618 Qa Api Automation Engineer jobs in New York,NY

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Quality Assurance Specialist

the fedcap group

New York, NY 10017

$66,300-$75,000/yr

OnsiteBilingual Preferred

A bachelor's degree in a related discipline required.
3-5 years' experience in Quality Assurance, monitoring, and/or Compliance experience in a similar role.
Experience with Continuous Quality Improvement frameworks and instruments.
Experience in accurate electronic data analysis and QA.
Prior experience responding to external audit reports and preparing corrective action plans.
Experience in developing and implementing processes for continual quality improvement.

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Quality Assurance Technician M/F

Safran

New York, NY 10025

$25-$30/hr

Onsite

Minimum of 2yrs experience in quality assurance or related role, preferably in electronics manufacturing
Familiarity with quality management systems and tools (ISO9001)
Experience in documentation and reporting on Quality Metrics
Associate Degree
More than 3 years
ITAR Controlled Position: Yes

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Quality Assurance Tech

Mercury Systems

Caldwell, NJ 07006

~ 43 min Onsite

Typically requires a minimum of three years of quality assurance experience.
High School diploma or General Education Degree (GED).
Previous ISO 17025 experience.
Previous AS9102 First article inspection experience.
Previous AS9100 Quality Management Standard experience.
Previous IPC-A-610 and IPC-J-STD-001 training and/or certification.
Experience with electrical and mechanical inspection tools.
Ability to work under a microscope as needed.
Ability to work overtime as needed.
Ability to travel between West Caldwell & Saddle River, NJ sites.
Must currently have or be eligible to obtain a DoD Secret clearance.
"This position requires you to have or obtain a government security clearance. Security clearances may only be granted to U.S. citizens."

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Principal Engineer - Python API Development

Fidelity Investments

Lyndhurst, NJ 07071

~ 23 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.

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Quality Control Engineer III (Hybrid - New York, NY)

Energy Solutions

New York, NY 10279

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Principal Engineer - Python API Development

Fidelity Investments

Harrison, NJ 07029

~ 23 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.

New, Posted 10 hours ago

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Cabinet Manufacturing Machine Operator (Night Shift)

FABUWOOD CABINETRY

Newark, NJ 07105

~ 28 min OnsiteUrgently HiringBilingual PreferredHealth InsurancePaid Time OffRetirement Benefit

Previous experience operating manufacturing machinery or industrial equipment strongly preferred.
Basic mechanical aptitude with the ability to perform minor troubleshooting.
Strong attention to detail and commitment to product quality.
Ability to read and follow written Standard Operating Procedures (SOPs).
Reliable, self-motivated, and able to work independently during the night shift.
English proficiency required; Spanish is a plus but not required.

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Senior Vice President, Forward Deployed Engineer

BNY

New York, NY 10007

$104,000-$210,000/yr

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Manufacturing Engineering Manager - Boonton, NJ

Hubbell Incorporated

Boonton, NJ 07005

~ 49 min Onsite

BS in Electrical, Industrial, Mechanical Engineering or similar
5+ years experience in an Electronics, Electro-Mechanical, or relevant manufacturing environment
Proven track record for handling new product launches through PFMEA assembly line creation, ERP setup work etc.
Proven track record of conceptualizing and implementing Test automation framework on the manufacturing floor to reduce takt times and improve process quality,
Must be fluent with mechanical 3D CAD package.
Must be able to read schematics to troubleshoot board level issues
Experience with Electronics and manufacturing of Printed Circuit Board (PCB) Assemblies.
Must possess excellent verbal and written communications skills
An understanding of lean tools and concepts is essential, i.e. time studies, kaizen events, Value Stream Maps, etc
A continuous improvement mindset is critical
Must be familiar with ISO 9000

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Quality Manager - Manufacturing

Versa Products Company

Paramus, NJ 07652

~ 29 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's Degree in Engineering, Business Administration, or related field preferred
Minimum of 5 years of experience in quality management within a manufacturing environment
Minimum of 5 years of leadership experience managing teams
Strong knowledge of:
Quality Management Systems (QMS)
ISO 9001 standards
ERP systems
Mechanical component inspection
Continuous improvement methodologies (Lean, Six Sigma)
Lean Six Sigma Green Belt or Black Belt strongly preferred
Hands-on experience with precision inspection tools (calipers, CMM, Keyence, etc.)
Ability to define problems, collect data, and draw valid conclusions.
Ability to interpret technical instructions, drawings, and specifications.
Strong attention to detail with a bias for action and results.
Ability to work effectively in a dynamic manufacturing environment.
Adaptability in situations involving change, ambiguity, and competing priorities.