AI/ML specialist

The team is composed by experienced professionals covering a wide range of competences including experts in the domains of Project Management, Business intelligence, AI and Data Science, Big Data, Cloud Data Architectures.

The position will consequently require a high level of interaction , experience and technical expertise.

The tasks performed by external service provider will cover the whole development cycle of AI and data architectures and solutions from end-to-end, including:

Design and Development:

Architect, design, and implement advanced machine learning models, including but not limited to deep learning, reinforcement learning, and large language models (LLMs).

Develop scalable AI solutions using state-of-the-art techniques and frameworks.

Collaborate with data scientists to refine data preprocessing, feature engineering, and model training pipelines.

Deployment and Integration:

Deploy machine learning models and AI solutions into production environments, ensuring scalability, performance, and reliability.

Integrate AI models with existing systems and workflows, providing seamless functionality across platforms.

Optimize models for performance, including latency, throughput, and accuracy, considering both cloud and edge deployment scenarios.

Research and Innovation

Stay up-to-date with the latest advancements in AI, ML, and LLM technologies, and apply them to enhance our AI capabilities.

Experiment with new algorithms, architectures, and techniques to push the boundaries of AI within the organization.

Contribute to research publications, patents, and open-source projects as appropriate.

Collaboration and Communication:

Work closely with cross-functional teams to understand business requirements and translate them into technical solutions.

Communicate complex AI concepts and technical details to non-technical stakeholders effectively.

Mentor junior engineers and provide guidance on best practices in AI and ML development.

Testing and Evaluation:

Conduct rigorous testing and validation of AI models, including A/B testing, cross-validation, and error analysis.

Monitor model performance in production and iterate on models to improve accuracy and robustness.

Implement monitoring systems to detect model drift and ensure continued performance

over time.

Requirements

Experience:

• Proven experience in designing, implementing, and deploying advanced machine learning models and AI systems.
• Strong experience with large language models (LLMs) and natural language processing (NLP) techniques.
• Experience with cloud platforms (AWS, Azure).

Technical Skills:

Deep understanding of machine learning frameworks and libraries.

Experience with data processing and ETL tools.

Familiarity with MLOps practices and tools.

Soft Skills:

Strong problem-solving skills and the ability to think critically and creatively.

Excellent communication skills, both written and verbal.

Ability to work collaboratively in a team environment and independently with minimal supervision.