Ai/ml Architect
1 week ago
Not just a job, but a career Yokogawa, award winner for ‘Best Asset Monitoring Technology’ and ‘Best Digital Twin Technology’ at the HP Awards, is a leading provider of industrial automation, test and measurement, information systems and industrial services in several industries. Our aim is to shape a better future for our planet through supporting the energy transition, (bio)technology, artificial intelligence, industrial cybersecurity, etc. We are committed to the United Nations sustainable development goals by utilizing our ability to measure and connect. About the Team Our 18,000 employees work in over 60 countries with one corporate mission, to "co-innovate tomorrow". We are looking for dynamic colleagues who share our passion for technology and care for our planet. In return, we offer you great career opportunities to grow yourself in a truly global culture where respect, value creation, collaboration, integrity, and gratitude are highly valued and exhibited in everything we do. AI/ML Architect will be responsible for designing and implementing AI/ML solutions that address complex business challenges. You will collaborate closely with cross-functional teams to define and execute AI/ML strategies, develop robust algorithms, and ensure the successful deployment of AI/ML models into production environments. This role requires a deep understanding of AI/ML technologies, strong problem-solving skills, and the ability to lead and mentor a team of data scientists and engineers. **Job Description**: - Collaborate with stakeholders to identify business problems that can be solved using AI/ML techniques. - Stay current with the latest advancements in AI/ML and recommend innovative approaches to solving problems. - Lead the development and implementation of AI/ML solutions, from concept to production deployment. - Design and architect scalable and efficient AI/ML systems and pipelines. - Provide technical leadership and mentorship to data scientists and engineers. - Evaluate and select appropriate AI/ML frameworks, tools, and technologies. - Ensure the ethical and responsible use of AI/ML by implementing fair and transparent algorithms. **Requirements**: - Minimum 5 years' experience in AI architecture and pipeline planning. Understand the workflow and pipeline architectures of ML and deep learning workloads. An in-depth knowledge of components and architectural trade-offs involved across the data management, governance, model building, deployment, and production workflows of AI is a must. - Minimum 5 years' experience in Software engineering and DevOps principles, including knowledge of DevOps, ML Ops workflows, and tools, such as Git, containers, Kubernetes, Kube-flow, and CI/CD. - Minimum 5 years' experience in Data science and advanced analytics, including knowledge of advanced analytics tools (such as SAS, R, and Python) along with applied mathematics, ML, and Deep Learning frameworks (such as TensorFlow, Scikit-learn, Keras) and ML techniques (such as AutoML, random forest and neural networks). - Experience in Software development for Industrial Automation and knowledge of IA protocols (OPC, OPC UA) and systems (DCS, SCADA) will be an added advantage. - Minimum 10 years' experience in Software Development using Java,.NET C#, C++ Yokogawa is an Equal Opportunity Employer. Yokogawa wants a diverse, equitable and inclusive culture. We will actively recruit, develop, and promote people from a variety of backgrounds who differ in terms of experience, knowledge, thinking styles, perspective, cultural background, and socioeconomic status. We will not discriminate based on race, skin color, age, sex, gender identity and expression, sexual orientation, religion, belief, political opinion, nationality, ethnicity, place of origin, disability, family relations or any other circumstances. Yokogawa values differences and enables everyone to belong, contribute, succeed, and demonstrate their full potential. Are you being referred to one of our roles? If so, ask your connection at Yokogawa about our Employee Referral process
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