Job Description:Your Roles and Responsibilities:
• Performance tune and scale out the ML models data scientists have developed. ML engineers will be expected to refactor their Python or R codes into production-ready code and ensure the models are scalable.
• Productionize models developed by data scientists. Examples include refactoring Python code written on Jupyter Notebook to PySpark.
• Develop AI and ML pipelines for continuous operation, feedback and monitoring of ML models demonstrating standard processes from the CI/CD vertical within the MLOps domain. This can include supervising for data drift, triggering model retraining and setting up rollbacks.
• Optimize AI development environments (development, testing, production) for usability, reliability and performance.
• Have a strong relationship with the infrastructure and application development team in order to understand the best method of integrating the ML model into enterprise applications
• Work with data engineers to ensure data storage (data warehouses or data lakes) and data pipelines fostering these repositories and the ML feature or data stores are working as intended.
• Evaluate open-source and AI/ML platforms and tools for feasibility of usage and integration from an infrastructure perspective. This also involves staying updated about the newest developments, patches and upgrades to the ML platforms in use by the data science teams.
Qualifications:Technical Skills:·Hands-on experience in various AI/ML techniques, such as deep learning, natural language processing (NLP), large language models (LLM), etc.·Develop and implement NLP Solutions for text classification, entity extraction and semantic search using libraries such as NLTK, Spacy, etc.·Expert knowledge of Python programming and machine learning frameworks (Scikit-learn, TensorFlow, Keras, PyTorch, etc.)·Experience in Prompt Engineering using Langchain with any Gen AI based platform like AWS Bedrock, Azure AI, Google Vertex AI.·Extensive experience in at least one cloud platform (e.g. AWS, GCP, Azure) and associated machine learning services, e.g. AWS Comprehend, Textract, SageMaker etc.·Experience working in accordance with DevSecOps principles, and familiarity with industry deployment best practices using CI/CD tools and infrastructure as code (e.g., Docker, Kubernetes, Terraform)·Experience in working with cross-functional and distributed teams in a global and diverse environment·Experience in establishing and enforcing AI/ML best practices, standards, and ethics·Proven excellent communication, presentation, and interpersonal skills, with the ability to explain complex AI/ML concepts and results to technical and non-technical audiences·Proven solid analytical, problem-solving, and decision-making skills, with the ability to balance innovation and pragmatism.·Demonstrated passion for learning and staying updated with the latest AI/ML trends and researchLocation: This position can be based in any of the following locations:
Chennai, Gurgaon
Current Guardian Colleagues: Please apply through the internal Jobs Hub in Workday
