An AI Researcher in industry leads the development of models and algorithms that address real organizational needs, drawing on expertise in AI, statistics, and mathematics. The role involves developing a deep understanding of business problems and the ability to frame them in a way that enables data driven solutions based on the data available within the organization. This includes selecting appropriate approaches and building models that can be implemented in a production environment.
This is a highly applied role that combines analytical thinking, systematic work with data, and the ability to take a model from initial concept to a working solution within an existing system.
AI Researchers operate at the core of the model layer while maintaining a strong understanding the broader system in which their solutions are integrated. As a result, their work is not purely theoretical but becomes part of an active product or operational system.
An AI Researcher is responsible for developing and leading model development as part of AI and Data teams.
Key responsibilities include:
The role combines deep analytical thinking with hands on responsibility for delivering practical solutions within an industrial R&D environment.
The AI Researcher career track is designed to prepare participants for advanced AI and Data roles in the industry. Depending on their academic background and personal profile, graduates typically pursue positions such as:
The program is intended for individuals who aim to join R&D teams and work on building models, analyzing data, and developing AI solutions as part of active products.
The work combines model development, working with data infrastructure, and collaboration with engineering and product teams, with the goal of creating solutions that deliver real business value.
The AI Researcher career track in industry (AI Research) is an intensive 32 week training program designed for STEM graduates who want to enter advanced AI roles and lead the development of models, machine learning systems, and AI algorithms within the high-tech industry.
We Are Looking for the 1% Who Will Drive the Other 99%
Artificial intelligence in industry requires the ability to work deeply with data, broad algorithmic understanding, and the capability to apply these skills within real systems.
The program is designed for candidates with a strong quantitative academic background, including graduates with Bachelor’s, Master’s, or research based PhD degrees, who want to operate at the forefront of AI and Data. The training emphasizes professional excellence and is designed for individuals who aim to work at the technological frontier and lead complex initiatives within organizations.
During the program, participants progress through three core stages:
The program is structured in progressive stages. It begins with building a strong engineering foundation in software development, moves into data infrastructure and systems, and culminates in developing models and integrating them into complete AI solutions.
The training combines quantitative depth with hands–on work in projects that simulate real R&D environments. Participants learn not only how to develop models, but how to solve real problems and work effectively within engineering and data teams.
The mentorship team and client partnerships department actively work to secure the first role for each graduate; the placement process begins during the program itself. Upon completing the 32 week program, graduates may continue to a focused internship stage designed to prepare them for their specific matched roles.
32 weeks Sunday - Thursday 08:30-18:30
Jabotinsky 1 Ramat Gan next to Savidor Merkaz train station
A unique WIN-WIN-WIN model, where we help you secure your first job with one of our 300+ client companies
The training takes place at the Infinity Labs R&D offices, located in the heart of the Bursa District in Ramat Gan, within walking distance of Savidor Mercaz train station.
The location provides convenient access from Tel Aviv, the greater Gush Dan area, the Sharon region, and the Shfela, as well as easy access for participants arriving from the north and south of the country via train and public transportation.
The AI Researcher career track at Infinity Labs R&D is designed as a structured, in depth training program aimed at preparing graduates to lead the development of models, algorithms, and advanced machine learning solutions in the industry.
The program begins with building a strong engineering foundation in software development. It then moves on to developing a systemic understanding of data infrastructure and Big Data environments, and later progresses into machine learning and deep learning, including advanced topics such as generative models.
Throughout the program, participants develop the ability to:
An in-depth technical breakdown is available in the full syllabus.
The first stage focuses on building a strong foundation in modern software development, with Python as the primary working language. The goal is not only to learn how to write code, but to develop a solid understanding of data structures, algorithms, and software architecture.
Participants learn to think systematically and precisely while following industry standards, writing clean and maintainable code, and working effectively within R&D teams.
Key topics include:
This stage establishes the engineering foundation required for deeper work with models later in the program, enabling participants to go beyond simply using existing libraries.
The second stage focuses on the data layer: how data is collected, organized, and processed at scale.
An AI Researcher must understand data quality and the processes used to clean and structure data, since these factors directly influence model performance. For this reason, the program introduces a systemic perspective on data pipelines and the flow of information across an organization.
Key topics include:
The goal of this stage is to build an understanding of how to design and work with data environments that support real model driven research.
The third stage focuses on building models, evaluating their performance, and improving results as part of real industrial workflows.
This stage begins with statistics, exploratory data analysis, and feature engineering. From there, participants learn to develop different types of models and make informed decisions between them based on quantitative performance metrics.
The program then moves deeper into deep learning, including neural networks, CNNs for computer vision, models for NLP, and work with advanced model architectures. In addition, participants are introduced to advanced topics such as generative models and reinforcement learning as part of a broader AI toolkit.
Key topics include:
The AI Researcher career track at Infinity Labs R&D is designed as a structured, in depth training program aimed at preparing graduates to lead the development of models, algorithms, and advanced machine learning solutions in the industry.
The program begins with building a strong engineering foundation in software development. It then moves on to developing a systemic understanding of data infrastructure and Big Data environments, and later progresses into machine learning and deep learning, including advanced topics such as generative models.
Throughout the program, participants develop the ability to:
An in-depth technical breakdown is available in the full syllabus
The first stage focuses on building a strong foundation in modern software development, with Python as the primary working language. The goal is not only to learn how to write code, but to develop a solid understanding of data structures, algorithms, and software architecture.
Participants learn to think systematically and precisely while following industry standards, writing clean and maintainable code, and working effectively within R&D teams.
Key topics include:
This stage establishes the engineering foundation required for deeper work with models later in the program, enabling participants to go beyond simply using existing libraries.
The second stage focuses on the data layer: how data is collected, organized, and processed at scale.
An AI Researcher must understand data quality and the processes used to clean and structure data, since these factors directly influence model performance. For this reason, the program introduces a systemic perspective on data pipelines and the flow of information across an organization.
Key topics include:
The goal of this stage is to build an understanding of how to design and work with data environments that support real model driven research.
The third stage focuses on building models, evaluating their performance, and improving results as part of real industrial workflows.
This stage begins with statistics, exploratory data analysis, and feature engineering. From there, participants learn to develop different types of models and make informed decisions between them based on quantitative performance metrics.
The program then moves deeper into deep learning, including neural networks, CNNs for computer vision, models for NLP, and work with advanced model architectures. In addition, participants are introduced to advanced topics such as generative models and reinforcement learning as part of a broader AI toolkit.
Key topics include:
The AI Researcher career track is built around the Infinity Labs R&D Mentored Social Learning (IMSL™) methodology, which simulates the experience of working within a real R&D team.
Working in small groups of around 14, participants are guided by an experienced Tech Leader from the R&D and AI fields. The learning process focuses on tackling complex problems, conducting independent research, running systematic experiments, writing production quality code, and critically evaluating results.
The emphasis is not only on reaching a technical solution, but on the process itself – formulating problems, selecting appropriate algorithmic approaches, designing meaningful experiments, and improving models based on clear quantitative metrics.
There are no lectures, no passive learning, and no traditional exams. Success is measured by the ability to take a complex problem, break it down, explore different approaches, implement solutions, measure outcomes, and deliver a high quality result within a defined timeframe.
Learning Principles
The program takes place five days a week, Sunday to Thursday, from 08:30 to 18:30, at the Infinity Labs R&D labs in Ramat Gan.
This is a full-time, intensive training program. In most cases, the level of commitment and depth required does not allow participants to work simultaneously.
The AI Researcher career track is designed for graduates in science and engineering fields; including computer science, mathematics, physics, neuroscience, engineering, and other quantitative disciplines who want to deepen their expertise in algorithms, machine learning, and advanced AI model development.
The program is designed for individuals with strong mathematical abilities and analytical thinking who want to develop models rather than rely solely on existing tools.
AI Researchers are expected to understand how models work at a deep level, formulate problems in computational terms, design experiments, and draw precise conclusions from data. This program is for curious and critical thinkers who enjoy exploring complex problems, working with uncertainty, and improving performance over time.
Important Personal Skills
To maintain the depth and intensity of the program, the admission requirements are clearly defined:
These requirements ensure that the program maintains the level of depth, pace, and professional standards required for training AI Researchers for industry.
Graduates of the AI Researcher career track go on to work in advanced AI and Data roles across high tech companies, startups, defense organizations, and global technology firms.
Through training in model development, working with data and infrastructure, and implementing solutions in real industrial environments, graduates join R&D teams where they work on building models, analyzing data, and improving system performance as part of active products.
Based on market analysis and the roles our graduates have taken in recent years, alumni of the program can be found in positions such as:
Depending on their background and the needs of the organization, graduates may also take on additional advanced AI roles focused on model development and data driven systems.
Following a postdoctoral fellowship in Biology at the Technion, heidentified the need to create tangible engineering solutions in the field of AI. The program provided him with the practical skills required to develop complex Deep Learning and Computer Vision projects.
Today, he serves as a Computer Vision Engineer at a global medical device company, where he develops algorithms for high-precision medical image analysis.
A Master’s graduate in Mechanical Engineering specializing in Computer Vision identified a significant gap between academic mathematics and the requirements of real-world development. During the program, he translated theoretical knowledge into practical development capabilities and deep systems-level thinking.
Today, as a Computer Vision engineer and algorithm developer at a leading defense company, he develops robotics systems and real-time visual recognition solutions—a role that combines advanced technology with a life-saving mission.
A Master’s graduate in Neuroscience from a leading research institute chose to apply her advanced analytical skills to the field of artificial intelligence. Today, as an ML Engineer in a defense unit, she is responsible for designing and developing intelligent models to analyze complex data in critical environments.
The combination of her deep research-oriented thinking and the technological tools she acquired during her rigorous training enables her to lead advanced solutions in decision-support systems.
After completing a PhD in Biology and engaging in extensive research, she sought to leverage her affinity for data by transitioning into the fields of AI and Data Science. The program provided her with a comprehensive understanding of the entire lifecycle – from framing research questions to implementing complex models in real-world environments.
Today, she is a Data Scientist at a fintech company, where she develops models for prediction and anomaly detection across the financial and cyber domains. In this role, she utilizes advanced tools such as AWS SageMaker and Bedrock, skills she mastered as part of her successful transition into the industry.
Following a PhD in Life Sciences and an accomplished academic career, she sought to translate her research-driven methodology into the fields of technology and artificial intelligence. The program provided the essential professional framework and practical tools she needed to transition from the world of academia to a complex operational environment.
Today, she serves as an ML Engineer within a defense unit, where she develops machine learning-based solutions to address sophisticated cyber challenges.
A Doctor by training with a strong affinity for technology dating back to his military service chose the program to transition his skills into a professional career in Machine Learning. The training provided the rigorous engineering foundation required to pivot from the medical field to developing complex algorithms and automated cyber solutions.
Today, as an ML Engineer at a leading cybersecurity company, he focuses on designing intelligent models and building advanced defense systems powered by AI technologies.
Following a career of over a decade in immunology research, she chose to transition from the biological lab to the data lab. The program provided the essential engineering framework needed to translate her extensive research experience into the field of applied Machine Learning.
Today, she serves as an ML Engineer and Technical Lead at a premier e-commerce company. In this role, she develops sophisticated models for real-time user behavior analysis, bridging the gap between deep scientific inquiry and high-scale commercial technology.
A graduate in Computer Science with a strong affinity for the mathematical foundations of technology sought to leverage his skills in a Data Science role at the core of the industry. The program provided the essential framework needed to transition from theory to practice—bridging the gap between in-depth research and the development of intelligent, applied models.
Today, he is a Data Scientist at a leading insurance company, where he is responsible for analyzing complex data and implementing advanced AI solutions within the firm’s financial systems.
Artificial intelligence has become widely accessible through short courses, workshops, and ready made tools. People learn how to use existing models or platforms, but few know how to design, develop, and deploy AI solutions within real organizational environments.
Short courses can provide familiarity with specific algorithms or libraries, but they rarely build the broader professional foundation required for industry work. Developing real AI systems requires strong algorithmic understanding, deep work with data, and the ability to operate within multidisciplinary R&D teams.
The AI Researcher career track at Infinity Labs R&D was designed to train AI and Data professionals at an industry level. It is a structured, intensive program that combines a solid engineering foundation, data infrastructure, and advanced machine learning.
During the program, participants learn to:
The program is built for those aiming to build a long term career in AI and data - not just gain surface-level familiarity with tools.
Alongside the training, the team prepares participants for the job market and actively works to place graduates in advanced AI and Data roles at leading companies in Israel.
Founded in 2014, Infinity Labs R&D is a research and development company that prepares university graduates for careers in high tech through a training environment designed to simulate real industry R&D teams. The program is conducted in small groups of around 14 participants, guided by an experienced Tech Leader, and focuses on working on complex projects at an industry level.
Participants are carefully selected based on strong academic background and quantitative abilities. Throughout the program, they develop systemic thinking, independent problem solving capabilities, and the ability to work within AI and Data teams at leading organizations.
To date, more than 2,500 graduates have secured roles that typically require 2 to 3 years of prior experience, across over 300 high tech companies, defense organizations, and leading development centers.
The combination of deep technical training, work in a real R&D style environment, and a comprehensive placement framework is what differentiates Infinity Labs from other training programs.
Key Advantages
The AI Researcher career track at Infinity Labs R&D is an intensive 32 week training program that takes place five days a week at the company’s Ramat Gan labs.
The program is designed for university graduates in STEM fields such as computer science, mathematics, physics, engineering and neuroscience who have strong analytical and mathematical abilities and want to pursue advanced AI and Data roles in the industry.
Short AI courses typically focus on using existing tools or libraries. The AI Researcher career track focuses on developing deep algorithmic understanding, working with data at scale and building machine learning models as part of real production systems.
Academic studies in AI typically emphasize theoretical knowledge and research oriented learning. In contrast, this program is designed to provide applied, industry focused training.
The curriculum is delivered by professionals with extensive industry experience and includes hands-on work with real datasets, machine learning models, and production level systems.
By the end of the program, participants are equipped not only with conceptual understanding, but with the practical skills required to integrate into AI roles within the tech industry.
Graduates of the program go on to work in advanced AI and Data roles such as Data Scientist, Machine Learning Engineer, Computer Vision Engineer and NLP Engineer in technology companies and research organizations.
The training is free for accepted candidates as part of the Infinity Labs R&D training model.
If you are a STEM graduate with strong mathematical foundations and an ambition to work at the forefront of AI, the AI Researcher career track at Infinity Labs R&D was designed for you.
up to 50,000 NIS to help with living expenses. Payable upon start of employment or after 1 year.
"The typical recruitment process for inexperienced developers often feels like a gamble due to the lack of prior experience and recommendations, so we seek out those who can demonstrate their wisdom and motivation. Infinity Labs R&D's training program stands out as a great route, offering thorough foundational learning with an emphasis on teamwork. I appreciate the structured approach of meeting motivated individuals during our focused recruitment days, knowing they will integrate seamlessly into our company culture. With several Infinity Labs R&D alumni on our team, all proving themselves as adept developers who seamlessly blend in, it's clear the investment pays off"
"We started with a pilot to assess if Infinity Labs R&D graduates could integrate as part of the team and swiftly add value. The pilot was a great success, so we extended our collaboration. The interview screening and selection process is efficient, consistently delivering high-quality candidates with exceptional learning abilities. Over 80% of our recruits are Infinity Labs R&D graduates, with the majority evolving into long-term assets for our company. It serves as a testament to the mutual success fostered by this partnership"
"Some of our recruits were from Infinity Labs R&D, where they undergo dedicated training according to a pre-defined syllabus so that they arrive as ready as possible for our tasks, and they do arrive ready. We got the people, they were successfully absorbed into the organization pretty quickly, and mostly demonstrated independent learning abilities and entered into new domains they were not familiar with prior. Over time I have seen that the quality of the people is truly exceptional. I am very satisfied with the people on both a personal level and professional level"
“There are several reasons why I decided to recruit from Infinity Labs R&D. Knowing that the participants are undergraduates, my understanding is that the training process is very demanding and in general the method includes a lot of practice while studying independently, as well as teamwork which simulates the way I work. Another thing I like is knowing that if I require one’s completion of technological knowledge specific to my needs, Infinity Labs R&D will complete it"
"We needed to recruit a very large number of people and we certainly have a place to recruit those who are completing a degree that is not necessarily in the sciences – or very talented people who are interested in and have a passion for software. It helps us increase our recruitment capacity and get great people"
"The things I look for and that are important to me as an employer are what I have found in our employees from Infinity Labs R&D. They have the ability to learn on their own, to take a task, understand it, go look for solutions, find them and realize them"
"Infinity Labs R&D's processes work well. The workers always come ready, work well, work like everyone else and are an integral part of the production of the company product"
"I was impressed by the learning abilities of the Infinity Labs R&D graduates that we interviewed, especially their mindset – they have a deep understanding of technology and excellent problem-solving skills. We successfully recruited graduates from them for a diverse range of cybersecurity roles. After interviewing several cyber track graduates, we quickly realized we had found the right company to work with, where candidates aligned with our expectations. If you are looking for efficient, high-quality candidates, I strongly recommend recruiting from Infinity Labs R&D"
Over the past few years, we have recruited several Infinity Labs R&D graduates in the fields of DevOps and C++ programming. Every one of them has integrated seamlessly into the company, demonstrating high technical skills, high energy, a desire to learn and improve, and a drive to make an impact. The interview process is efficiently managed, enabling interviewers to select the right candidate quickly and effectively. Infinity Labs R&D has proven itself as a leader in its field, with a professional and dedicated team that pays close attention to detail. I was impressed by the high level of service, deep knowledge, and personal approach.
