Computing jobs in edison USA
7 computing jobs found in edison: showing 1 - 7
Full Stack Developer
Company: Colgate-Palmolive |
computing (GCP, AWS, Azure) Test-driven development, continuous integration and deployment Preferred QualificationsLocation: Piscataway, NJ, USA
| Salary: US$110000 - 150000 per year | Date posted: 12 Nov 2026
Full Stack Developer
Company: Colgate-Palmolive |
/Next, Vue/Nuxt, or Angular Agentic Coding best practices GraphQL/Apollo & REST API development Cloud computing (GCP, AWSLocation: Piscataway, NJ, USA
| Salary: US$110000 - 150000 per year | Date posted: 11 Nov 2026
Jr Electrical Engineer
Company: Hays |
demands of modern IT systems, including AI and high-performance computing. Your new role You'll join the team as a JuniorLocation: Edison, NJ, USA
| Salary: US$110000 - 150000 per year | Date posted: 27 Oct 2026
Postdoctoral Scientist - Computational Biologist
Company: Colgate-Palmolive |
-on experience with high-performance computing (HPC) and cloud computing resources (AWS, GCP). Proven ability to workLocation: Piscataway, NJ, USA
| Salary: US$90000 - 96000 per year | Date posted: 15 Oct 2026
Postdoctoral Scientist - Computational Biologist
Company: Colgate-Palmolive |
modeling and target discovery. Hands-on experience with high-performance computing (HPC) and cloud computing resources (AWSLocation: Piscataway, NJ, USA
| Salary: US$90000 - 96000 per year | Date posted: 14 Oct 2026
Program Manager - Ai
Company: SHI International Corp. |
Management Manage AI infrastructure programs involving GPU clusters, AI factories, high-performance computing platforms..., storage, networking, and field deployment initiatives. Provide thought management on emerging trends in rack-scale computingLocation: Piscataway, NJ, USA
| Salary: unspecified | Date posted: 25 Sep 2026
Principal Data Scientist - R01568403
Company: Brillio |
engineering 5. Develop, validate, and maintain probabilistic graph models and advanced statistical computing frameworks 6... and SPSS for statistical analysis and computing 5. In-depth knowledge of probabilistic graph models 6. Experience