, and computer vision (like Oracle leader, Jenny Griffiths) is essential for careers in AI.”
Practical experience is also something that students should cultivate as soon as possible. That can be through hands-on personal projects, school projects, and even internships. That said, it isn’t realistic to expect industry newcomers to be able to do everything. That’s why Oracle fosters a growth environment for interns and grads.
“As a new grad software engineer, you could have opportunities to contribute to AI-related projects alongside other engineers.” Diana shares. Oracle also offers ML training that caters to all levels, from beginners to advanced, ensuring there’s something for everyone.”
Apart from that, Diana emphasizes a familiar set of AI-geared languages. Namely Python, Java, or R, along with familiarity with AI frameworks like TensorFlow and PyTorch. And the sooner you can get to grips with them, the more likely it is you’ll thrive.
“Having a strong foundation in data structures and algorithms helps in solving complex problems,” she adds. “We look for candidates who have strong analytical skills, the ability to break down problems into smaller tasks, and creative problem-solving approaches.”
What makes a great candidate?
Skills, qualifications, and certifications matter, but what sets a good candidate apart from a great one can be harder to pin down. Nate has observed over time that candidates who can show contributions to building competing products or who have solved problems that Oracle is currently working on are highly valued.
Soft skills matter too and will show how you gel with people and hit goals. Cherish adds that aligning with company values like collaboration and innovation and being able to demonstrate passion for them helps candidates stand out. Critical thinking is also vital, and it pays to have ready examples of times you questioned processes and delivered smarter solutions.
Your time to show this combination of technical and soft skills is at the interview, but this isn’t always easy. Nerves, preparing for the wrong questions, and being uncertain in your aims can add up to missed opportunities.
Nail your interview
To combat this, Nate advises candidates to prepare to demonstrate hands-on technical interview skills related to the role and to discuss the positives and negatives of their project experience. You should also avoid going ‘too high level’ in your answers. Instead, take the chance to really show your understanding of specifics.
He also believes that candidates should practice making clear distinctions between ‘we’ and ‘I’ actions when discussing project experience. Taking credit for team efforts gives unrealistic expectations of your abilities, but not taking credit for your achievements means that interviewers may not see your full potential! Try to strike a balance.
If in doubt, check out our 25 tips to master the job interview to get off to the best possible start with your prep.
It’s clear that AI is well on the way to changing everything about how we work, create, and live. It’s clear too that the technology is opening doors to unprecedented opportunities for people with the right skills. The pace of change is only set to quicken, and the potential continues to grow. Making the right move now ensures that you’re a part of it tomorrow.
Help us make the world a better place through AI solutions. Explore our latest Oracle career opportunities now and join the Oracle Talent Network for advice, insights, and more.
Hear more from Greg Pavlik, EVP, AI and Data Management Services for Oracle Cloud Infrastructure.