AI ENGINEER

Responsibilities and Duties • Collaborate with cross-functional teams to identify business needs and potential areas where AI solutions can add value.
• Design and develop proof-of-concepts (PoCs) using machine learning and deep learning techniques to demonstrate the feasibility and potential impact of AI-driven solutions.
• Evaluate and validate the performance of PoCs, considering factors such as accuracy, scalability, and computational efficiency.
• Work closely with stakeholders to understand their feedback and requirements, iterating on PoCs to enhance their value and address specific business challenges.
• Analyze the outcomes of PoCs and identify the most promising concepts with significant business value.
• Translate successful PoCs into minimum viable products (MVPs), working collaboratively with software engineers and data scientists to productize and scale the solutions.
• Optimize and fine-tune AI models and algorithms to meet performance requirements and align with business objectives.
• Conduct thorough testing and validation of MVPs, ensuring their reliability, stability, and usability in real-world scenarios.
• Collaborate with product teams to integrate AI capabilities into existing systems or develop new AIdriven applications.
• Stay informed about industry trends, advancements, and best practices in AI engineering and leverage this knowledge to drive innovation in PoC and MVP development.
• Document the development process, methodologies, and results, providing clear and concise reports and presentations to stakeholders.
• Provide technical guidance and support to junior AI engineers, fostering knowledge sharing and continuous learning within the team.
What we need • Bachelor's or master's degree in computer science, data science, artificial intelligence, or a related field.
• Proven experience working as an AI Engineer, machine learning engineer, or similar role.
• Solid understanding of LLMs, machine learning and deep learning techniques, algorithms, and frameworks (e.
., TensorFlow, PyTorch, Keras, LangChain).
• Proficiency in programming languages such as Python and Java, and experience with relevant libraries and tools for data manipulation, analysis, and visualization (e.
., NumPy, pandas, Matplotlib).
• Experience with big data processing and distributed computing frameworks (e.
., Hadoop, Spark) is a plus.
• Familiarity with cloud platforms (e.
., AWS, Azure, Google Cloud) and their AI services.
• Strong problem-solving skills and ability to translate business requirements into technical solutions.
• Excellent communication and teamwork abilities, with the capacity to collaborate effectively with crossfunctional teams.
• Strong attention to detail.
• A self-driven and proactive attitude, with a passion for learning and staying updated on emerging technologies and industry trends.
• Provide technical guidance and support to junior AI engineers, fostering knowledge sharing and continuous learning within the team.