Engineer - Artificial Intelligence

at  G42

THE OPPORTUNITY

Looking for an astute, proficient, and qualified Engineer - Artificial Intelligence to assess, analyze and work with data concepts, AI use-cases & complex new data sources to provide business insights to customers and support the implementation & integration of the data sources into the Presight platform. To play a critical role in the development of high-performance AI solutions at Presight.
Responsibilities:

TO QUALIFY, YOU MUST HAVE

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• 3+ years of professional experience in AI engineering, machine learning, or data science roles, with a proven track record of developing and deploying AI solutions in production environments.
• Proficiency in programming languages such as Python, R, or Java, and experience with AI/ML libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong understanding of machine learning algorithms, deep learning architectures, and statistical modeling techniques, with hands-on experience in building and training AI models for real-world applications.
• Experience with data preprocessing, feature engineering, and exploratory data analysis (EDA), utilizing tools and techniques for data manipulation, visualization, and statistical analysis.
• Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and AI/ML services for model training, deployment, and orchestration in distributed environments.
• Knowledge of software engineering principles, agile development methodologies, and version control systems (e.g., Git), with experience in building scalable and maintainable software systems.
• Excellent problem-solving skills, analytical thinking, and attention to detail, with the ability to translate business requirements into technical solutions and deliver results in a fast-paced, collaborative environment.
• Strong communication and interpersonal skills, with the ability to work effectively in cross-functional teams and convey technical concepts to both technical and non-technical stakeholders.
• Good corporate capacity, and good communication skills.
• Knowledge of machine learning and big data analytics and mining techniques in one or more areas of statistical modeling, text mining, and information retrieval.
• An innovative and creative approach to problem-solving.
• Strong AI, analytical, and data visualization skills.
• Excellent communication and presentation skills

Functional

• Design, develop, and deploy AI models and algorithms to address business challenges and enhance operational efficiency across various domains, including natural language processing (NLP), computer vision, recommendation systems, and predictive analytics.
• Collect, preprocess, and analyze data from diverse sources to derive meaningful insights and features for training AI models, employing techniques such as data cleaning, transformation, and feature extraction.
• Train, validate, and fine-tune machine learning and deep learning models using cutting-edge algorithms and frameworks, ensuring optimal performance, accuracy, and generalization on diverse datasets.
• Deploy trained AI models into production environments, integrating them into existing systems and applications to facilitate real-time inference and decision-making, while ensuring scalability, reliability, and security.
• Monitor the performance and behavior of deployed AI systems, diagnosing issues, optimizing model performance, and implementing enhancements to improve efficiency, scalability, and user experience.
• Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders, to gather requirements, prioritize tasks, and deliver AI solutions aligned with business objectives, effectively communicating technical concepts and solutions to non-technical audiences.
• Stay abreast of the latest advancements in AI technologies, tools, and methodologies, conducting research and experimentation to explore new approaches, algorithms, and applications that drive innovation and competitive advantage.
• Support the wider business with their data needs on an ad hoc basis.
• Comply with QHSE (Quality Health Safety and Environment), Business Continuity, Information Security, Privacy, Risk, Compliance Management and Governance of Organizations policies, procedures, plans and related risk assessments.

Qualifications: