About us:Intuitive is an innovation-led engineering company delivering business outcomes for 100’s of Enterprises globally. With the reputation of being a Tiger Team & a Trusted Partner of enterprise technology leaders, we help solve the most complex Digital Transformation challenges across following Intuitive Superpowers:Modernization & MigrationApplication & Database ModernizationPlatform Engineering (IaC/EaC, DevSecOps & SRE)Cloud Native Engineering, Migration to Cloud, VMware ExitFinOpsData & AI/MLData (Cloud Native / DataBricks / Snowflake)Machine Learning, AI/GenAICybersecurityInfrastructure SecurityApplication SecurityData SecurityAI/Model SecuritySDx & Digital Workspace (M365, G-suite)SDDC, SD-WAN, SDN, NetSec, Wireless/MobilityEmail, Collaboration, Directory Services, Shared Files ServicesIntuitive Services:Professional and Advisory ServicesElastic Engineering ServicesManaged ServicesTalent Acquisition & Platform Resell ServicesAbout the job:Title: Modelling & Simulation OPsStart Date: ImmediatePosition Type: Full-time EmploymentLocation: Remote across IndiaABOUT THE ROLE:The ideal candidate will be an experienced ML Engineer (MLE) or a MLOPs Engineer with in-depth knowledge of scaling computationally intensive modelling and simulation systems. Candidates must demonstrate expertise in developing Data and Feature engineering pipelines that are robust, scalable, and continuously deployable (CI/CD). They must be adept at collaborating with subject matter experts (SMEs) and Data Scientists (DS) as part of a multi-faceted team.Core Skills:The successful candidate will be able to work with DS & SME to scale complex analytical workflows used in multi model ML and simulation systems, while pragmatically optimizing around scalability, parallelization, issues of memory usage, storage, and latency, specifically:Be very strong at feature engineeringStrong understanding of Cloud Systems, and their ML options, particularly Azure.Familiar with CI/CD pipelines, particularly Azure Pipelines.Able to combine and coordinate Cloud Services, Data Services and Compute Services into robust systems.Able to clearly communicate to SMEs, DS and other stake holders options and trade-offs in taking models and simulations to production that are both compute and data intensive.Python experience is also required. Python will be used for automating & scaling modeling workflows, pre/post-processing, and for customizing processing intensive pipelines .Experience scaling modelling and simulation in the context of biomechanical systems is strongly preferred.QUALIFICATIONSRequired:5+ years of experience in Simulation & Modelling as an MLE or an MLOPs Engineer.Nice to Have:Advanced Degree (MSc, PhD) in Computer Science.Advanced Degree (MSc, PhD) in Computer Science.Some familiarity with Azure Machine Learning.PREFERRED SKILLS & EXPERIENCEIn addition to deep familiarity with Python programming, we are looking for complementary experience in one or more of the following areas:AI/ML breadth and depth including: EDA, model training/retraining, model evaluation & interpretation.Strong familiarity with best practices for ML, including: Regression, Tree, Deep Neural NetworkEngagement with emerging best practices for LLM & Generative AI models
Job Title
MLOPs Engineer