ML/AI Engineer

On-siteSeniorML Engineerposted 3w ago

✦Role summaryAI-generated

Accenture seeks an ML/AI Engineer to design and deploy machine learning systems, including LLMOps and deep learning models, for clients in Kuala Lumpur. The role involves transforming unstructured data, building predictive algorithms, and presenting insights to business stakeholders.

Skills required

LLMOps Deep learning Statistical modeling Software engineering Data analysis Image auto-tagging Text-to-speech Predictive modeling Ml algorithms Machine learning AI Data science Statistics Azure Data analytics Data warehousing MLOps Natural language processing Neural networks

About this role

Summary

We are looking for an experienced ML/AI Engineer with hands-on experience in LLMOps, deep learning, statistical modeling, and software development. As part of Data& AI team, you will develop analytics solutions based on machine learning & statistical predictive algorithms for our clients. Together we do what matters

Key responsibilities

Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models.
Prepare advanced data analyses and support in the presentation of results to business stakeholders
Work with team members and leads to define Data Science use cases using current and emerging technologies
Transforming data science prototypes and applying appropriate ML algorithms and tools
Turning unstructured data into useful information by auto-tagging images and text-to-speech conversions.
Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.
Developing ML algorithms to analyze huge volumes of historical data to make predictions.
Running tests, performing statistical analysis, and interpreting test results.

Additionally, you’ll also be comfortable in working on application development projects for our client who is a reputable business operating within the Alcohol, Tobacco, and Sanitary industry sector.

Skills and experiences

Min 5+ years hands-on experience implementing and deploying ML solutions in Azure
Experience in data analytics, BI, data warehousing, a data platform development or other relevant hands-on technical experience.
Experience in MLOps frameworks and tools, Ml Model deployment and maintenance
Understanding of structured and unstructured data analysis, streaming data, IoT, artificial intelligence, NLP and related topical analytics fields.
Knowledge of neural networks and transformers