The Team :
- As a member of the Commodity Insights you will work on building and deploying ML / LLM powered products and capabilities to power natural language understanding, data extraction, information retrieval and data sourcing solutions for S&P Global Market Intelligence and our clients.
- You will be responsible for the management, deployment and optimization of ML Models and pipelines while leading-by-example in a highly engaging work environment. You will work in a (truly) global team and encouraged for thoughtful risk-taking and self-initiative.
What s in it for you :
Exciting tasks and the team with own product development in the space of intelligent data solutions based on Machine LearningResponsibilities :
Play a central role in all stages of the AI product development life cycle, including :Designing Machine Learning systems and model scaling strategiesResearch & Implement ML and Deep learning algorithms for productionRun necessary ML tests and benchmarks for model validationFine-tune, retrain and scale existing model deploymentsExtend existing ML library s and write packages for reproducing componentsPartner with business leaders, domain experts, and end-users to gain business understanding, data understanding, and collect requirementsInterpret results and present them to business leadersManage production pipelines for enterprise scale projectsPerform code reviews & optimization for your projects and teamLead and mentor by example, including project scrumsTechnical Requirements :
Proven track record as a ML engineerExpert proficiency in Python (Numpy, Pandas, Spacy, Sklearn, Pytorch / TF2, HuggingFace etc.)Excellent exposure to large scale model deployment strategies and toolsExcellent knowledge of ML & Deep Learning domainSolid exposure to Information Retrieval, Web scraping and Data Extraction at scaleKnowledge in AWS Technologies : Terraform, CFT, Lambda, Fargate, ECS and also in SQL, containerization and Django.Experience with SOTA models related to NLP like Classification, Summarization, Phrase extraction, Table Extraction and OCROpen to learning new technologies and programming languages as requiredKnowledge in model monitoring and retrain & tuning of modelsGood to have :
4+ years of relevant experience in ML EngineeringPrior substantial experience regarding document processingSkills Required
Machine Learning, Natural Language Processing, Python, Deep Learning, Aws