662 Ai Engineer Mainframe Modernization jobs in New York,NY

New, Posted 4 hours ago

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Sr. Data Engineer

Subway Restaurants

Southport, CT 06890

$119,200-$149,000/yr

~ 1 hr 5 min OnsiteEducation AssistanceHealth InsuranceRetirement Benefit

Bachelor's degree in Computer or Information Science or related field, or equivalent combination of education and experience
5–8 years creating quality data pipelines and system integrations
At least 3 years of experience in a cloud environment
Hands-on experience building lakehouse solutions on Databricks (Delta Lake, Unity Catalog) or Snowflake (Iceberg Tables, Horizon Catalog)
Proven ability to design Bronze/Silver/Gold layers for curated, analytics-ready data
Experience implementing Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake Dynamic Tables / Snowpipe Streaming
Experience building and managing semantic models using Databricks AI/BI Genie or Unity Catalog Metrics or Snowflake Semantic Views / Cortex Analyst
Building pipelines with Airflow, Databricks Lakeflow, or Snowflake Openflow; familiarity with dbt is a plus
Strong PySpark or advanced SQL skills; Python for data engineering or automation
Dimensional modeling, Data Vault, or schema design for analytical workloads
Cluster/warehouse sizing, partitioning, clustering keys, Z-ordering, or query optimization
Working knowledge of Unity Catalog (Databricks) or Horizon Catalog (Snowflake) for lineage, access control, or data quality
Git, Databricks Asset Bundles or Snowflake CLI/Schemachange, automated testing, or deployment pipelines
AWS (S3, Glue, Kinesis), Azure, or GCP services supporting modern data platforms
Familiarity with Databricks Mosaic AI or Snowflake Cortex for GenAI or ML use cases
Strong communication skills to partner with Product Owners, Analysts, or cross-functional engineering teams
Authorized to work in the country the position is based

SmartExplore AI is experimental.

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Manufacturing Engineer

Whippany Actuation Systems

Whippany, NJ 07981

$90,000-$110,000/yr

~ 50 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

A bachelor's degree in manufacturing, Aerospace, or Mechanical Engineering from an accredited university or college;
One year of experience in a manufacturing environment which includes interpreting blueprints and familiarity with GD&T;
Previous experience with CAD systems;

SmartExplore AI is experimental.

New, Posted 4 hours ago

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Sr. Data Engineer

Subway Restaurants

Wilton, CT 06897

$119,200-$149,000/yr

~ 1 hr 8 min OnsiteEducation AssistanceHealth InsuranceRetirement Benefit

Bachelor's degree in Computer or Information Science or related field, or equivalent combination of education and experience
5–8 years creating quality data pipelines and system integrations
At least 3 years of experience in a cloud environment
Hands-on experience building lakehouse solutions on Databricks (Delta Lake, Unity Catalog) or Snowflake (Iceberg Tables, Horizon Catalog)
Proven ability to design Bronze/Silver/Gold layers for curated, analytics-ready data
Experience implementing Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake Dynamic Tables / Snowpipe Streaming
Experience building and managing semantic models using Databricks AI/BI Genie or Unity Catalog Metrics or Snowflake Semantic Views / Cortex Analyst
Building pipelines with Airflow, Databricks Lakeflow, or Snowflake Openflow; familiarity with dbt is a plus
Strong PySpark or advanced SQL skills; Python for data engineering or automation
Dimensional modeling, Data Vault, or schema design for analytical workloads
Cluster/warehouse sizing, partitioning, clustering keys, Z-ordering, or query optimization
Working knowledge of Unity Catalog (Databricks) or Horizon Catalog (Snowflake) for lineage, access control, or data quality
Git, Databricks Asset Bundles or Snowflake CLI/Schemachange, automated testing, or deployment pipelines
AWS (S3, Glue, Kinesis), Azure, or GCP services supporting modern data platforms
Familiarity with Databricks Mosaic AI or Snowflake Cortex for GenAI or ML use cases
Strong communication skills to partner with Product Owners, Analysts, or cross-functional engineering teams
Authorized to work in the country the position is based

SmartExplore AI is experimental.

New, Posted 1 day ago

Recommended

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

Capital One

New York, NY 10001

New, Posted 1 day ago

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Sr Software Engineer - AI and Observability

Disney Entertainment and ESPN Product & Technology Careers

New York, NY 10025

$148,700-$199,400/yr

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Project Engineer

Oerlikon Surface Solutions

Westbury, NY 11590

$75,000-$100,000/yr

~ 40 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's degree in materials science or mechanical engineering
3 years job experience in thermal spray or PVD coating technologies
Must be proficient in using business and communications software (preferably Word, Excel, PowerPoint, common Windows operating systems, and Outlook)
Ability to travel 30% travel may be required
Work Location: In person

SmartExplore AI is experimental.

Recommended

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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.

SmartExplore AI is experimental.

New, Posted 1 day ago

Recommended

Software Engineer II - AI and Observability

Disney Entertainment and ESPN Product & Technology Careers

New York, NY 10025

$117,500-$157,500/yr

Recommended

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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.