694 Ap Computer Science Principles Tutor jobs in New York,NY

Exceptional NYC-based Dyslexia Tutor (Orton-Gillingham) - part-time

The Reading Guru

New York, NY 10001

$113/hr

OnsiteFlexible Schedule

MUST HAVE significant multisensory Orton Gillingham-based training (i.e. AOGPE, Wilson, Barton, Lindamood Bell, IMSE, Lexercise, etc.)
Minimum of one year experience teaching OG lessons one-on-one, in a small group, or classroom setting
At least one year of experience working with dyslexic students
Four-year college degree
Must live in the NYC area or be able to travel to NYC easily at least twice a week
Willingness to submit to a background check
Must be available to tutor either during the afternoons and evenings or on the weekends

SmartExplore AI is experimental.

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Clinical Laboratory Scientist

United States Army

Newark, NJ 07104

New, Posted 1 day ago

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Director - Life Sciences Advisory - Commercial

Guidehouse Careers

New York, NY 10025

New, Posted 1 day ago

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Business Development Manager, STEM Partnerships

Liberty Science Center

Jersey City, NJ 07305

~ 22 min OnsiteHealth InsurancePaid Time OffRetirement Benefit

Valid driver's license (required)
8 hours per day, Monday through Friday, with flexibility for evenings and weekends as needed to meet business requirements
Travel to partner sites and conferences will be required
Ability to drive is a requirement
Travel to conferences, meetings, and partner sites to observe off-site programming will be required

SmartExplore AI is experimental.

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Environmental Science Officer

United States Army

Elizabeth, NJ 07202

New, Posted 1 day ago

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Lead Software Engineer - Data Streaming/Integration Platforms

Disney Entertainment and ESPN Product & Technology Careers

New York, NY 10025

$155,700-$208,700/yr

New, Posted 1 day ago

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Lead AI Engineer (AI Foundations, LLM Core and Agentic AI)

Capital One

New York, NY 10001

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Principal Engineer - Python API Development

Fidelity Investments

Jersey City, NJ 07311

~ 22 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.