Cryptography Research Scientist, FHE

Data & AIposted 3mo ago

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About the Team - LG's Emerging Technology Lab

LG's Emerging Technology Lab (ETL) is the catalyst for technological innovation within LG’s CTO organization. Located in the Silicon Valley and New Jersey, we drive excellence across CTO organizations and business units by pioneering in select emerging technology areas. As the Center of Excellence (CoE), we define and shape key technology domains, setting strategic directions that foster impactful internal and external partnerships to deliver measurable business value.

Position Overview

We are seeking a highly motivated Cryptography Research Engineer / Scientist to join our Advanced Security team located in Santa Clara, CA. This can be a hybrid position.

The Cryptography Research Scientist will be working on next-generation cryptographic technologies, with a primary focus on Fully Homomorphic Encryption (FHE) and additional involvement in Post-Quantum Cryptography (PQC). This position is intended for early-career researchers, typically candidates with a PhD and 0–2 years of relevant research or industry experience.

This role is centered on the research, optimization, implementation, and deployment of privacy-enhancing technologies for real-world applications. The ideal candidate will have strong mathematical foundations in modern cryptography, hands-on software development skills, and a passion for translating advanced cryptographic concepts into practical systems and Proof-of-Concept (PoC) demonstrations.

The candidate will work on cutting-edge problems involving encrypted computation, privacy-preserving AI/analytics, and quantum-safe cryptographic systems.

Key Responsibilities

Conduct advanced research and development in Fully Homomorphic Encryption (FHE) and related privacy-enhancing technologies.
Design, optimize, and implement FHE algorithms and pipelines for practical applications and deployment scenarios.
Develop high-performance implementations for specialized use cases, including:

privacy-preserving AI/ML inference,
secure analytics and recommendation systems,
confidential cloud computation.

Develop and demonstrate Proof-of-Concept (PoC) systems showcasing practical FHE applications.
Evaluate and integrate modern FHE frameworks and libraries such as:

OpenFHE,
HEAAN/CKKS-based frameworks,
TFHE,
Microsoft SEAL,
PALISADE,
Concrete,
or related technologies.

Contribute to research and development efforts in Post-Quantum Cryptography (PQC), including lattice-based cryptography and quantum-safe migration technologies.
Collaborate with cross-functional engineering and product teams to transition research into deployable technologies.
Track emerging developments in cryptography, privacy-enhancing technologies, and quantum-safe security.

Required Qualifications

PhD in Computer Science, Mathematics, Electrical Engineering, Cryptography, or a related field, with 0-2 years of relevant industry experience.
Strong theoretical background in modern cryptography, particularly lattice-based cryptography and/or Fully Homomorphic Encryption.
Hands-on experience implementing cryptographic algorithms and optimizing performance-critical systems.
Strong programming skills in languages such as:

C++,
Python,
CUDA,
Rust,
or similar.

Familiarity with one or more FHE libraries/frameworks.
Strong understanding of algorithm optimization, computational complexity, and memory-performance tradeoffs.
Ability to independently drive research ideas into working prototypes and PoCs.
Strong analytical, problem-solving, and communication skills.

Preferred Qualifications

Experience with GPU acceleration and high-performance computing for cryptographic workloads.
Familiarity with CKKS, TFHE, BFV, or BGV schemes.
Experience with encrypted machine learning or privacy-preserving AI systems.
Knowledge of Post-Quantum Cryptography standards and NIST PQC algorithms (e.g., ML-KEM/Kyber, ML-DSA/Dilithium).
Publications or open-source contributions in cryptography, security, or privacy-enhancing technologies.
Experience working in research labs or advanced technology development environments.

Please Note: the salary range listed is dependent on the experience of the candidate. There are additional incentives to this compensation package.

#LI-JH1 #LI-Hybrid

Recruiting Range

$169,000—$186,000 USD

Benefits Offered Full-Time Employees:

No-cost employee premiums for you and your eligible dependents for competitive medical, dental, vision and prescription benefits.
Auto enrollment with immediate vesting of competitive company matching contributions in a 401(k) Retirement Savings Plan with several investment options.
Generous Paid Time Off program that includes company holidays and a combined bank of paid sick and vacation time.
Performance based Short-Term Incentives (varies by role).
Access to confidential mental health resources to help you and your loved ones improve your quality of life. Personal fitness goal incentives.
Family orientated benefits such as paid parental leave and support for families raising children with learning, social, behavioral challenges, or developmental disabilities.
Group Rate Life and Disability Insurance.

Benefits Offered Temporary/Contractors:

Eligible for the relevant benefit programs offered through our partner agencies.

Privacy Notice to California Applicants

Applicants who need assistance or a reasonable accommodation during the hiring process may contact our team by phone at: 973-477-7090 or support@lg4me.freshdesk.com. This email and phone number will only reply to accommodation requests and is not intended for general employment inquiries.

All qualified applicants will be considered for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable federal, state, or local law.

In addition to the above, LG believes that pay transparency is a key part of diversity, equity, and inclusion. Our salary ranges take into account many factors in making compensation decisions including but not limited to skillset, experience, licensure, certifications, internal equity, and other business needs. While we consider geographic pay differentials in final offers, because we operate in many geographies where applicable, the salary range listed may not reflect all geographic differentials applied.