Machine Learning Platform

Machine Learning Platform Engineer Jobs

3 jobs found

Today

Machine Learning Engineer, Advertising & Marketing Performance Intelligence

Amazon.com Services LLC Seattle, WA

Seattle, WA

Today

$144k - $194k/yr Full time Marketing Agentic Ai Ai Agent

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Job Description

Amazon’s Advertising & Marketing Performance Intelligence (AMPI) team is hiring a Machine Learning Engineer to develop, deploy, and scale production-grade machine learning and GenAI solutions. This onsite role in Seattle focuses on building ML infrastructure and enabling automated decision-making and personalized marketing communications.

Role Responsibilities

Partner with Data and Applied Scientists to process structured and unstructured data inputs, scaling ML and LLM infrastructure for production while optimizing infrastructure costs, GPU utilization, memory management, and training workflows.
Work on production training approaches such as offloading optimizer states and massive parallelization to support production environments.
Build and deliver reusable technical assets that accelerate adoption of ML, Optimization, and GenAI across multiple science initiatives.
Design and maintain production-grade, large-scale distributed training systems for ML, Causal, GenAI, and multi-modal foundation models.
Optimize AWS AI/ML infrastructure to improve cost efficiency, GPU utilization, latency, training cost, and fine-tuning performance on massive datasets.
Create robust monitoring and debugging tooling to support reliability and performance of training workflows, including piloting LLMs and diagnosing system issues.
Collaborate with Engineers, Data, and Applied Scientists to evaluate design approaches, prototype new GenAI and ML models, assess technical feasibility, and resolve complex problems.

Required Qualifications

3+ years of non-internship professional software development experience.
2+ years of non-internship design or architecture experience for new and existing systems, including design patterns, reliability, and scaling.
Experience programming with at least one software programming language.
Experience in machine learning, data mining, information retrieval, statistics, or natural language processing.

Technologies and Tools

Machine Learning; large language models (LLMs); large quantitative models (LQMs)
AI/ML workflows and distributed training systems
AWS Bedrock; Amazon Q; SageMaker
Agentic AI (RAG, agentic architectures, vector databases)
Containerized deployments
Hugging Face; LangChain
Guardrail implementations
Foundational models such as Qwen, Anthropic Claude, Mistral
RCTs

Preferred Qualifications

3+ years of full software development life cycle experience, including coding standards, code reviews, source control management, build processes, testing, and operations.
Bachelor’s degree in computer science or equivalent.
1+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization, or search.

Compensation and Location

Location: Seattle, WA (onsite).
Salary: USD 143,700 - 194,400 per year.

Benefits

Sign-on payments
Restricted stock units (RSUs)
Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
401(k) matching
Paid time off
Parental leave

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Today

Machine Learning Engineer 5 (IC)

Capital One New York, NY

New York, NY

Today

$251k - $286k/yr Full time Backend Developer Ai Ml Artificial Intelligence

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Job Description

Capital One is building and scaling production-grade AI and machine learning systems, and this Machine Learning Engineer IC role supports that mission in an onsite position in New York, NY. You will design and deliver ML models and the platforms, data pipelines, and responsible AI practices needed to run them reliably at scale.

Role focus

The work centers on taking ML from model development to production operations. You will collaborate with Product and Data Science teams to build multi-tenant training and serving capabilities, automate deployment, and retrain, maintain, and monitor models. The role also emphasizes using cloud architectures and engineering best practices to optimize performance while keeping governance and Responsible and Explainable AI standards in view.

Responsibilities

Design, build, and/or deliver ML models and components that address real-world business problems with Product and Data Science teams
Build and scale massive multi-tenant platforms for large-footprint ML model training and/or serving
Guide ML infrastructure decisions using expertise in model selection, data and feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation
Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
Collaborate in a cross-functional Agile team to create and improve software for big data and ML applications
Retrain, maintain, and monitor models in production
Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale
Construct optimized data pipelines to feed ML models
Apply CI/CD best practices, including test automation and monitoring, to support successful deployment
Ensure code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and ML follows best practices in Responsible and Explainable AI
Use programming languages such as Python, Scala, or Java

Requirements

Bachelor’s Degree or higher in Computer Science, Machine Learning, or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
At least 6 years of experience programming with Python, Java, Golang, or C++
At least 6 years of Machine Learning experience using PyTorch or TensorFlow and libraries including Pandas, NumPy, Scikit-learn
At least 6 years using and operating large-scale distributed systems (including Spark and Ray) to prepare AI/ML data
At least 4 years deploying and operating ML solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large-scale containerized ML systems

Technologies

Python, Scala, Java, Golang, C++
PyTorch, Tensorflow, Pandas, NumPy, Scikit-learn
Spark, Ray
AWS, GCP, Azure, Kubernetes
CI/CD

Benefits

Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits supporting total well-being
Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)

Preferred qualifications

Master’s or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field
5+ years optimizing ML algorithms, configurations, and infrastructure
5+ years following software development best practices including source control, testing, code reviews, and CI/CD
5+ years building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans
5+ years working with ML techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.), model types (Regression, Classification, Clustering, etc.), model architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and evaluating model accuracy while diagnosing underfitting/overfitting
5+ years designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences

Compensation

USD 250,800 - 286,200 per year for New York, NY (Machine Learning Engineer 5). The role is at the IC level 5.

Additional employment and application details

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position
Applications are expected to accept for a minimum of 5 business days
No agencies please
Equal Opportunity Employer (EOE, including disability/vet) committed to non-discrimination
Capital One promotes a drug-free workplace
If accommodations are needed when visiting the website to apply, contact Capital One Recruiting at 1-800-304-9102 or RecruitingAccommodation@capitalone.com
For technical support or questions about recruiting, email Careers@capitalone.com
Capital One does not provide, endorse, or guarantee third-party products, services, educational tools, or other information available through this site

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Today

Machine Learning Engineer II

Amazon.com Services LLC Seattle, WA

Seattle, WA

Today

$144k - $194k/yr Full time Ai Ml Artificial Intelligence Data Pipeline

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Job Description

As a Machine Learning Engineer II on Amazon’s MusicIQ team, you will design and evolve scalable, high-performance machine learning systems that support content intelligence and catalog serving. The role emphasizes building ML infrastructure, moving models into production, and enabling both offline processing and real-time customer experiences.

Responsibilities

Improve core machine learning infrastructure for tagging music content and enhance music similarity capabilities.
Work with research scientists to deploy scalable machine learning models to production, improving model performance and overall architecture.
Explore and validate design approaches by prototyping new technologies and assessing technical feasibility, including options such as AutoML and real-time model serving systems.
Partner with scientists to design and build data pipelines capable of processing massive datasets and scaling machine learning models.
Create and maintain platforms and services that support the end-to-end workflow for building, evaluating, and deploying machine learning models for real-world applications.

Requirements

3+ years of non-internship professional software development experience.
2+ years of non-internship experience designing or architecting new and existing systems, including design patterns and reliability and scaling.
1+ years of software development engineer or related occupational experience.
1+ years of experience designing and developing large-scale, multi-tiered, multi-threaded, embedded, or distributed applications, tools, systems, and services using C#, C++, Java, or Perl.
1+ years of Object Oriented Design experience.
Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field.
Experience programming with at least one software programming language.
3+ years of full software development life cycle experience, including coding standards, code reviews, source control management, build processes, testing, and operations.
Bachelor's degree in computer science or equivalent.

Technologies

C#
C++
Java
Perl

Location

Seattle, WA (onsite)

Compensation

USD 143,700 - 194,400 per year

Benefits

Sign-on payments
Restricted stock units (RSUs)
Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
401(k) matching
Paid time off
Parental leave

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Machine Learning Platform Engineer Jobs

Machine Learning Engineer, Advertising & Marketing Performance Intelligence

Machine Learning Engineer 5 (IC)

Machine Learning Engineer II

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