By: Kurt Scholl, Vice President of Recruiting, BravoTECH
Artificial Intelligence (AI) is disrupting nearly every industry, from healthcare to finance and companies are scrambling to integrate AI and machine learning into their operations.
And while you may have seen news of layoffs and reduced staff due to AI there’s a question many are starting to ask: Should I be looking at AI jobs? Balancing those layoffs is a surge in new roles AI-savvy professionals.
AI and machine learning job postings have grown nearly 9x since 2022, and LinkedIn reports that AI-related roles have increased by 74% annually over the last few years. According to the U.S. Bureau of Labor Statistics, careers in computer and information research – which includes AI and machine learning – are slated to grow 26% by 2033.
Translation? The AI job market isn’t just hot, it’s exploding. And now is the time to get your foot in the door for what could be the career of the future.
But here’s the reality: breaking into AI isn’t as simple as taking a weekend online bootcamp. These roles demand real technical expertise like programming skills, data systems experience, cloud infrastructure knowledge.
If you’re already working in technology or have a strong technical background, AI represents a powerful career pivot with strong long-term growth potential.
The good news? If you have the right experience and are willing to invest in building AI-specific skills, there may just be a perfect AI job for you.
What is an “AI Job”?
Before we take a look at particular roles, let’s get an idea of what these jobs actually look like.
At its core, AI refers to systems that perform tasks typically requiring some level of human intelligence. This could include visual perception, speech recognition, decision-making, or language translation.
Machine learning is a subset of AI focused on systems that learn from experience without being explicitly programmed.
Within machine learning, you’ll find a few specialized areas:
- Deep Learning: Deep learning uses neural networks to process complex data
- Natural Language Processing (NLP): Natural language processing is what allows machines to understand human language
- Computer Vision: Computer vision gives machines the ability to interpret images and videos,
- Reinforcement Learning: This is the field focused on training AI models through trial and error
This means that when we talk about jobs in AI, we’re not looking at one single career path or role. The field has an entire ecosystem of roles, with jobs ranging from research scientists to engineers, data annotators to product managers.
For experienced IT professionals, this means your existing skills in software development, cloud infrastructure, or even data engineering could translate perfectly into an AI-focused role.
15 Machine Learning & AI Jobs Hiring Right Now
Contract AI Positions
1. AI Data Analyst
This is one of the fastest-growing AI roles on the market. An AI data analyst will spend their days analyzing AI-generated data and model outputs to optimize machine learning performance. This role combines statistical analysis with proficiency in AI tools – and exists across a variety of industries.
2. AI/Digital Solutions Consultant
Are you more of a consultant-minded professional? This role exists to help guide organizations through AI adoption and digital transformation. You’ll help teams assess their current systems, recommend the best AI solutions, and implement them while ensuring the designs are functional and scalable.
3. Principal Software Engineer – AI/ML Platform
Want to get in on the ground floor of AI design? This role is all about building the foundational platforms that enable AI and machine learning at scale. But in a lead role, you’ll also manage architecture decisions, mentor engineering teams, and perform other executive functions.
4. Lead AI Platform Engineer
This role will have you overseeing the development and maintenance of AI platforms. In particular, these platforms support model training, deployment, and monitoring through AI – essential for data science teams to perform their roles.
5. Lead Cloud Engineer – Cloud & TechOps
A lead cloud engineer will help manage cloud infrastructure, which is increasingly necessary to support massive AI workloads. Expertise in AWS, Azure, or Google Cloud is essential for supporting compute-intensive AI systems.
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6. Application and Cloud Architect
Design comprehensive architectures that integrate AI applications with cloud infrastructure. Bridge the gap between application developers and infrastructure teams to ensure scalable, secure AI deployments.
7. OpenShift Cloud Engineer
This role is highly specific and involves deploying and managing containerized AI applications using Red Hat OpenShift. You’ll likely need experience in handling Kubernetes orchestration, as well as CI/CD pipelines for AI workloads in enterprise environments.
8. Cloud Architect
Big AI needs big data solutions. A cloud architect is responsible for designing and maintaining cloud infrastructure to support AI and machine learning. You’ll evaluate technology, design for scalability and cost-efficiency, and ensure compliance across cloud platforms.
Core AI and Machine Learning Positions
9. Machine Learning Engineer
On the more intensive side, a machine learning engineer will be involved with the design and deployment of predictive models in production environments. You’ll likely work with frameworks like TensorFlow and PyTorch to build scalable systems for a variety of different industry use cases.
10. AI Engineer
This role will have you developing AI-driven applications and automation tools for SaaS, logistics, manufacturing, and other industries. You’ll be responsible for creating intelligent systems that solve real business problems every single day.
11. Data Scientist
Do you enjoy analyzing large datasets? Enjoy using data to drive strategic decisions? An AI data scientist works with company leaders to build predictive models using AI and ML.
12. NLP Engineer
An NLP engineer is responsible for building language systems that are used by chatbots, voice assistants, and text analytics tools. The demand for this role has surged with the growth of generative AI, making it one of the hottest specializations in AI.
13. Computer Vision Engineer
One of the fastest-growing use cases for AI is integration with computer vision. This engineer will help develop systems for facial recognition, autonomous vehicles, and more – across a ton of different industries.
14. AI Research Scientist
If you want a role where you push the boundaries of AI, an AI Research Scientist may be a great fit! These professionals develop new algorithms and models, typically in academic settings or specialized AI companies. This role also includes publishing research and collaborating with other researchers.
15. MLOps Engineer
An MLOps Engineer is responsible for deploying, monitoring, and maintaining machine learning models in production at scale. This role will bridge the gap between data science and DevOps, and will likely engage with cloud platforms and ML frameworks.
Work With Us
For over 30 years, BravoTECH has been connecting skilled IT professionals with opportunities that match their expertise and passions. We know the technical landscape well, and we know what companies are searching for to fill AI roles.
Whether you’re an experienced software engineer ready to jump into AI or looking to pivot into a Machine Learning role, we work with clients who value your skills.
The AI revolution is here. The jobs are real, and the opportunities are growing. If you have the experience, we have the connections to help you find your next best career move.
Contact BravoTECH today to learn how we can help you navigate the AI job market and land the machine learning role that fits your skills and ambitions.
About the Author
Kurt has led BravoTECH’s onshore and offshore recruiting delivery operations across the U.S. and India since joining the organization in 2018. With over twenty years of experience in the staffing industry, he drives strategic growth, operational excellence and innovation in talent acquisition. A U.S. Navy veteran, Kurt also champions BravoTECH’s veteran initiatives.
Frequently Asked Questions
Do I need a PhD to work in AI and machine learning?
Not necessarily, though educational requirements will vary by role. Research scientist positions typically require advanced degrees, but many engineering and platform roles value hands-on experience with AI technologies and software development. Strong portfolios demonstrating real-world AI project experience can be as valuable as formal credentials.
Which programming languages should I learn for AI jobs?
There are many different options, but Python is usually a must for AI and ML work. SQL is great for database work, and R is valuable for statistical analysis. Roles such as AI Platform Engineer or Cloud Architect typically require years of experience in infrastructure and systems design.
Are AI jobs only in tech companies?
Absolutely not! As AI grows, you’ll find that it starts to enhance and interact with nearly every field. Healthcare, finance, manufacturing, retail, and marketing all hire extensively for AI roles – and that list is growing fast!
Is the AI job market sustainable or just a bubble?
All indicators suggest sustained growth in the AI field. The World Economic Forum projects AI expertise will be among the fastest-growing skill areas through 2030, with annualized growth rates above 30%. As organizations move from experimental AI to production systems, demand for experienced professionals to build and maintain AI infrastructure continues to grow.