Engineer, AI/ML & Analytics Platform Engineering

Job Title: Engineer - AI/ML & Analytics Platform Engineering
Location: Hybrid - Plainsboro Township, NJ
Employment Type: Full-Time, Permanent
Industry: Pharmaceutical / Biotech

Position Summary

We are seeking a skilled AI/ML & Analytics Platform Engineer to design, build, and scale enterprise platforms that empower Machine Learning Engineers, Researchers, Data Scientists, and Analysts to develop and operationalize advanced analytics solutions.

This role emphasizes platform engineering and distributed systems architecture rather than pure model development. The ideal candidate will bring strong systems engineering expertise and a track record of building high-performance, scalable infrastructure that supports AI/ML workloads in production environments.

Key Responsibilities

• Design and implement scalable AI/ML and analytics platforms.

• Build infrastructure and tooling for experimentation, model training, deployment, and monitoring.

• Develop self-service platform capabilities for data and ML teams.

• Architect distributed computing environments for large-scale data processing.

• Collaborate cross-functionally with research, engineering, and analytics stakeholders.

• Ensure system performance, reliability, scalability, and operational stability.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Mathematics, Statistics, Operations Research, or related quantitative discipline.

• 5+ years of experience in software engineering, platform engineering, or similar roles.

• Demonstrated experience building AI/ML or analytics platforms.

• Proficiency in at least one strongly typed language (C/C++, Java, Go, or Rust).

• Experience with distributed systems and large-scale processing frameworks such as Ray, Dask, or Spark.

• Background supporting ML or analytics workloads in production environments.

Preferred Qualifications

• Experience in pharmaceutical or biotech organizations.

• Exposure to high-performance computing environments (e.g., Slurm).

• Experience designing and operating large-scale distributed systems.

• Familiarity with regulated environments and data governance standards.