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AI/ML & Analytics Platform Engineer

Macpower Digital Assets Edge Private Limited

  • Plainsboro, NJ
  • 11 days ago
  • $110,000–$150,000 Per Year
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Skills

  • Amazon Web Services (AWS)unmatched
  • Architectural Servicesunmatched
  • Artificial Intelligence (AI)unmatched
  • Atlassian JIRAunmatched
  • Automationunmatched
  • Biotech and Pharmaceuticalunmatched
  • C Programming Languageunmatched
  • C++ Programming Languageunmatched
  • CPU (Central Processing Unit)unmatched
  • CUDA (Compute Unified Device Architecture)unmatched
  • Cloud Computingunmatched
  • Communication Skillsunmatched
  • Computer Scienceunmatched
  • Continuous Deployment/Deliveryunmatched
  • Continuous Integrationunmatched
  • Cost Controlunmatched
  • Cross-Functionalunmatched
  • Data Analysisunmatched
  • Data Scienceunmatched
  • Distributed Computingunmatched
  • Dockerunmatched
  • GCP (Good Clinical Practices)unmatched
  • GPU (Graphics Processing Unit)unmatched
  • GitHubunmatched
  • Go Programming Language (Golang)unmatched
  • Javaunmatched
  • Jenkinsunmatched
  • Large-Scale Systemsunmatched
  • Mathematicsunmatched
  • Microsoft Windows Azureunmatched
  • Operations Managementunmatched
  • Operations Researchunmatched
  • Performance Analysisunmatched
  • Performance Managementunmatched
  • Problem Solving Skillsunmatched
  • Product Testingunmatched
  • Production Systemsunmatched
  • Python Programming/Scripting Languageunmatched
  • Regulatory Complianceunmatched
  • SQL (Structured Query Language)unmatched
  • Scalable System Developmentunmatched
  • Snowflake Schemaunmatched
  • Statisticsunmatched
  • System Architectureunmatched
  • Team Playerunmatched
  • Technical Leadershipunmatched
  • Use Casesunmatched

Description

Education: Bachelor's or Master's in Computer Science, Engineering, Data Science, Mathematics, Statistics, Operations Research, or related field.
Key Responsibilities:
  • Contribute to building AI/ML & Analytics platform, services, and tools across dev, test, and prod environments to accelerate model training, inference, and deployment.
  • Build capabilities for batch and real-time workflows at scale with flexible deployment strategies for use cases like low-latency predictions and offline inference.
  • Improve platform performance, reduce manual intervention, scale compute, and increase deployment efficiency.
  • Collaborate with cloud teams to ensure operational effectiveness, reliability, security, and efficiency.
  • Provide technical guidance on monitoring systems like registries and alerting, plus governance frameworks for regulatory compliance.
  • Work with cross-functional teams on AI/ML system architecture, deployment pipelines, and solution scaling.
  • Champion self-service patterns, IaC, and GitOps for platform development.
Required Technical Skills:
  • Experience building scalable AI/ML & Analytics platforms for ML Researchers, Engineers, Data Scientists, and Analysts.
  • Proficiency in Python, Spark, SQL, and ML frameworks like PyTorch or TensorFlow.
  • Strong AWS knowledge, including AI/ML services like SageMaker.
  • IaC tools such as Terraform, OpenTofu, CDK, or Pulumi, plus CI/CD pipelines.
  • Containerization with Docker or Podman, and orchestration with Kubernetes or Rancher.
  • VCS like GitHub or GitLab, CI/CD tools like GitHub Actions or Jenkins, and JIRA.
  • Ops fundamentals including registries, observability, monitoring, performance analysis, and cost optimization.
Required Functional/Behavioral Skills:
  • Hands-on problem-solving for technical and architectural challenges in scalable, secure platforms.
  • Automation-first mindset with security consciousness and focus on developer experience.
  • Strong communication to engage stakeholders effectively.
  • Ability to work collaboratively in cross-functional, agile teams valuing individual development.
Preferred Skills:
  • Pharma/biotech domain experience.
  • Strongly typed languages like C/C++, Java, Go, or Rust.
  • Large-scale distributed systems like Ray, Dask, Spark, or HPC like Slurm.
  • Data platforms like Databricks, Snowflake, or dbt with Delta, Iceberg, Hudi.
  • Real-time streaming like Kafka or Spark Streaming.
  • GitOps tools like ArgoCD or Crossplane.
  • Multi-cloud (AWS, GCP, Azure).
  • High-performance inference frameworks like ONNX Runtime, TensorRT, or Triton.
  • Large-scale CPU/GPU infrastructure with CUDA knowledge.

Numbers & Facts

LocationPlainsboro, NJ
Salary$110,000–$150,000 Per Year

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