736 Software Engineer Python Hadoop jobs in New York,NY

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.

SmartExplore AI is experimental.

New, Posted 5 hours ago

Recommended

Software Engineer II - Ad Platform, CRM Analytics

Disney Entertainment and ESPN Product & Technology Careers

New York, NY 10025

New, Posted 1 day ago

Apply Directly

Senior Vice President, Infrastructure Engineer

BNY

New York, NY 10007

Urgently Hiring

New, Posted 1 day ago

Recommended

Apply Directly

Principal Engineer - Python API Development

Fidelity Investments

Weehawken, NJ 07086

~ 12 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 5 hours ago

Recommended

Software Engineer II - Infrastructure

Disney Entertainment and ESPN Product & Technology Careers

New York, NY 10025

$117,500-$157,500/yr

Apply Directly

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

SmartExplore AI is experimental.

Head of Engineering for Wealth Management

MassMutual

New York, NY 10025

Onsite

15+ years of progressive technology leadership experience, including leadership of large-scale software engineering organizations.
Experience leading organizations of 75+ engineers across multiple disciplines and geographic locations.
Proven track record modernizing enterprise platforms through cloud-native architectures, microservices, APIs, and event-driven systems.
Deep experience delivering customer-facing platforms in wealth management, capital markets, banking, fintech, retirement, or financial services.
Demonstrated success partnering with executive stakeholders to align technology investments with business outcomes.
Experience managing large-scale digital transformation initiatives with measurable business impact.
Must have Series 99 or ability to obtain it within 6 months.

SmartExplore AI is experimental.

New, Posted 1 day ago

Recommended

ZipRecruiter

Scientist 4 - Informatics (Python & SQL) SK71741

TechData Service Company LLC

Summit, NJ 07901

$63/hr

ResumeLibrary

Senior AWS Redshift Data Engineer (Contract | 1099)

BrainTrust

New York, NY 10001

New, Posted 23 hours ago

Recommended

Apply Directly

AML Compliance Model Developer – Associate

Santander Holdings USA

New York, NY 10012

Onsite

Bachelor's degree in computer science, Information Systems, Data Analytics, Finance, Mathematics, or related field
3–5 years of experience in AML Compliance Technology, AML model development, or a related field within banking or financial services
Strong programming and analytical experience using SAS for data analysis, reporting, model support, and testing
Good working knowledge of Python for data manipulation, scripting, automation, and analytical processing
Strong SQL skills with experience developing complex queries, joins, procedures, and handling large-scale datasets
Experience working with Jira for Agile project tracking, sprint management, and defect lifecycle management
Working knowledge of testing methodologies including functional testing, regression testing, SIT, and UAT
Understanding of AML regulations and compliance frameworks including BSA/AML, OFAC, KYC, and transaction monitoring concepts
Strong analytical, quantitative, and problem-solving skills
Ability to multitask, manage priorities, and work effectively in fast-paced environments
Strong communication, documentation, and stakeholder management skills
Applicants must be legally authorized to work in the United States on a full-time basis without requiring employer sponsorship to commence employment

SmartExplore AI is experimental.