AI/ML & Analytics Platform Engineering in Plainsboro Township, NJ
$110k - $145kGD Resources
Job Description
Job Description
Location: Hybrid – Plainsboro Township, NJ - Onsite - Locals required
Employment Type: Permanent
Industry: Pharmaceutical / Biotech Required
Compensation: $110,000 – $145,000 base + STI & LTI
Relocation: Not available
We are seeking an experienced AI/ML & Analytics Platform Engineer to design, build, and scale enterprise-grade platforms that enable Machine Learning Engineers, ML Researchers, Data Scientists, and Data Analysts to develop, deploy, and operationalize advanced analytics solutions.
This role focuses on platform engineering and distributed systems , not purely model development. The ideal candidate will have strong systems engineering expertise and experience building scalable, high-performance infrastructure to support AI/ML workloads.
Key ResponsibilitiesDesign and build scalable AI/ML and analytics platforms.
Develop infrastructure and tooling to support ML experimentation, training, deployment, and monitoring.
Enable self-service capabilities for ML Engineers, Data Scientists, and Analysts.
Architect and optimize distributed computing solutions for large-scale data processing.
Collaborate cross-functionally with research, engineering, and analytics teams.
Ensure performance, reliability, and scalability of ML systems in production environments.
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Mathematics, Statistics, Operations Research, or a related quantitative field.
5+ years of experience in software engineering, platform engineering, or related roles.
Proven experience building AI/ML or analytics platforms.
Strong experience with at least one strongly typed programming language (e.g., C/C++, Java, Go, Rust).
Experience working with distributed systems and large-scale data processing frameworks (e.g., Ray, Dask, Spark).
Experience supporting ML or analytics workloads in production environments.
Prior experience in the pharmaceutical or biotech industry.
Experience with high-performance computing environments (e.g., Slurm).
Experience designing and operating large-scale distributed systems.
Familiarity with regulated environments and data governance considerations.
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