SKM Group
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We are an expert software house with a 18-year history of success, a rich portfolio, projects all over the world and an appetite for more. We have built our brand reputation on professionalism and flexibility in delivering optimal software solutions. We are not afraid of unconventional ideas but are open to innovation and imaginative changes.
We are not a big company, but we turn it into an advantage. What distinguishes us from others is our natural atmosphere and open communication structure. We rely on people who want to create something new and are not afraid to try, change and improve solutions for our customers. If you value a good atmosphere and the spirit of cooperation, you will fit in here.
As a Senior Generative AI Engineer, you will lead the design and deployment of advanced AI solutions in cloud environments like AWS, Azure, and GCP. Your responsibilities include building robust data pipelines, optimizing performance, and deploying large language models (LLMs) for various business needs. Emphasizing AI ethics, you'll ensure responsible practices are integrated throughout development. Additionally, you'll collaborate with stakeholders to translate business needs into technical requirements and communicate complex AI concepts clearly.
Data Engineering and Pipeline Development:
Design, build, and maintain robust data pipelines to support AI/ML models.
Design and implement AI architectures in cloud environments such as AWS, Azure, or GCP.
Collaborate with cloud engineers to ensure seamless integration and deployment of AI models.
Utilize cloud-native tools and services to enhance AI capabilities.
Deployment of Large Language Models (LLMs):
Deploy and fine-tune LLMs for various business applications.
Ensure that LLM deployments are scalable, efficient, and secure.
Monitor and optimize model performance in production environments.
Integrate ethical considerations and bias mitigation strategies into AI development processes.
Promote and ensure responsible AI practices across all projects.
Stay updated on AI ethics guidelines and industry best practices.
Stakeholder Communication and Requirement Gathering:
Collaborate with stakeholders to understand business needs and translate them into technical requirements.
Communicate complex technical concepts to non-technical stakeholders effectively.
Provide regular updates and insights on AI project progress and outcomes.
Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
Advanced Python knowledge for data processing and scripting.
Hands-on experience with one or more cloud computing platforms (Azure, AWS, GCP).
Proficiency in RDBMS/NoSQL data stores and appropriate use cases.
Experience with Data as Code; version control, small and regular commits, unit tests, CI/CD, packaging, familiarity with containerization tools such as Docker and Kubernetes.
Expertise in designing and implementing AI architectures in cloud environments (AWS, Azure, GCP).
In-depth knowledge of AI ethics, bias mitigation, and responsible AI practices.
Experience with Infrastructure as Code is a plus.
Excellent problem-solving skills and ability to work independently in a fast-paced environment
Strong communication skills and ability to collaborate effectively with team members and external partners, fluent English
No unhealthy competition, team approach to meeting challenges
Company apartments in cool cities across Europe: work and enjoy a memorable getaway
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