20 hours ago
Bengaluru, IndiaStaff+
Responsibilities
- Lead end-to-end architecture for AI/ML computational science solutions, including data ingestion, simulation pipelines, feature engineering, model development, deployment, and monitoring.
- Define technical direction for scientific AI, physics-informed ML, surrogate modeling, optimization, uncertainty quantification, generative AI, and accelerated computing.
- Own architecture decisions across compute, storage, orchestration, MLOps, model governance, security, observability, performance, cost optimization, and enterprise integration.
- Partner with scientists, engineers, product owners, data architects, cloud engineers, delivery leads, and clients to translate complex problems into scalable solutions.
- Lead design reviews, architecture governance, technical risk assessment, estimation, implementation planning, and quality assurance for complex programs.
- Guide engineering teams on reference architectures, accelerators, coding standards, model lifecycle practices, and production readiness.
- Support sales and pre-sales with solution narratives, technical proposals, demos, proofs of concept, and industry-specific AI/ML offerings.
- Drive thought leadership and reusable assets related to scientific AI, simulation intelligence, digital twins, agentic workflows, generative AI, and cloud-native scientific computing.
Requirements
- A bachelor's degree or equivalent in Computer Science, Engineering, Applied Mathematics, Statistics, Physics, Computational Science, Data Science, or a related field is required.
- At least 12 years of experience is stated in the project role requirements; the detailed qualifications also require at least 8 years in AI/ML or related fields and 5 years architecting enterprise-scale platforms.
- At least 4 years of experience with Python and scientific or ML frameworks such as NumPy, SciPy, pandas, scikit-learn, PyTorch, TensorFlow, JAX, or XGBoost.
- At least 3 years of experience with MLOps or production ML practices, including experiment tracking, model registries, feature stores, testing, monitoring, and lifecycle governance.
- At least 3 years of experience with scalable data engineering, distributed computing, workflow orchestration, APIs, batch or stream processing, and cloud-native deployment patterns.
- At least 4 years of experience leading technical teams, reviewing architecture, guiding delivery, and communicating technical trade-offs to senior stakeholders.
- At least 5 years of hands-on Databricks experience across lakehouse architecture, AI/ML workflows, scientific data engineering, distributed analytics, and enterprise integration.
- Experience with Python, SQL, Git, containers, orchestration tools, distributed processing, robust software engineering, and AI/ML methods including surrogate modeling, physics-informed ML, optimization, time series, anomaly detection, computer vision, NLP, generative AI, and uncertainty-aware modeling.
- Experience with Databricks Lakehouse, Delta Lake, Unity Catalog, Workflows, notebooks, jobs, MLflow, Feature Store, Mosaic AI, vector search, Spark, and AWS, Azure, or GCP integration.
- Preferred qualifications include an advanced degree, client-facing consulting or pre-sales experience, HPC or GPU acceleration experience, scientific or engineering domain experience, reusable architecture or technical asset development, relevant certifications, and experience with agentic AI, RAG, knowledge graphs, semantic layers, or scientific knowledge management.
Tech Stack
Apache SparkAWSAzureDatabricksGitGoogle Cloud PlatformMLflowNumPyPandasPythonPyTorchscikit-learnSciPySQLTensorFlowXGBoost
Categories
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.