AI / Machine Learning Engineer Jobs in Attica | Information Technology / IT
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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.
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Required Skills
Essential skills needed for AI / Machine Learning Engineer positions
Proficiency in Python programming language for software development, automation, and data analysis.
The skill of designing and refining input prompts to optimize the output of AI language models.
Expertise in understanding and utilizing large-scale neural network models designed to process and generate human language.
Proficiency in Structured Query Language for managing and querying relational databases.
Ability to develop algorithms and statistical models that enable computers to learn from and make predictions based on data.
A technique combining information retrieval and natural language generation to improve response relevance and accuracy.
Expertise in designing and implementing AI models that generate new content based on training data.
Proficiency in Java programming language for developing cross-platform applications and backend systems.
Experience with PyTorch, an open-source machine learning library for deep learning applications.
Proficiency in using TensorFlow, an open-source machine learning framework for building and deploying ML models.
Additional Skills & Traits
Nice-to-have skills and soft skills that can help you stand out
Practices and tools for deploying, monitoring, and managing machine learning models in production environments.
Experience with Docker containerization technology for developing, shipping, and running applications.
Knowledge and use of Microsoft's Azure AI Foundry platform for building and deploying AI applications.
Knowledge and management of the processes involved in the supply chain and logistics operations.
An open-source platform for automating deployment, scaling, and management of containerized applications.
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.
The field of computer science that enables computers to interpret and process visual data from the real world.
Expertise in using Graphics Processing Unit systems for accelerating training processes in computing tasks.
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 collaborate effectively with others to achieve common goals.
Ability to identify issues and develop effective solutions efficiently.
Ability to guide and motivate a group towards achieving goals effectively.
Desire to learn and explore new ideas, concepts, and experiences.
Ability to analyze facts and form a judgment through thoughtful evaluation.
Ability to drive oneself to take initiative and persistently pursue goals without external prompting.
Ability to interact positively and effectively with others in a friendly and approachable manner.
Commitment to constantly acquiring new knowledge and skills to improve oneself.
AI / Machine Learning Engineer Jobs - Attica
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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.
No specific academic field required; open to all educational backgrounds.
Study of numbers, quantities, shapes, and their relationships through abstract reasoning and logical deduction.
Study of algorithms and systems that enable machines to perform tasks requiring human intelligence.
Study of data collection, analysis, interpretation, and presentation to make informed decisions.
Study of electrical systems, electronics, computer hardware, and integrated technologies.
Studies in disciplines related to the specified area of expertise.
Study of designing, developing, testing, and maintaining software systems.