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Solution Architect

1 month ago

Singapore ARISTON SERVICES PTE. LTD. Full time
Roles & Responsibilities

As an AI/ML Solution Architect, you will be responsible for designing and overseeing the architecture of AI and machine learning solutions.

You will work closely with data scientists, engineers, and business stakeholders to ensure that our AI/ML initiatives are scalable, robust, and aligned with business objectives.

Your expertise in machine learning, deep learning, natural language processing (NLP), and generative AI will be crucial in guiding the development and deployment of advanced AI solutions.

Responsibilities:

• Design and architect end-to-end AI/ML solutions that meet business requirements and technical specifications.


• Develop and implement scalable machine learning and deep learning models, ensuring they integrate seamlessly into existing systems.


• Create architectures for NLP applications, including text processing, sentiment analysis, named entity recognition, and language modelling.


• Leverage generative AI and large language models (LLMs) to develop innovative applications.


• Collaborate with data engineers to design data pipelines and ensure data quality and accessibility.


• Provide technical leadership and guidance to data scientists and engineers throughout the development lifecycle.


• Evaluate and select appropriate AI/ML tools, frameworks, and technologies to meet project needs.


• Ensure best practices in AI/ML model development, including versioning, testing, and validation.


• Stay updated with the latest advancements in AI/ML technologies and incorporate them into architectural designs.


• Communicate complex AI/ML concepts and solutions effectively to non-technical stakeholders.

Requirements:


• Proven experience (8+ years) in designing and implementing AI/ML solutions, with a strong focus on machine learning, deep learning, NLP, and generative AI.

  1. Above can include 2-3 Years of Generative AI hands on experience as a Solution Architect – this needs to be global/regional or equivalent level
  2. Should have a developer background with prior exposure of being a Data Scientist
  3. GCP expertise is a must


• Extensive experience with machine learning algorithms, model development, and deployment.


• Proficiency in deep learning frameworks such as TensorFlow, PyTorch, and Keras.


• Strong expertise in NLP techniques and tools, including experience with LLMs like Gemini, GPT, BERT, etc.


• Experience with cloud platforms (AWS, GCP, Azure) and their AI/ML services.


• Knowledge of big data technologies and tools such as Hadoop, Spark, and Kafka.


• Proficiency in programming languages such as Python, R, and Java.


• Excellent problem-solving skills and the ability to design robust, scalable AI/ML architectures.


• Strong communication skills, with the ability to present technical concepts to both technical and non-technical audiences.( CXO level, Business Head audiences )


• Experience in leading and mentoring technical teams with a hands on approach with strategic planning

Preferred Qualifications:


• Experience with MLOps practices and tools for continuous integration and deployment of machine learning models.


• Familiarity with data visualization tools such as Looker, Tableau, Power BI, or similar.

Tell employers what skills you have

Mentoring
Machine Learning
Azure
Big Data
Natural Language Processing
Architect
Architectural
Hadoop
Sentiment Analysis
Keras
PyTorch
Python
GCP
Java
Technical Leadership
Business Requirements