AI Systems Developer
Há 4 dias
KI performance is at the forefront of the AI revolution, driving digital transformation and unlocking new opportunities for businesses. As an AI Engineer, you will be part of a dynamic team that develops and implements cutting-edge AI solutions that shape the future of industry.
About Your Role
You will be responsible for designing and developing innovative AI solutions that meet the evolving needs of our clients.
With a focus on scalability, reliability, and maintainability, you will work closely with cross-functional teams to ensure that AI-driven insights translate into tangible business value.
Your key responsibilities will include:
- Developing and deploying end-to-end AI solutions, from data ingestion to deployment and operations.
- Applying machine learning and advanced analytics techniques to solve complex business challenges.
- Building, integrating, and optimizing Large Language Models (LLMs), including Text-to-Speech (TTS) and Speech-to-Text (STT).
- Ensuring data quality by handling ingestion, preparation, and transformation for AI use cases.
- Implementing scalable and production-ready AI solutions using cloud-based MLOps best practices.
- Staying up-to-date with the latest advancements in AI and cloud technologies and evaluating their potential for integration.
- Collaborating with cross-functional teams to customize AI tools and embed them into business processes for maximized value.
- Ensuring compliance with data privacy, security, and ethical AI guidelines in all solutions.
We seek a talented AI Engineer with a strong background in AI, machine learning, and data science, as well as excellent communication and collaboration skills.
The ideal candidate will possess:
- 3+ years of experience in AI engineering, data science, or machine learning, preferably with data engineering expertise.
- End-to-end AI expertise – expertise in data preparation, feature engineering, model training, deployment, and continuous optimization.
- Strong Python skills – proficiency in ML frameworks and cloud-based AI platforms like Azure ML and Databricks.
- Cloud & AI ecosystem knowledge – familiarity with Microsoft Azure Data & AI services and leading AI platforms/APIs such as OpenAI, Gemini, and Anthropic.
- MLOps & production deployment – hands-on experience with MLOps tooling (Azure DevOps, GitHub, GitLab) and deploying AI solutions in production.
- AI infrastructure expertise – skilled in designing and deploying AI infrastructure, including containerization with Docker.
- Broad AI/ML understanding – strong foundation in NLP, computer vision, and conversational AI (e.g., Azure Bot Services, Microsoft Copilot).
- Experience with AI models – familiarity with LLMs, TTS, and STT technologies.
- Awareness of AI regulations – understanding of data privacy regulations (e.g., GDPR) and their implications for AI projects.
- Customer interaction & leadership – comfortable engaging with stakeholders and leading workshops.
- Innovative & team-oriented mindset – passion for AI, proactive attitude, and collaborative work style.
- Excellent communication skills – fluent in English (C2).
- Education: Bachelor's or master's degree in computer science, artificial intelligence, or a related field.
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