3595 Net Software Developer Human Resources jobs in New York,NY

Bachelor's degree/equivalent in engineering, data analytics, computer software or related technical or quantitative discipline.
Five (5) years experience in data analytics, data management and/or engineering
Excellent analytical, problem solving, presentation, project management, SQL, data analytics tools (e.g. SAS), data visualization tools (e.g., Tableau, SAS VA, Spotfire)
Excellent human relations, organizational/time management and communication skills.

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Software JOB Training Program

Year Up United

New York, NY 10261

$525/wk

Onsite

A high school graduate or GED recipient
Eligible to work in the U. S.
Have not obtained a Bachelor's degree

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User Experience Designer

Adecco

New York, NY 10025

$79.81/hr

HybridHealth InsurancePaid Time OffRetirement Benefit

Bachelor's degree in Design, Human-Computer Interaction (HCI), Interaction Design, UX Design, Graphic Design, or a related field, or equivalent practical experience.
4+ years of experience in Product Design, UX Design, or related role.
4+ years of experience using design and prototyping tools such as Figma.
4+ years of experience collaborating with Product Management, Engineering, and Business stakeholders.
4+ years of experience working within established design systems and design standards.
Experience designing data-intensive, workflow-driven, or complex enterprise applications.
Experience working within highly regulated environments such as Financial Services, Banking, Healthcare, Insurance, or similar industries.
Strong portfolio showcasing design process, problem-solving approach, outcomes, and measurable impact.

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Technical Project Manager

Kaav

New York, NY 10001

New, Posted 16 hours ago

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Principal Engineer - Python API Development

Fidelity Investments

Hoboken, NJ 07030

~ 16 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.