G-P
Design and deploy AI solutions using advanced techniques in machine learning and natural language processing. Collaborate with teams to address complex business challenges and enhance user satisfaction through robust engineering practices.
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Senior AI Engineer at Awin: Design and deploy conversational AI models using LLMs, collaborate with cross-functional teams, and contribute to a diverse and inclusive company culture.
Awin Global
Senior AI Engineer at Awin: Design and deploy conversational AI models using LLMs, collaborate with cross-functional teams, and contribute to a diverse and inclusive company culture.
Awin Global
Senior AI Engineer at Awin: Design and deploy conversational AI models using LLMs, collaborate with cross-functional teams, and contribute to a diverse and inclusive company culture.
Awin Global
Senior AI Engineer at Awin: Design and deploy conversational AI models using LLMs, collaborate with cross-functional teams, and contribute to a diverse and inclusive company culture.
Awin Global
Senior AI Engineer at Awin: Design and deploy conversational AI models using LLMs, collaborate with cross-functional teams, and contribute to a diverse and inclusive company culture.
Awin Global
Senior AI Engineer at Awin: Design and deploy conversational AI models using LLMs, collaborate with cross-functional teams, and contribute to the company's mission to build a leading open partner ecosystem.
Awin Global
Senior AI Engineer at Awin: Design and deploy conversational AI models using LLMs, collaborate with cross-functional teams, and work remotely.
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Horizons
Data and AI Engineer at Horizons: Design and develop AI solutions, lead integration efforts, and promote technology adoption in a corporate setting.
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Keboola
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G-P
As a Senior AI Engineer, you will design, develop, and deploy AI solutions to address complex business challenges. This role requires advanced expertise in artificial intelligence, including machine learning and natural language processing, with the ability to implement these technologies in production-grade systems. Key responsibilities include developing innovative, scalable AI solutions for real business problems; managing complex datasets, designing efficient data pipelines, training robust models; owning end-to-end projects from analysis to deployment; researching new techniques in NLP and ML; collaborating with product managers and stakeholders; writing technical documentation; staying updated on the latest developments; exploring new technologies; developing high-quality machine learning services; and prioritizing robust engineering practices. Required skills include a Master's degree, deep understanding of ML and NLP, statistical modeling, data curation, model training, experience with Python, Docker, AWS, and strong communication skills.
As a Senior AI Engineer, you will design, develop, and deploy AI solutions that address complex business challenges. This role requires advanced expertise in artificial intelligence, including machine learning and natural language processing, and the ability to implement these technologies in production-grade systems.
Key Responsibilities:
Develop innovative, scalable AI solutions for real business problems. Drive the full lifecycle of projects from conception to deployment, ensuring alignment with business objectives.
Manage complex data sets, design efficient data processing pipelines, and train robust models. Expect to spend approximately 70% of your time on data and ML engineering tasks related to developing AI systems.
Own highly open-ended projects end-to-end, from the analysis of business requirements to the deployment of solutions. Dedicate about 30% of your time to researching new techniques in NLP and ML that could benefit the business.
Work closely with other AI engineers, product managers, and stakeholders to ensure that AI solutions meet business needs and enhance user satisfaction.
Write clear, concise, and comprehensive technical documentation for all projects and systems developed.
Stay updated on the latest developments in the field. Explore and prototype new technologies and approaches to address specific challenges faced by the business.
Develop and maintain high-quality machine learning services. Prioritize robust engineering practices and user-centric development.
Required Skills and Qualifications:
Master’s degree in Computer Science, Machine Learning, Statistics, Engineering, Mathematics, or a related field
Deep understanding and practical experience in machine learning and natural language processing, especially with deep learning architectures
Strong foundational knowledge in statistical modeling, probability, and linear algebra
Extensive practical experience with curating datasets, training models, analyzing post-deployment data, and developing robust metrics to ensure model reliability
Experience developing and maintaining machine learning services for real-world applications at scale
Strong Python programming skills and ability to write maintainable, production-ready code
Proficiency with Container Orchestration services such as Docker
Proficiency with AWS, including Serverless
Proven track record in driving AI projects with strong technical leadership.
Excellent communication skills when engaging with both technical and non-technical stakeholders
Proactive attitude with a continuous improvement mindset, seeking help and providing feedback when necessary
Preferred Qualifications:
Experience with LLMs for non conversational use cases
Experience with natural language processing for legal applications
Proficiency with Terraform
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