Hire AI Engineers: Core Technical Domains
Your Steps To Hire AI Engineers
STEP 1
Call us and define your project
Tell us more about your needs on a discovery call! Within 24 hours, we’ll discuss your project requirements, success criteria, timescale, budget and required skill sets to see how we can help.
STEP 2
Get the developers you need
Through our careful vetting process, we identify AI engineers whose skills and soft skills match your project’s specific requirements. Interview and evaluate these engineers based on technical and company fit.
STEP 3
Seamless integration
Once chosen, our AI engineers blend into your team effortlessly, providing the support and innovation you need to drive your project forward, typically within just 7 days.
Hire AI Engineers for Algorithm and Model Development
Algorithm Development and Optimization
Crafting and refining machine learning algorithms for maximum efficiency and/or accuracy. AI engineers can also engage in research and experimentation to enhance current models.
Feature Engineering and Selection
Identifying and creating the most relevant features from raw data to improve model performance. This involves applying techniques to select the best subset of features that enhance the predictive power of models.
Data Engineering and Preprocessing
Gathering, cleaning, and prepping data for analysis and model training.
This involves leveraging big data technologies such as Hadoop, Spark, and SQL databases to manage and preprocess extensive datasets.
AI System Integration and Testing
Integrating AI solutions into existing systems and workflows.
Conducting comprehensive testing to validate the performance and robustness of AI models within different environments and use cases.
Ethics, Security, and User Experience
Implementing security measures to protect AI models and data. Ensuring compliance with privacy regulations and protecting sensitive information.
Developing intuitive interfaces and user experiences for AI applications. Ensuring that AI systems are accessible and user-friendly.
Complex AI Projects
As part of a collaboration with Bluebird, I had the opportunity to participate in several projects where we trained LLMs (Large Language Models) used by well-known tech giants to generate (program) source code.
In these projects, our task was to devise software problems where the problem description required complex language, posing a challenge for the models to understand, and for which assembling the solution was not a straightforward process.
The next step was writing the source code that provides an optimal solution to the problem formulated in the previous step, using Java, Python, and SQL. Essentially, we simulated a conversation with the AI, starting with a problem statement and then providing a solution, that is, we created prompts. In certain projects, this had to be divided into a 5-10 step process, and in each step, refining and modifying the source code according to the given rules until it reached its final form in the last step.
I also worked on several projects where we assembled coding prompts focused on Data Science. Here, coding in Python, using NumPy, Pandas, Matplotlib, and Seaborn libraries, we had to clean and transform the given data before further processing, then answer the predefined analytical questions based on the data.
This work required a lot of creativity and concentration, and it was challenging to come up with unique, sufficiently complex prompts week after week.
Zsolt Horvath | Bluebird
Software QA Team Lead (AI)
Hire AI Engineers to Contribute to These Products (and more)
By implementing natural language processing (NLP) algorithms, AI engineers enable these systems to understand and respond to user queries effectively. This results in more conversational and intuitive virtual assistants, enhancing user interaction and support.
AI engineers are crucial in developing fraud detection systems for banking and financial institutions. They build machine learning models that analyze transaction data to identify patterns and anomalies indicative of fraudulent activities.
These advanced models help reduce false positives and accurately detect fraudulent transactions, protecting customers and financial assets.
AI engineers play an important role in developing computer vision and sensor fusion technologies, which enable vehicles to accurately perceive their surroundings.
These experts are needed to develop models that can analyze X-rays, MRIs, and CT scans to detect abnormalities such as tumors or fractures. These tools assist healthcare professionals in making faster and more accurate diagnoses, directly improving patient care.
AI Engineers can design algorithms that analyze customer data to create targeted marketing campaigns and personalized content. This targeted approach allows businesses to reach their audience more effectively.
Hire AI Engineers for Fintech Projects
Building machine learning models that detect fraudulent transactions in real-time is a key area for AI Engineers. They use techniques like anomaly detection and neural networks to identify unusual patterns and flag potentially fraudulent activities.
AI engineers are crucial in developing fraud detection systems for banking and financial institutions. They build machine learning models that analyze transaction data to identify patterns and anomalies indicative of fraudulent activities.
These advanced models help reduce false positives and accurately detect fraudulent transactions, protecting customers and financial assets.
Developing AI-powered chatbots and virtual assistants that handle customer inquiries efficiently.
Another area where AI Engineers have an important role. They create systems that offer personalized financial advice based on an individual’s financial situation and goals. Analyzing spending habits, income, and market trends, these systems provide personalized recommendations for investments and savings.
AI engineers can also work on systems that help financial institutions comply with regulations by automating monitoring and reporting tasks. These systems analyze transactions and communications to detect compliance issues, reducing the risk of regulatory violations.
Why Hire AI Engineers through Bluebird
1
1st REASON
Trusted by Global Fortune 500 Companies
Proven track record in providing IT professionals for big brands like Blackrock, Ford, and GE.
2
2nd REASON
Impressive 95% Success Rate
Your projects are our top priority, and we take pride in delivering skilled IT professionals with a 95% success rate.
3
3rd REASON
IT Professionals Introduced in Just 7 Days
We prioritize speed without sacrificing quality, aiming to integrate AI talent into your team within 7 days. Onboard your new team members, manage performance, and scale your headcount as needed.
4
4th REASON
Diverse Talent Pool
We have a wide-reaching network of experienced AI professionals with varied skills and backgrounds.
5
5th REASON
Precision in Talent Matching
We prioritize a close match between the AI engineers' skills and your exact project requirements.
6
6th REASON
Comprehensive Support
From the day our experts start work on your project, our account managers offer continuous support to make sure everything goes smoothly.
7
7th REASON
Timezone Compatiblity
We offer engineers who can work within a 4-8 hour overlap with your team's schedule.
Engagement models
Aiming to add permanent members to your team?
Tech Recruitment
Would you like to expand your team with permanent hires? We have all the resources, domain-specific expertise and over a decade of experience to find the right remote IT/ tech professionals for you.
Looking to integrate AI engineers into your team at a daily rate?
IT Staff Augmentation
Add our experienced AI engineers to your team for any duration you need. Our professionals will fit right into your workflow while we manage all the administrative details.
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to hire AI Engineers
Hire AI Engineers: FAQs
AI Engineers are specialists who apply artificial intelligence and machine learning methodologies to build applications and systems. Their work aims to enhance organizational efficiency, reduce costs, boost profits, and facilitate more informed business decisions. These engineers play an increasingly key role in shaping the technological strategies of companies across various industries.
Coding is an essential and significant part of an AI engineer's role. These professionals spend a considerable amount of their time writing and refining code as they design, develop, and deploy AI systems and applications. The result: intelligent solutions that can automate tasks, analyze vast datasets, and solve complex problems across various domains.
AI engineers handle a wide range of tasks across various types of machine intelligence, including neural networks. Their goal is to create AI models for specific applications, using all available AI technologies.
In contrast, machine learning engineers focus mainly on developing and fine-tuning machine learning algorithms and models. These models are designed to learn and make predictions from large datasets automatically.
While both roles use data and algorithms, AI engineers typically cover the entire field of artificial intelligence, whereas machine learning engineers specialize in the details of machine learning.
An AI engineer in the fintech sector should possess a deep understanding of machine learning algorithms, data analytics, and programming languages such as Python and R. In addition to that, knowledge of financial principles, cybersecurity measures, and regulatory compliance is also important in this field.
These skills let AI engineers create solutions that are not only technologically advanced but also matched to the unique challenges of the fintech industry.
Getting started is easy! Contact us through our website or give us a call. We will discuss your project needs carefully and match you with the perfect AI Engineers—or other tech experts you need.