Job Title

Experience: 6-12yrs Location : Bangalore, Hyderabad, Mumbai, Pune, Chennai, Kolkata Notice period: Immediate - 30 days Transform data science prototypes into appropriate scale solutions in a production environment Orchestrate and configure infrastructure that assists Data Scientists and analysts in building low latency scalable and resilient machine learning and optimization workloads into an enterprise software product Combine expertise in mathematics statistics computer science and domain knowledge to create advanced AIML models Collaborate closely with the AI Technical Manager and GCC Petro technical professionals and data engineers to integrate and scale models into the business framework Identify data appropriate technology and architectural design patterns to solve business challenges using approved standard analytical tools and AI design patterns and architectures Partner with Data Scientists and IT Foundational services to implement complex algorithms and models into enterprise scale machine learning pipelines Run machine learning experiments and finetune algorithms to ensure optimal performance Consistently deliver complex innovative and complete solutions driving them through design planning development and deployment that simplify business processes and workflows to drive business value Work collaboratively with a large variety of different teams including data scientists data engineers and solution architects from various organizations within business units and IT Required Qualification Minimum 2 years experience in Object Oriented Design and or Functional Programming in Python 2 to 5 years of experience Mature software engineering skills such as source control versioning requirement spec architecture and design review testing methodologies CICD etc. Must have a disciplined methodical minimalist approach to designing and constructing layered software components that can be embedded within larger frameworks or applications Experience implementing machine learning frameworks and libraries such as ML flow Experience with containers and container managements docker Kubernetes Experience developing cloud first solutions using Microsoft Azure Services including building machine learning pipelines in Azure Machine Learning and or Fabric hands on experience in deploying machine learning pipelines with Azure Machine Learning SDK Working knowledge of mathematics primarily linear algebra probability statistics and algorithms Proficient at orchestrating largescale MLDL jobs leveraging big data tooling and modern container orchestration infrastructure to tackle distributed training and massive parallel model executions on cloud infrastructure Experience designing custom APIs for machine learning models for training and inference processes and designing implementing and delivering frameworks for ML Ops Experience with model lifecycle management and automation to support retraining and model monitoring Experience implementing and incorporating ML models on unstructured data using cognitive services and or computer vision as part of AI solutions and workflows History of working with large scale model optimization and hyperparameter tuning applied to MLDL models Knowledge of enterprise SaaS complexities including security access control scalability high availability concurrency online diagnoses deployment upgrade migration internationalization and production support Knowledge of data engineering and transformation tools and patterns such as Databricks Spark Azure Data Factory Ability to engage other technical experts at all organizational levels and assess opportunities to apply machine learning and analytics to improve business workflows and deliver information and insight to support business decisions Ability to communicate in a clear concise and understandable manner both orally and in writing