671 Ai Data Engineering Manager jobs in New York,NY

Head of AI Data Science, Intelligence Ventures

Spectrum

New York, NY 10036

OnsiteUrgently Hiring

Deep expertise in transformer-based sequence modeling and its application to behavioral or interaction data at consumer scale — including architecture design, training methodology, fine-tuning, and embedding quality evaluation
Proven track record developing and deploying household- or user-level embedding models applied to real-world use cases in media, marketing, commerce, and/or customer intelligence — not just research environments. Demonstrated understanding of the unique characteristics of behavioral sequence data: sparsity, temporal dynamics, multi-entity structure, and the signal differences between behavioral intent and explicit interaction
Strong command of the full data science lifecycle in production settings — from exploratory data analysis and feature engineering through model training, validation, deployment, monitoring, and iteration — at large dataset scale (billions, even trillions of records)
Hands-on proficiency with Python, PyTorch or TensorFlow, and distributed ML training frameworks; experience running ML workloads on cloud platforms (AWS SageMaker, Snowflake Cortex, Databricks, or equivalent)
Experience designing and operationalizing feature stores and predictive modeling pipelines that serve downstream intelligence products, audiences, or decision systems in production environments
Ability to communicate complex AI/ML concepts clearly to non-technical executive audiences, product stakeholders, and external partners; comfort operating as an external-facing technical spokesperson for the platform's modeling capabilities and intelligence differentiation
Track record of leading and growing high-performing data science teams; experience recruiting and developing senior ML talent in competitive markets
Genuine intellectual curiosity about the application of AI to behavioral science, consumer intelligence, and agentic systems; awareness of the evolving landscape of foundation models, retrieval-augmented generation, and multi-agent AI architectures
Bachelor's Degree in Computer Science, Statistics, Mathematics, or a related quantitative field
Experience leading applied ML or data science teams building consumer-facing or enterprise intelligence products — 7 years
Hands-on experience designing and training transformer or deep learning models on sequential behavioral data at scale — 5 years
In-office position preferably based in New York City
Travel as required for partner engagements, executive meetings, and industry events

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Senior Vice President, Infrastructure Engineer

BNY

Jersey City, NJ 07306

Urgently Hiring

New, Posted 1 day 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.

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

Capital One

New York, NY 10001

New, Posted 20 hours ago

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Senior Vice President, Forward Deployed Engineer

BNY

New York, NY 10007

$104,000-$210,000/yr

New, Posted 5 hours ago

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Software Engineer II - AI and Observability

Disney Entertainment and ESPN Product & Technology Careers

New York, NY 10025

$117,500-$157,500/yr

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Head of AlphaGen - Investor Research Product Engineering, Director

Blackrock

New York, NY 10025

OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's degree in Computer Science, Engineering, or a related field; or equivalent practical experience
An advanced degree is a plus
Strategic Engineering Leadership: Proven experience leading large-scale engineering organizations through product transformation initiatives (e.g., platform modernization, cloud migration, operating model changes). Demonstrated success in setting vision and executing across complex, multi-year technology programs
Alpha generation workflows or closely related quantitative research processes in finance/investments
Cloud technologies and cloud-native architectural patterns (e.g., microservices, containerization, distributed computing e.g. Ray)
API-first platform design and developer experience best practices
AI/ML applications for workflow automation, data validation, and operational excellence
Modern stack knowledge and skills - e.g. Python, Polars, Ray, MLFlow or equivalent technology
Demonstrated strength in partnership-building and cross-functional collaboration
Able to influence and align product teams, platform/infrastructure teams, and governance bodies around a common vision and roadmap
Ability to operate in complex market and organizational contexts, translating strategic objectives into actionable plans
Proven track record of driving innovation, navigating ambiguity, and delivering measurable outcomes at scale
AI-First, Human-in-the-Loop: Embraces AI-driven solutions as a default for efficiency and scale, while keeping expert human judgment in critical loops to ensure quality and trust
Platform Over People: Prioritizes building robust platforms and automation over relying on individual heroic efforts, enabling sustainable and scalable growth
Single Front Door: Advocates for a unified user experience where researchers and stakeholders have one intuitive portal for all their needs, simplifying access and support
Standardization Everywhere: Drives consistency in tools, processes, and data across the board, reducing complexity and improving interoperability and maintainability
Self-Service as the Default: Champions self-service capabilities, empowering users to accomplish tasks independently (from data ingestion to model deployment) without bespoke engineering work
Deep Co-Ownership with PMG: Fosters a culture of partnership with the Portfolio Management Group, aligning closely on priorities, sharing roadmaps and KPIs, and co-owning outcomes to ensure the platform truly meets investment teams' needs
For New York, NY Only the salary range for this position is USD$225,000.00 - USD$285,000.00
Additionally, employees are eligible for an annual discretionary bonus, and benefits including healthcare, leave benefits, and retirement benefits
BlackRock operates a pay-for-performance compensation philosophy and your total compensation may vary based on role, location, and firm, department and individual performance
4 days in the office per week, with the flexibility to work from home 1 day a week

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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

New, Posted 6 hours ago

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Head of Product Management – Intelligence Ventures

Spectrum

New York, NY 10036

Onsite

Bachelor's Degree in Business, Computer Science, Engineering, Economics, or a related field
10+ years Product management leadership experience for data, intelligence, SaaS, or platform products
5+ years Hands-on product leadership, including directly owning products and building or leading a small, senior team
Deep expertise in product management for data, intelligence, or platform products built on AI/ML systems, with the ability to turn embeddings, features, and scores into successful commercial offerings
Proven success owning the full product lifecycle for technical and business-facing products, including APIs, feeds, SDKs, dashboards, and insights tools
Experience building and packaging data products across APIs, feeds, clean rooms, zero-copy platforms, and audience/activation products, with strong commercial and developer-experience instincts
Strong product strategy and commercial acumen, including pricing, packaging, tiering, business cases, and prioritizing investments across markets and revenue streams
Deep market fluency in adtech, martech, data, measurement, identity, clean rooms, DSPs/SSPs, and retail media, with the ability to translate market feedback into product decisions
Skilled at communicating complex AI/ML and data concepts to executives and partners, with a strong grasp of privacy-preserving data products, governance, and regulatory considerations
Comfortable as a hands-on, player-coach leader in a lean, early-stage environment, with the ability to build teams, navigate ambiguity, and deliver against ambitious goals
Strong interest in agentic AI and emerging intelligence-product interfaces, including AI-ready APIs, retrieval-grounded experiences, and multi-agent workflows
Ability to serve as a visionary leader, think strategically, and anticipate future needs and trends with respect to relevant technologies
Ability to lead large change, complex projects and initiatives, foster teamwork, and build a strong culture of collaboration

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