1010 Ml Systems Engineer Infrastructure Cloud jobs in New York,NY

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AI Engineer

Capital One

New York, NY 10001

New, Posted 21 hours ago

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Principal Quant Developer (MLOps)

Fidelity Investments

Jersey City, NJ 07305

~ 22 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

A Bachelor's degree in Computer Science, Financial Engineering, Information Technology, Information Systems, Mathematics, Physics, Statistics, Engineering, or a closely related field and six (6) years of experience as a Senior Quant Developer or similar role.
Alternatively, a Master's degree (or equivalent foreign education) in the same fields, accompanied by four (4) years of experience as a Lead Quantitative Development or similar role.
This experience should include building high-quality, robust, and efficient systems and solutions for financial investment decisions, utilizing R, Python, PL/SQL databases, and quantitative techniques.
Expert in Python with experience across the development stack (full stack)
Exposure to object-oriented programming (OOP) and design patterns
Experience in at least one unit testing framework and understanding of test-driven development (TDD) concepts and methodologies
A commitment to writing clean, maintainable, and efficient code, with best practices for long-term maintainability
Skilled in a range of database technologies: SQL (Oracle & Snowflake), NoSQL, Graph
Skilled in batch and API technologies: such as batch scheduling (using Autosys and Airflow) and creating REST APIs (using FAST API and Flask)
Proven ability to construct and manage robust data pipelines and event-driven workflows
Proven expertise in system design and cloud architecture on AWS, leveraging resources including Lambda, S3, EKS, and EC2
Experience in containerization with Docker and orchestration with Kubernetes
Implement CI/CD pipelines (using Linux and Jenkins), code versioning using GitHub
Experience in Infrastructure as Code methodologies for consistent and scalable infrastructure management
Experience operationalizing machine learning models on AWS, including services such as SageMaker (training, deployment, model registry, monitoring) and Bedrock (foundation model access and fine-tuning)
Operationalizing AI/ML pipelines using modern MLOps principles, including production lifecycle management of AI models
Familiarity with experiment tracking and model versioning tools (e.g., MLflow)
Identifying and deploying applied ML solutions relevant to quantitative investing: time series forecasting, anomaly detection, NLP, and predictive analytics
Awareness of responsible AI governance practices
Demonstrated enthusiasm for contributing to all facets of our AI ecosystem, from application development to MLOps/LLMOps infrastructure, with a versatile, full-stack engineering mindset
Demonstrated knowledge of mathematics, statistics, and quantitative finance
Deep understanding of quantitative techniques and methods, statistics and econometrics including probability, linear regression and time series data analysis
Analyze and design systems to implement quantitative models for systematic financial investments using R and Python, including time series forecasting models, multi-asset class portfolio construction strategies, risk management tools, alpha research, and simulation-based algorithms
Domain knowledge in either equities, fixed income or alternative asset classes
Progress towards CFA (or equivalent) a plus

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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

SmartExplore AI is experimental.

New, Posted just now

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Solution Architect

KPMG

New York, NY 10001

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Systems Analyst – Enterprise Automation

MassMutual

New York, NY 10012

Onsite

Bachelor's degree in Computer science, engineering or other applicable discipline
8+ years of experience in business analysis, process improvement, automation, or digital transformation roles.
5+ years of experience working with Robotic Process Automation (RPA) platforms (e.g., UiPath or similar)

SmartExplore AI is experimental.

Head of AI Data Science, Intelligence Ventures

Spectrum Careers

New York, NY 10025

New, Posted 19 hours ago

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Staff Backend Engineer, Customer Value Optimisation

HelloFresh

New York, NY 10025

New, Posted just now

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Sr. Software Development Engineer, Bedrock AgentCore Knowledge Bases

Amazon.com Services LLC

New York, NY 10261

New, Posted 1 hour ago

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CIB, Structured Finance Associate - Infrastructure

Santander Holdings USA

New York, NY 10022

Onsite

Bachelor's Degree or equivalent work experience in Finance, Business, Accounting, Engineering, or Economics or equivalent work experience
3+ years of relevant professional work experience
Between 1-3+ years of experience in banking or finance industry with strong credit analysis experience. Exposure in infrastructure, real estate, renewable or digital/AI infrastructure debt or equity transactions is preferred but not required depending on credit analysis or prior project finance experience.
Significant experience in the analysis and structuring of highly complex transactions, including project-oriented financings
Must have exposure to analyzing and negotiating transaction documents
Must have detailed direct experience of modelling and execution project financing transactions
Ability to travel as required
Strong credit and risk analysis skills
Strong analytical / problem solving skills
Strong relationship management and negotiation skills
Excellent written and verbal communications skills
Superior organizational and time management skills with the ability to efficiently work on several priorities at a time
Ability to work independently and in a fast-paced environment with little supervision
Proficiency in Microsoft office products - Word, Excel and Outlook.

SmartExplore AI is experimental.

New, Posted 5 hours ago

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