AI / Machine Learning Engineer Jobs in Attica | Information Technology / IT
20+ open positions from 5 companies
Search JobsAbout AI / Machine Learning Engineer Jobs
An AI / Machine Learning Engineer develops and implements intelligent algorithms and models to enable machines to learn and make decisions autonomously. They work with data scientists and software teams to design scalable AI solutions, automate processes, and improve business insights. This role is in high demand across industries like technology, finance, and manufacturing, offering significant career growth in AI innovation.
Find your next employer
Discover active opportunities with leading companies
Required Skills
Essential skills needed for AI / Machine Learning Engineer positions
Proficiency in Python programming language for software development, automation, and data analysis.
Expertise in understanding and utilizing large-scale neural network models designed to process and generate human language.
Proficiency in Java programming language for developing cross-platform applications and backend systems.
Ability to develop algorithms and statistical models that enable computers to learn from and make predictions based on data.
The skill of designing and refining input prompts to optimize the output of AI language models.
Understanding of neural network architectures and algorithms for training AI models on large datasets.
Experience with major cloud service platforms such as Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP) for deploying and managing applications.
Proficiency in Structured Query Language for managing and querying relational databases.
Expertise in designing and implementing AI models that generate new content based on training data.
Practices and tools for deploying, monitoring, and managing machine learning models in production environments.
Additional Skills & Traits
Nice-to-have skills and soft skills that can help you stand out
Knowledge of non-relational database systems designed for distributed data storage and scalability.
An open-source platform for managing the end-to-end machine learning lifecycle, including experimentation, reproducibility, deployment, and a central model registry.
Knowledge and use of Microsoft's Azure AI Foundry platform for building and deploying AI applications.
Expertise in using Graphics Processing Unit systems for accelerating training processes in computing tasks.
Providing guidance and support to individuals to help their professional or personal development.
The ability to identify and pursue opportunities to grow and close business deals.
Skills related to selling products or services and developing business opportunities to increase revenue.
Certification demonstrating foundational knowledge in Microsoft technologies as part of the Microsoft Certified Professional program.
Ensuring adherence to laws, regulations, and company policies.
Expertise in packaging applications into containers and managing their deployment and scaling with orchestration tools.
Ability to collaborate effectively with others to achieve common goals.
Ability to convey information clearly and effectively in verbal and written form.
Ability to adjust effectively to new conditions and changes in the work environment.
Ability to identify issues and develop effective solutions efficiently.
Commitment to constantly acquiring new knowledge and skills to improve oneself.
Desire to learn and explore new ideas, concepts, and experiences.
Ability to drive oneself to take initiative and persistently pursue goals without external prompting.
Ability to guide and motivate a group towards achieving goals effectively.
Ability to analyze facts and form a judgment through thoughtful evaluation.
Ability to generate innovative ideas and think outside the box.
AI / Machine Learning Engineer Jobs - Attica
Latest opportunities from top employers
Educational Background
Recommended education and qualifications for AI / Machine Learning Engineer positions
Study of computational systems, programming, algorithms, and software development.
Study of applying scientific principles to design, build, and maintain structures and machines.
Study of methods to analyze, interpret, and extract knowledge from data using statistical and computational techniques.
Study of numbers, quantities, shapes, and their relationships through abstract reasoning and logical deduction.
Study of data collection, analysis, interpretation, and presentation to make informed decisions.
No specific academic field required; open to all educational backgrounds.
Study of algorithms and systems that enable machines to perform tasks requiring human intelligence.
Studies in disciplines related to the specified area of expertise.
Study encompassing various scientific disciplines related to the primary field of interest.
Study of matter, energy, and the fundamental forces of nature.