Key Responsibilities
- Design, develop, and deploy advanced AI solutions with a focus on LLMs, LMMs, Foundation Models, and Machine Learning applications across multiple industries.
- Provide technical leadership in AI architecture, model optimization, and production deployment, ensuring scalable and reliable AI performance.
- Lead the transition of AI models from research environments into enterprise grade production systems.
- Collaborate closely with Product, Infrastructure, Security, and Engineering teams to integrate AI solutions into enterprise GPU and Cloud platforms.
- Research and apply emerging AI technologies to practical business use cases, including Natural Language Processing, Computer Vision, Recommendation Systems, and Generative AI.
- Design and optimize large scale training and inference pipelines using distributed GPU infrastructure, HPC, and Cloud environments.
- Drive AI innovation initiatives and contribute to strategic technology direction within the organization.
- Mentor and develop AI engineering teams while supporting technical assessments, innovation programs, and industry recognition initiatives.
Requirements
Experience
- Minimum 8 years of hands on experience in Artificial Intelligence, Machine Learning, and Deep Learning system development.
- At least 3–5 years in senior, principal, or lead engineering roles within technology companies or large enterprises.
- Proven experience in training, fine tuning, post training optimization, deployment, and integration of LLMs and Foundation Models into real world products.
- Strong expertise in building scalable AI pipelines for training and inference using multi GPU and distributed computing environments.
- Experience leading AI driven digital transformation initiatives and mentoring engineering teams.
- Deep understanding of enterprise AI governance, including data standardization, security, testing, quality assurance, and AI product lifecycle management.
Education
- Bachelor’s, Master’s, or PhD degree in Artificial Intelligence, Machine Learning, Computer Science, Computer Engineering, Data Science, Information Technology, or related disciplines.
- International certifications in AI/ML, Cloud, GPU computing, or distributed systems are considered a strong advantage.
- Candidates with published AI research papers or participation in international AI research collaborations are highly preferred.
Preferred Qualifications
- Proven track record leading enterprise AI projects that delivered measurable operational improvements, cost optimization, or business impact.
- Recognition through AI related awards, technical achievements, patents, publications, or industry contributions.
- Experience contributing to open source AI tools, frameworks, or developer communities.
- Author of research papers published in reputable journals or conferences such as IEEE, ACM, or equivalent.
- Strong experience optimizing GPU based AI pipelines to significantly improve model training or inference performance.
- Advanced AI Cloud certifications such as AWS SageMaker, GCP Professional ML Engineer, or equivalent.
- Demonstrated success in reducing inference costs or latency through AI optimization strategies.
- Experience launching AI products from concept to General Availability (GA) within fast paced development timelines.
HOW TO APPLY: Please send your CV to the consultant in charge:
E-mail: my.do@ev-search.com
All applications will be considered without regard to race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, parental status, military service, or any other non-merit factor.
