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Engaged Employer

Synopsys

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3.9

based on 344 Reviews

145 Synopsys Jobs

AI, Sr Staff Engineer

Synopsys (India) Private Limited

3.9

based on 344 Reviews

3-7 years

Hyderabad / Secunderabad, Bangalore / Bengaluru

1 vacancy

AI, Sr Staff Engineer

Synopsys

posted 5mon ago

Job Role Insights

Flexible timing

Key skills for the job

Python Cloud Computing Architecture Machine Learning Scheduling Deep Learning

+ 2 more

Job Description

We are looking for an experienced, passionate, and self-driven individual who possesses both a broad technical strategy and the ability to tackle architectural and modernization challenges. As an Ideal candidate will help build enterprise Machine Learning platform. They will work with a team of enthusiastic and dynamic ML engineers and Data scientists in building a platform to help Synopsys RD teams to experiment, train models and build Gen AI ML products.

You will be responsible for:

Building AI Platform for Synopsys to orchestrate enterprise-wide Data pipelines, ML training, and inferencing servers.
Develop "AI App Store" eco system to enable RD teams to host Gen AI applications in Cloud
Develop capabilities to ship Cloud Native (Containerized) AI applications/AI systems to on-premises customers
Orchestrate GPU Scheduling from within Kubernetes eco-system (e.g. Nvidia GPU Operator, MIG, and so on)
Create reliable and cost-effective Hybrid cloud architecture using cutting edge technologies (E.g. Kubernetes Cluster Federation, Azure Arc and so on)

Required Qualifications

BS/MS/PhD in Computer Science/Software Engineering or an equivalent degree
12+ years of total experience building systems software, enterprise software applications, and microservices
Expertise and/or experience in following programming languages : Go and Python
Experience building highly scalable REST API
Experience with event driven software architecture and message brokers (NATS / Kafka)
Design complex distributed systems (High-level and low-level systems design)
Knowing CAP theorem in depth and applying it in building real-world distributed systems.
In-Depth Kubernetes knowledge: Be able to deploy Kubernetes on-prem,working experience with managed Kubernetes services (AKS/EKS/GKE) and Kubernetes APIs
Strong systems knowledge in Linux Kernel, CGroups, namespaces, and Docker
Experience with at least one cloud provider (AWS/GCP/Azure)
Ability to solve complex problems using efficient algorithms
Experience with using RDBMS (PostgreSQL preferred) for storing and queuing large sets of data

Nice to have:

Experience with service meshes (Istio)
Experience with Kubernetes cluster federation
Prior experience with AI/ML workflows and tools (PyTorch, ML Flow, AirFlow, )
Experience prototyping, experimenting, and testing with large datasets, and analytic data flows in production
Strong fundamentals in Statistics, Machine Learning, and/or Deep Learning