Pivoting your Developer career into AI? Here’s What to know in 2025

By Akshay Sharma October 18, 2024 Business

Artificial Intelligence is the trendy buzzword in the tech arena and rapidly integrates with every sector to transform them into a powerful technological force. The latest version of automated tools and AI’s capability are catchy phrases for newcomers and experienced professionals.

AI trends are reflecting it as a powerful and immersive technology that has the power to work on large amounts of datasets, understand the patterns, and predict future outcomes, ultimately empowering an organization to enter the world of new adaptation and innovation. With it, continuous growth and impactful impression make it an attention-grabbing area for anyone looking for a smooth career in the digital world.

Here is the roadmap that guides how to the beat challenges and difficult tracks of the AI revolution and create a future-proof career.

The professionals seeking a career change must be ready for multiple sets of challenges. Undoubtedly, this immersive technology is rewarding and exciting.

Improve technical skills: It is very important to identify the interest areas in technical subjects. Most AI jobs need programming skills and practical knowledge of subjects like Python, R, TensorFlow, and sci-kit-learn. Besides experience in AI framework, the job seeker should have a conceptual understanding of machine learning, statistics, and deep learning.
For a better job transition, it is very important to acquire the mandatory skills and practical knowledge. Acquire the top AI certification in 2025, and show your credibility and skills validation. There are multiple artificial intelligence certification courses or formal degree programs that cover fundamental concepts about neural networks, machine learning, deep learning, and data mining.
Concentrate on Specific Industry Domain: The foremost thing is to bring clarity to your vision and decide your area of interest. AI is a ruling technology across every sector; it means AI is not limited to technical profile. Target your aim and choose any technical role like data scientist and robotics engineer or a non-technical role such as AI business analyst and AI project manager to craft a successful career in AI.
It is very important to do self-actualization to find out which job profile matches your skills and capabilities.
Connect with open-source projects: The theoretical knowledge is not enough to get AI jobs, so take the initiative and start working on some online projects to upgrade your skills and knowledge. The on-field training, internship, and online open-source projects are self-taught techniques. A little bit of effort can enhance practical knowledge and help to build an impressive portfolio.
Embrace Perpetual Learning: Of course, continuous learning helps an individual to know more about the toolbox, new methods, frameworks, and industry tactics. The latest report by McKinsey & Company mentioned that by 2030, 30% of working hours in European countries and the United States could be done by generative AI. It is very crucial to enhance AI skills and focus on creativity, problem-solving mechanisms, and domain knowledge to remain updated.

The Scope of Career

An aspirant looking for better opportunities in the AI field must remain up-to-date and have deep knowledge of neural networks, programming languages like Python, and relevant platforms like cloud services. With good experience and skill sets, an individual can try their luck in these key areas.

Data Science: A non-technical candidate can also apply for AI jobs. The Data Scientist adds intelligence and by utilizing the unprocessed data generated from social media platforms and other internet sources like web traffic, reference links. As per the PayScale, a fresher with a tag entry-level data scientist can earn around $85,075. Data science is the perfect mixing of ML and Statistics.
Machine Learning: A person with strong technical knowledge can apply for this job role. He/she should know programming frameworks and know how to operate big data tools. Their role and responsibility is to work on multiple models and algorithms that can predict future outcomes. According to Glassdoor, the average salary range of an ML Engineer in the US is $131,000.
AI Engineer: A techie with a strong knowledge of programming languages like Java, Python, R, and C++ can become AI experts. AI engineers are hired to implement and create AI models, real-time-based applications and infrastructure using their theoretical knowledge and practical approach. According to Indeed, an Artificial Intelligence engineer can get a handsome salary ranging from $114K – $212K/yr.

Final Thought:

The professionals who are interested in the AI career track should focus on their technical skills, problem-solving skills and communication skills. Though, a master’s degree in computer science is not mandatory but aspirants should have Bachelor’s Degree in CS or IT to apply for entry-level jobs.