Job DescriptionResponsibilityApplies existing machine learning techniques to new problems and datasets.Evaluates the outcomes and performance of machine learning systems.Identifies issues and recommends improvements to machine learning systems and the data they use.Designs, codes, verifies, tests, documents, amends and refactors moderately complex programs/scripts.Applies agreed standards and tools to achieve a well-engineered result.Monitors and reports on progress.Identifies issues related to ML development activities.Proposes practical ML solutions to resolve issues.Collaborates in reviews of work with others as appropriate.Elicits requirements for systems and software / ML life cycle working practices and automation.Selects systems and software / ML life cycle working practices for components and micro-services.Deploys automation to achieve well-engineered and secure outcomes. Systems integration and build.Defines the ML modules needed for an integration build and produces a build definition for each generation of the solution.Accepts completed ML modules, ensuring that they meet defined criteria.Applies existing data science techniques to new problems and datasets using specialised programming techniques.Evaluates the outcomes and performance of data science models.Identifies and implements opportunities to train and improve models and the data they use.Applies data engineering standards and tools to create and maintain data pipelines and extract, transform and load data.Supports monitoring of the external environment and assessment of emerging technologies.Contributes to the creation of reports, technology road mapping and the sharing of knowledge and insights.RequirementsStrong understanding of machine learning concepts, statistical analysis techniques and ability to effectively explain them to both technical and non-technical colleagues.Hands-on experience in programming, machine learning and software engineering.Application of state-of-the-art data science and analytical tools and relevant programming languages (Python with its Data Science frameworks, e.g., PyTorch, TensorFlow, Hugging Face, Langchain, Autogen, Pandas/Polars, PySpark, Scikit-learn).Additionally, at least 3 of the following items to be met:Experience with developing, optimizing and maintaining AI pipelines.Experience in measuring model performance and assessments.Experience in using and applying the pre-trained machine learning models (for example Generative AI) for specific use cases.Experience with Version Control, MLOps (train, package, deploy, monitor) and CI/CD.Experience with container technologies (e.g., Docker) and orchestration (Kubernetes).Experience with workflow orchestration (e.g., Airflow, Argo etc.).Experience with REST API development.Experience with front-end development.Hiring Team MemberAvula SrivalliRecruitment CoordinatorLinkedInMail
#J-18808-Ljbffr