Graph Machine Learning Scientist

Key Skills

Apache Hadoop, C++, Computer Vision (CV), Cypher, Java Programming, Machine learning techniques, Natural Language Processing (NLP), Neo4J, Python Programming, PyTorch, SPARK Programming, SPARQL, SQL, TigerGraph

Job Description

Based in Southern California with locations in Malibu, Calabasas and Camarillo; HRL has been on the leading edge of technology, conducting pioneering research and advancing the state of the art. 

ESSENTIAL JOB FUNCTIONS:

Perform research and development in graph machine learning and its intersection with other relevant research areas, including network science, computer vision, and natural language processing. Tasks will include the development, simulation, evaluation, and implementation of graph computing algorithms applied to a variety of applications. Additional job functions include solving customer problems, writing invention disclosures, publishing papers, briefing customers, writing proposals, and assisting in marketing HRL expertise.

EXPERIENCE DESIRED:

• Research experiences in graph mining, graph representation learning, and their real-world applications to (e.g., cybersecurity, social network, and business analytics).
• Proficient in at least one major coding language (e.g., Python, Java, C++) and graph machine learning framework (e.g., PyTorch Geometric, Deep Graph Library).
• Experience working with knowledge graphs, graph data models (e.g., RDF, LPG), graph databases (e.g., Neo4J, TigerGraph), and graph query languages (e.g., SPARQL, Cypher).
• Research experiences with Computer vision and Natural Language Processing.
• Experience working with SQL databases (any variants) and distributed AI computing frameworks (e.g., Ray, Spark, Hadoop) is a plus
• Publications in top-tier research conferences and journals. 

KNOWLEDGE DESIRED:

Expertise in one or more of the following areas: Graph Neural Networks, Resource-efficient Graph Learning, Trustworthy Graph Learning, Explainable AI, Text Mining, Vision-Language Modeling, and Multi-modal Machine Learning. 

EDUCATION DESIRED:

Ph.D. in Computer Science, Data Science, Network Science, Applied Math, Statistics, EE or related fields

ESSENTIAL PHYSICAL/MENTAL REQUIREMENTS:

Good communication (verbal and written) skills, active participation in R&D team activities is required. Able and willing to occasionally travel.

SPECIAL REQUIREMENT:

U.S. Citizenship or Permanent Resident Status Required.

Compensation:

The base salary range for this full-time position is $104,000 - $174,000 + bonus + benefits.

Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range during the hiring process. Please note that the compensation details listed reflect the base salary only, and do not include potential bonus or benefits.

This position must meet Export Control compliance requirements, therefore a U.S. Person as defined by 22 C.F.R. § 120.15is required. U.S. Person includes U.S. Citizen, lawful permanent resident, refugee, or asylee.

HRL offers a very competitive compensation and benefits package. Our Regular/Full Time benefits include medical, dental, vision, life insurance, 401K match, gym facilities, PTO, growth potential, and an exciting and challenging work environment.

HRL Laboratories is an Equal Employment Opportunity employer and does not discriminate in recruiting, hiring, training or promoting, on the basis of race, ethnicity, color, creed, religion, sex, sexual orientation, gender, gender identity, genetic information, national origin, physical or mental disability, pregnancy, medical condition, age, U.S. military or protected veteran status, union membership, or political affiliation. We maintain a drug-free workplace and perform pre-employment substance abuse testing.