ML/AI Engineer
The ML/AI Engineer will design and implement end‑to‑end machine learning systems, including LLMOps pipelines, deep‑learning models, and statistical predictive algorithms for client projects. They will also transform unstructured data such as images and speech into actionable insights and communicate results to business stakeholders.
Skills required
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.
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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
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