AI/ML & Analytics Platform Engineer

MissionHires • United State
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AI Summary

MissionHires is seeking a hands-on AI/ML & Analytics Platform Engineer to design, build, and optimize secure, compliant AI/ML platforms. The role involves collaborating with ML engineers and data scientists to enable scalable model training, inference, and deployment. Key requirements include 5+ years of experience in AI/ML platform engineering and strong programming skills in Python, Spark, and SQL.

Key Highlights
Design and enhance AI/ML & Analytics platform services
Enable scalable batch and real-time ML workflows
Improve platform performance and reduce operational overhead
Key Responsibilities
Design and enhance AI/ML & Analytics platform services
Enable scalable batch and real-time ML workflows
Improve platform performance and reduce operational overhead
Technical Skills Required
Python Spark SQL PyTorch TensorFlow AWS services Infrastructure-as-Code tools (Terraform, CDK, Pulumi, OpenTofu) CI/CD pipelines Git-based version control Containerization and orchestration (Docker, Kubernetes)
Benefits & Perks
Relocation assistance may be provided
Hybrid work environment (approx. 60% onsite in Plainsboro Township, NJ)
Nice to Have
Experience in pharmaceutical or biotech environments
Familiarity with GitOps tools (ArgoCD, Crossplane)
Multi-cloud exposure (AWS, GCP, Azure)

Job Description


This position is located in Plainsboro, NJ. Relocation assistance may be provided to the right candidate.


Why This Role Matters

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.


How You'll Contribute

  • 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


What Makes You a Great Fit

  • 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

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