Careers in Artificial Intelligence: Building a Future in AI

Recent advancements in AI, such as ChatGPT, Dall-E, and Tesla's Fully Self-Driving mode, have made it clear that AI is becoming an increasingly integral part of our lives. While it is understandable that some may have concerns about the impact of AI on employment, it is important to remember that many of the jobs that AI has taken over in the past have been those that are dangerous, repetitive, and unfulfilling. The reality is that AI has the potential to improve our lives by taking over these types of jobs and freeing up individuals to pursue more meaningful work.

However, it is important to note that AI does not have the capacity to care about its role in the workforce. As AI continues to improve and advance, it will undoubtedly have a significant impact on the job market. While some jobs may be replaced by AI, it is also important to recognize that AI will also create many new and exciting job opportunities. The field of AI is growing rapidly, and there are many career options available for those interested in this dynamic industry.

AI research scientist

At the core of AI is the role of the AI research scientist. These professionals conduct research and development in the field of artificial intelligence and machine learning, with the goal of creating new techniques and algorithms that can be applied to a wide range of problems. They typically work in academic institutions, research centers, or R&D departments of technology companies, and are at the forefront of developing new AI technologies. They also examine the broader implications of AI, such as its impact on different industries, ethical considerations, and potential environmental effects. The main objective for an AI research scientist is to generate new knowledge and advance the field, rather than addressing specific business challenges. These projects can take several years and require significant resources to complete.

The responsibilities of an AI research scientist are vast and encompass a wide range of knowledge and skills, including expertise in computer science, mathematics, and statistics, as well as the ability to think critically and creatively.

AI data scientist

An AI data scientist takes the theoretical concepts of AI research and applies them to real-world situations. They use their knowledge of artificial intelligence and machine learning to analyze and interpret large and complex data sets, with the goal of uncovering valuable insights and creating predictive models. Essentially, they bridge the gap between the high-level research and the practical implementation of AI technology.

AI data scientists often work on projects related to natural language processing, computer vision, or speech recognition. They fine-tune complex models to enable them to learn from data and make predictions or decisions without explicit programming.

To be successful in this role, AI data scientists must possess a deep understanding of machine learning algorithms and techniques, and have the ability to work with large and complex data sets. It is not a task of a couple of Excel spreadsheets.

Machine learning engineer

As we move further down the AI development process, we come to the stage of creating actual AI products and services for consumers. This is the role of a machine learning engineer.

They use their expertise in machine learning and software engineering to design, develop and implement systems that can learn from data and continually improve over time.

Machine learning engineers typically collaborate closely with data scientists to turn machine learning models from the research phase into functional products. While data scientists provide the algorithms, machine learning engineers are responsible for turning those algorithms into a tangible product.

Machine learning engineers must also integrate their models with existing software systems, which requires a solid understanding of software engineering principles and hands-on experience with deployment platforms and infrastructure.

For example, in the case of Tesla's self-driving mode, the data scientist will develop the program that allows the AI system to analyze its training history and identify patterns. The machine learning engineer's job is to then implement this algorithm into the Tesla vehicle, ensuring it works seamlessly with all the other technology in the car, such as the command for the car to hit the brakes when it recognizes a car running in front of it.

The responsibilities of a Machine Learning Engineer are often more extensive than that of a data scientist. Their primary objective is to bring the model to production readiness and ensure its performance and scalability.

AI product manager

For those who may not have a background in technology, there are still opportunities in AI. An AI product manager is a role that focuses more on sales and marketing than science or engineering.

These professionals are responsible for leading the development and launch of AI-based products and services. They must have a deep understanding of customer needs and market trends, and work with cross-functional teams to bring an AI product to market.

An AI product manager should have a solid grasp of AI and machine learning concepts, as well as knowledge of the industry and market in which the product will be used. However, they do not necessarily need to understand the technical details of how the AI technology works.

AI product managers can work in various settings such as technology companies, startups, consulting firms, or different industry verticals. They collaborate closely with data scientists, engineers, and other stakeholders to ensure that the product is developed and launched successfully.

To be successful in this role, an AI product manager must have the ability to balance technical knowledge, market understanding, customer needs, and business objectives to create and market a successful product.

AI consultant

An AI consultant is an expert who assists non-AI companies and organizations in identifying and implementing AI solutions to improve their business operations.

To be successful in this role, an AI consultant must have a comprehensive understanding of the field of AI and machine learning, including the various technologies and platforms available. They should also have specialized knowledge in a specific industry or domain and understand how AI can be applied to solve business challenges within that area. Due to this, many consultants choose to specialize in specific fields such as healthcare or agriculture.

Unlike other roles in AI, this role does not necessarily require a deep technical or scientific understanding of AI algorithms and machine learning, but instead a broad base of knowledge on the AI products and services available within certain sectors, what they do and how they work.

How you can get an AI investing assistant

If you're convinced that AI is the future and want to incorporate it into your daily life, you may be interested in using it to manage your investment portfolio. At Q.ai, we use AI to provide investors with access to advanced strategies that are typically only available to high-profile hedge fund clients.

For example, our Emerging Tech Kit utilizes AI to predict performance across four technology sectors, and then automatically adjusts the portfolio on a weekly basis based on these projections.