Deep Learning Engineer

About Solutyics

Solutyics is an innovative, technology-driven company committed to harnessing the power of Data and Artificial Intelligence to create transformative business opportunities. The team excels in AI, Machine Learning, Data Engineering, and Advanced Data Analytics, providing customized solutions to address complex client challenges and foster sustainable success. The company prioritizes transparency, integrity, and mutual dedication to growth, cultivating a collaborative atmosphere that encourages innovative breakthroughs.

Job Role and Responsibilities

We are seeking a full-time Deep Learning Engineer to join our on-site team in Abu Dhabi Emirate, United Arab Emirates. The successful candidate will be responsible for designing, developing, and fine-tuning deep learning systems for practical applications. Collaborating closely with data scientists, engineers, and product stakeholders, daily tasks will include data collection and preparation, choosing suitable neural network architectures, model development and training, as well as performance assessment using relevant evaluation metrics. Additional duties involve deploying models into live production settings, ongoing monitoring, and iterative refinement based on feedback and incoming data. The role also encompasses creating detailed technical documentation, keeping abreast of latest deep learning advancements, and actively participating in cross-team problem solving.

Required Qualifications and Skills

• Solid expertise in Machine Learning and Deep Learning, with hands-on experience in neural network models such as CNNs, RNNs, and Transformer architectures.
• Proficient in AI programming languages and frameworks, including Python, TensorFlow, PyTorch, and associated libraries.
• Experience in Data Engineering and Advanced Analytics, covering data cleaning, feature extraction, and handling both structured and unstructured datasets.
• Knowledge of deploying and optimizing models through APIs and familiarity with MLOps best practices for production tuning.
• Strong grounding in algorithms, statistics, and linear algebra pertinent to AI and ML applications.
• Ability to work collaboratively across diverse teams, clearly explaining complex technical concepts and contributing to client-oriented solutions.
• Educational background with a Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related discipline, or equivalent practical experience.
• Experience in AI consulting or client engagement to translate requirements into technical designs is a valuable addition.
• Awareness of cloud infrastructures such as AWS, Azure, or Google Cloud Platform, plus container technology like Docker and Kubernetes, is a plus.