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Software Engineer Python C Front Office

New York,NY

2184 Software Engineer Python C Front Office jobs in New York,NY

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New York, NY 10279

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Software Engineer II - Infrastructure

Disney Entertainment and ESPN Product & Technology Careers

New York, NY 10025

$117,500-$157,500/yr
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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.
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New, Posted 20 hours 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 9 hours ago
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Head of Technology, Intelligence Ventures

Spectrum

New York, NY 10036

Onsite

  • Deep expertise across the full intelligence platform stack — including distributed data pipelines, ML platform architecture, embedding systems, feature stores, agent-to-agent API design, and LLM-powered application layers — with demonstrated ability to architect and ship all layers as a coherent, production-grade product
  • Demonstrated experience architecting and operating consumer data intelligence or data product platforms underpinned by complex machine learning systems and built on modern, cloud-native data infrastructure
  • Hands-on proficiency with Snowflake (including Cortex, Native Apps, and data sharing frameworks), cloud data platforms (AWS, Azure, or GCP), and production ML/AI systems at scale
  • Experience building agentic AI systems and LLM-powered product interfaces — including agent-to-agent APIs, retrieval-augmented generation architectures, and natural language UIs grounded in proprietary data — with strong product instincts around accuracy, trust, and user experience for non-technical enterprise audiences
  • Proven ability to translate complex technical architecture into clear executive and partner-facing communications; comfortable engaging at the C-suite level and in strategic partner negotiations with hyperscalers and technology platforms
  • Strong understanding of privacy-preserving data architecture, including differential privacy, de-identification techniques, zero-copy and clean room frameworks, and the regulatory landscape governing consumer behavioral data
  • Track record of recruiting and developing exceptional engineering talent in competitive markets; experience building high-performance teams from early-stage through scaled operations
  • Experience managing external development partners and outsourced engineering resources alongside an internal team in a fast-moving, build-from-scratch environment
  • Ability to operate in an ambiguous, early-stage environment while maintaining rigorous engineering standards and delivering against aggressive milestones
  • Experience building externally-consumed data or intelligence platforms — including developer-facing APIs, data marketplace integrations, or partner-accessible data products — with strong instincts around developer experience, access governance, and commercial platform design
  • Bachelor's Degree in Computer Science, Software Engineering, Electrical Engineering, or a related technical field
  • Experience leading consumer data intelligence, AI/ML platform, or data product engineering organizations — 10 years
  • Engineering leadership and team-building experience, including managing senior technical staff — 7 years
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New York, NY 10279

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Senior Test Engineering Technician - AI Data Center Systems (Servers & GPUs)

Advanced Micro Devices

Secaucus, NJ 07094

~ 18 min Onsite

  • Ability to lift up to 35 pounds, safely climb ladders, wear personal protective and ESD gear correctly, and stand and walk throughout the facility for extended periods without loss or reduction of productivity.
  • CompTIA A+ or equivalent experience.
  • CompTIA Server+ or equivalent experience.
  • Windows OS experience.
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Machine Learning Engineer

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New York, NY 10001

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