1047 Aiml Engineer Intern jobs in Piscataway,NJ

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Immunohistochemistry Histotechnologist

Memorial Sloan Kettering Cancer Center - New York, NY

Immunohistochemistry Histotechnologist

~ 50 min Onsite

New, Posted 1 day ago

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Principal Engineer - Python API Development

Fidelity Investments

Elizabeth, NJ 07202

~ 29 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's or Master's degree in Computer Science, Software Engineering, or a closely related engineering discipline
8+ years (typically 10+) building and operating production platforms and services at scale
Deep software engineering expertise in Python and distributed systems
A track record of building production‑grade services, libraries, and internal platforms
Linux fluency and scripting are required
Cloud platform leadership (AWS) —hands-on with S3, Lambda, Batch, Step Functions, EventBridge, CloudWatch, and SNS/SQS—and experience shaping platform patterns that other teams adopt
Experience enabling managed ML services (e.g., SageMaker) as part of broader platform capabilities; exposure to Azure or GCP is beneficial
DevOps and CI/CD at scale, owning standards for automated build/test/deploy (e.g., Jenkins, Git‑based workflows), containerization (Docker), release governance, and multi‑environment promotion for ML‑enabled workloads
Infrastructure as Code (CloudFormation, Terraform/OpenTofu) and platform reliability engineering (SLOs/error budgets, capacity planning, cost observability, incident response, and post‑mortems) for ML serving and data/feature pipelines
ML enablement in production: model packaging, deployment strategies (batch/online/streaming), inference routing, traffic management, performance tuning, observability, and controls for responsible use—without a research or modeling focus
Cross‑org technical leadership: you mentor junior and senior engineers, are a backbone of code review across repos, and routinely consider impacts on upstream/downstream systems when proposing changes
Set platform strategy and standards for ML packaging, deployment, serving, and observability—driving consistent adoption across squads and business units
Partner with Data Scientists to package, scale, and operationalize models; define the APIs, guardrails, and automation that take work from experimentation to reliable production
Enable secure, scalable access to traditional and generative models by collaborating with platform and application engineers to integrate through enterprise gateways and services
Advance model/data observability—tooling for data and feature drift detection, prediction‑quality monitoring and uncertainty signals, and automated diagnostics/ explainability
Lead cross‑platform incident response and post‑mortems, drive systemic fixes, and evolve standards to prevent recurrence—across applications and the platform
Uplevel engineering velocity by introducing reusable frameworks, paved paths, and CI/CD templates that simplify integration, reduce toil, and improve reliability at scale
Reduce cost and complexity across the ML ecosystem through pragmatic technology choices, clear abstractions, and a long‑term platform roadmap
The base salary range for this position is $107,000-216,000 USD per year.
Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.

SmartExplore AI is experimental.

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HR & Talent Intern (Fall 2026)

Pure Power Engineering

Bayonne, NJ 07002

$20-$25/hr

New, Posted 1 day ago

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Principal Engineer - Python API Development

Fidelity Investments

Jersey City, NJ 07311

~ 37 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's or Master's degree in Computer Science, Software Engineering, or a closely related engineering discipline
8+ years (typically 10+) building and operating production platforms and services at scale
Deep software engineering expertise in Python and distributed systems
A track record of building production‑grade services, libraries, and internal platforms
Linux fluency and scripting are required
Cloud platform leadership (AWS) —hands-on with S3, Lambda, Batch, Step Functions, EventBridge, CloudWatch, and SNS/SQS—and experience shaping platform patterns that other teams adopt
Experience enabling managed ML services (e.g., SageMaker) as part of broader platform capabilities; exposure to Azure or GCP is beneficial
DevOps and CI/CD at scale, owning standards for automated build/test/deploy (e.g., Jenkins, Git‑based workflows), containerization (Docker), release governance, and multi‑environment promotion for ML‑enabled workloads
Infrastructure as Code (CloudFormation, Terraform/OpenTofu) and platform reliability engineering (SLOs/error budgets, capacity planning, cost observability, incident response, and post‑mortems) for ML serving and data/feature pipelines
ML enablement in production: model packaging, deployment strategies (batch/online/streaming), inference routing, traffic management, performance tuning, observability, and controls for responsible use—without a research or modeling focus
Cross‑org technical leadership: you mentor junior and senior engineers, are a backbone of code review across repos, and routinely consider impacts on upstream/downstream systems when proposing changes
Set platform strategy and standards for ML packaging, deployment, serving, and observability—driving consistent adoption across squads and business units
Partner with Data Scientists to package, scale, and operationalize models; define the APIs, guardrails, and automation that take work from experimentation to reliable production
Enable secure, scalable access to traditional and generative models by collaborating with platform and application engineers to integrate through enterprise gateways and services
Advance model/data observability—tooling for data and feature drift detection, prediction‑quality monitoring and uncertainty signals, and automated diagnostics/ explainability
Lead cross‑platform incident response and post‑mortems, drive systemic fixes, and evolve standards to prevent recurrence—across applications and the platform
Uplevel engineering velocity by introducing reusable frameworks, paved paths, and CI/CD templates that simplify integration, reduce toil, and improve reliability at scale
Reduce cost and complexity across the ML ecosystem through pragmatic technology choices, clear abstractions, and a long‑term platform roadmap
The base salary range for this position is $107,000-216,000 USD per year.
Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.

SmartExplore AI is experimental.

Apply Directly

Senior Data Product Engineer, Commercial

Genmab

Plainsboro, NJ 08536

RemoteUrgently HiringEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

5+ years in data engineering, analytics engineering, or data platform development.
10+ years of experience IT with some in Biotech/Pharma industry
Expert-level proficiency in:
**DBT:** advanced macros, Jinja, testing, exposures, dbt Cloud deployment.
**Databricks:** Spark (PySpark, SQL), Delta Lake, Unity Catalog.
**Snowflake**
**AWS: S3, Glue, Lambda, Step Functions, Datasync, EMR, Redshift, IAM and networking/security fundamentals.**
**Data Visualization:** Power BI or Tableau.
Strong programming background in Python and SQL (including query optimization).
Proven experience with distributed systems and large-scale datasets (TB scale).
Experience implementing CI/CD pipelines, data testing, and infrastructure as code.
Solid understanding of data governance, security, and compliance in enterprise environments.

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Lead Systems Engineer (HPC)

Princeton University

Princeton, NJ 08542

~ 36 min Onsite

10+ years of strong experience managing advanced research computing systems.
Strong expertise with Linux system administration, installation, and troubleshooting.
Advanced experience writing scripts in languages such as bash, Python and/or Perl.
Proficient in managing networking in HPC environments.
Strong experience managing software in an advanced research computing environment.
Experience supporting scheduling and managing jobs (SLURM) in large-scale computing environments.
Strong oral and written communication skills, with the ability to proactively engage peers and communicate effectively across a diverse stakeholder community.
Strong ability to solve complex and system infrastructure problems, and share expertise with colleagues at all levels.
Demonstrated ability to collaborate across teams to solve systems and infrastructure challenges, aligning day‑to‑day operational needs with longer‑term technical and organizational goals as technologies evolve.
When provided access to personal, proprietary and/or otherwise confidential data, maintain such data in the strictest confidence and follow procedures to ensure the privacy, security, and proper use of data.
Education: Bachelors degree in a related field or equivalent experience.

SmartExplore AI is experimental.

New, Posted 4 hours ago

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