Analytics Platform Engineer (Pharma) - Plainsboro Township, New Jersey

MissionHires; Plainsboro Township (NJ); Hybrid; USD 120,000 - 150,000; Full time

Job summary

MissionHires is collaborating with a global biopharmaceutical organization to hire an AI/ML & Analytics Platform Engineer in a hybrid role based in Plainsboro Township, NJ. The role involves designing and optimizing AI/ML platforms, collaborating with cross-functional teams to enable scalable model training, and implementing modern DevOps practices.

The ideal candidate should have 5+ years of experience in platform engineering, strong programming skills in Python, Spark, and SQL, and familiarity with AWS AI/ML tools.

Qualifications

• 5+ years of experience in AI/ML platform engineering or analytics platforms.
• Proven experience building scalable platforms using microservices or event-driven architectures.
• Hands-on experience with AWS services, including AI/ML tooling.

Responsibilities

• Design and enhance AI/ML & Analytics platform services.
• Enable scalable batch and real-time ML workflows.
• Improve platform performance and reduce operational overhead.

Skills

Python

Spark

SQL

AWS

Infrastructure-as-Code

Terraform

Docker

Kubernetes

CI/CD

Git

Education

Bachelor’s or Master’s in Computer Science, Engineering, Data Science, Mathematics, Statistics, Operations Research

Tools

SageMaker

PyTorch

TensorFlow

GitHub

GitLab

Jenkins

Dask

Databricks

Snowflake

Kafka

Job description

MissionHires is partnering with a global biopharmaceutical organization to hire a hands‑on AI/ML & Analytics Platform Engineer. In this hybrid role (approx. 60% onsite in Plainsboro Township, NJ), you will design, build, and optimize secure, compliant AI/ML platforms that power advanced analytics across research, commercial, and business operations. You’ll collaborate with ML engineers, data scientists, and cloud teams to enable scalable model training, inference, and deployment, championing automation‑first, IaC, and modern DevOps practices to improve reliability, performance, and developer experience.

Responsibilities

• Design and enhance AI/ML & Analytics platform services across development, testing, and production environments
• Enable scalable batch and real‑time ML workflows with flexible deployment strategies
• Improve platform performance, optimize CPU/GPU utilization, and reduce operational overhead
• Implement Infrastructure-as-Code (IaC) and GitOps practices to scale cloud infrastructure
• Partner with cloud engineering teams to ensure reliability, security, compliance, and cost efficiency
• Support monitoring, observability, model/artifact registries, and governance frameworks
• Guide cross‑functional teams on architecture design, CI/CD pipelines, and scalable ML deployments
• Continuously improve platform usability and efficiency for internal users

Requirements

• Bachelor’s or Master’s in Computer Science, Engineering, Data Science, Mathematics, Statistics, Operations Research, or related field
• 5+ years of experience in AI/ML platform engineering, analytics platforms, or similar environments
• Proven experience building scalable, self‑service platforms using microservices or event‑driven architectures
• Strong programming skills in Python, Spark, and SQL with familiarity in PyTorch or TensorFlow
• Hands‑on experience with AWS services, including AI/ML tooling such as SageMaker
• Proficiency with Infrastructure-as-Code tools (Terraform, CDK, Pulumi, OpenTofu) and CI/CD pipelines
• Experience with Git‑based version control and CI tools (GitHub, GitLab, Jenkins, etc.)
• Containerization and orchestration expertise (Docker, Kubernetes, etc.)
• Experience managing large‑scale CPU/GPU or multi‑GPU environments
• Knowledge of observability, monitoring, and system performance optimization
• Strong communication skills and experience collaborating with cross‑functional stakeholders
• Preferred: Experience in pharmaceutical or biotech environments
• Preferred: Proficiency in strongly typed languages (C/C++/Java/Go/Rust)
• Preferred: Experience with distributed systems (Ray, Dask, Spark) or HPC (Slurm)
• Preferred: Experience with data platforms (Databricks, Snowflake, Lake Formation)
• Preferred: Experience with streaming technologies (Kafka, Spark Streaming)
• Preferred: Familiarity with GitOps tools (ArgoCD, Crossplane)
• Preferred: Multi‑cloud exposure (AWS, GCP, Azure)
• Preferred: Experience with high‑performance inference frameworks (ONNX Runtime, TensorRT, Triton) or GenAI workloads