Intel Cloud Software Development Engineer 

Israel, Center District, Petah Tikva 

843737684

Job Description

At Intel Trusted AI Products, we are on a mission to create a Secure Federated AI Service and Trust Platform as a Service based on state-of-the-art distributed systems, cryptography, confidential computing, and federated learning. These services have the potential to revolutionize the way enterprises store and process sensitive data in the cloud by ensuring data integrity, resiliency, confidentiality, and verifiability-all with the advantages of a managed service.

Key Responsibilities:

• Collaborate with ML, AI, security, and distributed systems teams to design and architect scalable, secure, and efficient platforms for federated learning and decentralized AI.
• Develop, implement, and maintain distributed systems software components and machine learning model orchestration.Analyze and optimize the performance of distributed systems and federated learning pipelines, ensuring high throughput, low latency, and fault tolerance.
• Create prototypes and proof-of-concept implementations to validate federated learning use cases in secure enclaves and privacy-preserving AI environments.
• Implement secure, privacy-preserving training techniques, such as secure aggregation, differential privacy, and homomorphic encryption.
• Conduct rigorous unit testing, integration testing, and performance testing to ensure the reliability and security of ML models running in federated environments.
• Document software designs, ML model orchestration, federated learning architecture, and technical specifications.

Qualifications

Qualifications

• BSc or MSc degree in Computer Science, Computer Engineering, or a related field.
• 5+ years of professional experience in software development with a focus on distributed systems, federated learning, or secure AI.
• Hands-on experience in architecting and developing scalable, reliable, low-latency, and high-throughput distributed systems.
• Strong programming skills in Python and C++.
• Strong problem-solving skills and the ability to work in a collaborative team environment.
• Excellent communication and interpersonal skills.

Preferred Qualifications:

• Understanding of federated learning principles, including FedAvg, FedProx, and decentralized AI model aggregation.
• Experience implementing privacy-enhancing technologies, such as secure enclaves, SMPC, and trusted execution environments (TEE).
• Experience with federated learning frameworks (e.g., Flower, OpenFL, PySyft, TensorFlow Federated (TFF)).
• Experience in real-world federated learning applications (e.g., healthcare, finance, IoT, smart cities).

Experience Contributing to Open-Source projects.

Experience with AI training architectures on CPUs and GPUs.

Experience working on Cloud and Edge-based architecture.

Knowledge of Unix/Linux operating systems especially with virtual containerized environments (Docker, Conda).

Multi-node cluster setup and orchestration (Kubernetes); CI/CD tools and methodologies.

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock, bonuses, as well as, benefit programs which include health, retirement, and vacation. Find more information about all of our Amazing Benefits