527 Engineer jobs in Gillette,NJ

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Senior Vice President, Infrastructure Engineer

BNY

Jersey City, NJ 07306

New, Posted 6 hours ago

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Sr. Database Engineer, SQL Server

Disney Entertainment and ESPN Product & Technology Careers

New York, NY 10025

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Photonics manufacturing engineer

Coherent

Budd Lake, NJ 07828

~ 40 min Onsite

Bachelor's degree in Optical Engineering, Electrical Engineering, or a related field with 5+ years of experience, or a master's degree or higher.
Experience in manufacturing engineering, particularly with optical systems and components.
Experience working in a cleanroom environment.
Proficiency with CAD software (e.g., SolidWorks) and strong knowledge of manufacturing processes.
Experience with lasers, optical components, and related test equipment.

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New Product Manufacturing Engineer

CACI International Inc

Florham Park, NJ 07932

~ 30 min Onsite

Ability to work independently with minimal supervision and mentor lower-level professionals.
Must be a US person.
BA/BS degree in a technical discipline from an accredited college or university.
Minimum of five (5) years of experience as a manufacturing engineer or in a related role.
Percentage of Travel Required: Up to 10%
Type of Travel: Local

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Chief Engineer

Ace Hotel New York

New York, NY 10001

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Manufacturing Engineer

Whippany Actuation Systems

Whippany, NJ 07981

$90,000-$110,000/yr

~ 27 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

A bachelor's degree in manufacturing, Aerospace, or Mechanical Engineering from an accredited university or college;
One year of experience in a manufacturing environment which includes interpreting blueprints and familiarity with GD&T;
Previous experience with CAD systems;

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Principal Engineer - Python API Development

Fidelity Investments

Harrison, NJ 07029

~ 31 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.