PyTorch

PyTorch Engineer Jobs

48 jobs found

Today

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

Capital One New York, NY

New York, NY

Today

$211k - $241k/yr Full time Agentic Ai AI Ai Ml

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Job Description

Capital One is seeking a Lead AI Engineer to advance AI Foundations, LLM Core and Agentic AI within the Intelligent Foundations and Experiences (IFX) team in New York, NY. This onsite role offers a salary range of USD 211,000 to 240,800 per year and focuses on delivering AI powered products alongside scalable AI infrastructure.

Responsibilities

Collaborate with a cross functional team of engineers, research scientists, technical program managers, and product managers to deliver AI driven products that alter how associates work and how customers engage with Capital One.
Design, build, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, among other areas.
Utilize a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and related tools.
Invent and introduce state-of-the-art LLM optimization techniques to improve scalability, cost, latency, and throughput for large scale production AI systems.
Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

Requirements

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related field with at least 4 years of experience developing AI and ML algorithms or technologies; or a Master’s degree in the same fields with at least 2 years of experience.
At least 4 years of experience programming with Python, Go, Scala, or Java.

Technologies

Python
Go
Scala
Java
AWS Ultraclusters
Huggingface
VectorDBs
Nemo Guardrails
PyTorch

Benefits

Health benefits
Performance-based incentive compensation (cash bonuses and/or long term incentives)

Team

The Intelligent Foundations and Experiences (IFX) team sits at the core of Capital One's AI strategy. The group partners across the company to advance AI science and engineering, building and deploying proprietary solutions central to the business and delivering value to millions of customers. The AI models and platforms developed by IFX empower teams across Capital One to enhance products with AI capabilities.

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Today

AWS AI Engineer

Hudson Manpower Cincinnati, OH 🇺🇸 Remote

Cincinnati, OH

Today

Full time AI Amazon Web Services Artificial Intelligence

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Job Description

Hudson Manpower is seeking an experienced AWS AI Engineer in Cincinnati with remote options. The role centers on building retrieval-augmented generation systems, fine-tuning large language models, and delivering AWS-native microservices to support automation and governance in an enterprise environment. This position prioritizes practical cloud engineering, secure architectures, clear collaboration, and scalable AI capabilities.

Benefits

Competitive base salary
Medical, dental, and vision insurance coverage
Optional life and disability insurance
401(k) with company match and optional profit sharing
Paid vacation time
Paid bench time
Training allowance offered
Eligibility to earn referral bonuses

Responsibilities

Hands on work with AWS services including Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3 to build scalable AI systems
Implement and manage AWS cloud services across infrastructure, machine learning, and AI platform components
Develop LLM based applications, implementing Retrieval-Augmented Generation (RAG) with LangChain and similar frameworks
Create cloud native microservices, APIs, and serverless functions to enable intelligent automation and real time data processing
Collaborate with internal stakeholders to translate business goals into secure, scalable AI solutions
Own the software release lifecycle, including CI/CD pipelines, GitHub based SDLC, and infrastructure as code with Terraform
Support the development and evolution of reusable platform components for AI and ML operations
Create and maintain technical documentation for the team and internal customers
Excellent verbal and written communication skills in English

Requirements

7 years of hands-on software engineering experience with a strong focus on Python
Experience with AWS services, especially Bedrock or SageMaker
Familiar with fine tuning large language models or building datasets and deploying ML models to production
Demonstrated experience with AWS Organizations and policy guardrails (SCP, AWS Config)
Solid experience implementing RAG architectures and LangChain
Experience with infrastructure as code best practices and building Terraform modules for AWS
Strong background in Git based version control, code reviews, and DevOps workflows
Demonstrated success delivering production ready software with release pipeline integration

Technologies

Python
Bedrock
SageMaker
Lambda
ECS
Step Functions
DynamoDB
S3
LangChain
Transformers
PyTorch
TensorFlow
Terraform
Git
GitHub
Hugging Face
Node.js
Terraform Sentinel
AWS Config
AWS Organizations
SCP

Supervisory responsibilities

None

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1d ago

AWS AI Engineer

Hudson Manpower Morton Grove, IL 🇺🇸 Remote

Morton Grove, IL

1d ago

Full time Backend Developer AI Amazon Web Services

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Job Description

Senior AWS AI Engineer responsible for delivering AI/ML applications on AWS, focusing on retrieval-augmented generation (RAG), fine-tuning LLMs, and AWS-native microservices for enterprise automation.

Responsibilities

Hands-on work with AWS services such as AWS Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3 to build and operate AI/ML capabilities.
Design and implement AWS cloud services spanning infrastructure, ML platforms, and AI services to support enterprise automation.
Develop LLM based applications, including Retrieval-Augmented Generation using LangChain and other frameworks.
Build cloud-native microservices, APIs, and serverless functions to enable intelligent automation and real-time data processing.
Collaborate with stakeholders to translate business goals into secure, scalable AI systems.
Own the software release lifecycle, managing CI/CD pipelines, GitHub-based SDLC, and infrastructure as code with Terraform.
Support development and evolution of reusable platform components for AI/ML operations.
Create and maintain technical documentation for the team and internal customers.
Demonstrate excellent verbal and written communication skills in English.

Requirements

Hands-on experience with AWS services such as Bedrock, SageMaker, ECS, and Lambda.
Experience with AWS Organizations and policy guardrails, including SCPs and AWS Config.
Proven experience implementing RAG architectures and working with ML frameworks/tools such as Transformers, PyTorch, TensorFlow, and LangChain.
Strong Infrastructure as Code practices and experience building Terraform modules for AWS.
Fine-tuning large language models, building datasets, and deploying ML models to production.
Experience with Git-based version control, code reviews, and DevOps workflows.
Minimum 7 years of relevant professional experience.

Technologies

AWS Bedrock
AWS SageMaker
AWS ECS
AWS Lambda
AWS Step Functions
DynamoDB
S3
LangChain
Transformers
PyTorch
TensorFlow
Terraform
Terraform Sentinel
Hugging Face
Node.js
Git

Benefits

Competitive base salary
Medical, dental, and vision insurance coverage
Optional life and disability insurance provided
401(k) with a company match and optional profit sharing
Paid vacation time
Paid bench time
Training allowance offering
Referral bonuses

Top Skills

Must Have
- AWS Bedrock
- AWS SageMaker
- AWS ECS
- AWS Lambda
- Experience with AWS Organizations and policy guardrails (SCP, AWS Config)
- Experience implementing RAG architectures and using ML tooling like Transformers, PyTorch, TensorFlow, and LangChain
- Infrastructure as Code best practices and building Terraform modules for AWS
- Fine-tuning LLMs, building datasets, and deploying ML models to production
- Git-based version control, code reviews, and DevOps workflows
Nice To Have
- AWS or relevant cloud certifications
- Data privacy and compliance best practices (PII handling, secure model deployment)
- Data science background or experience with structured/unstructured data
- Exposure to FinOps and cloud cost optimization
- Hugging Face, Node.js
- Policy as Code development (Terraform Sentinel)

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1d ago

AWS AI Engineer

Hudson Manpower Redmond, WA 🇺🇸 Remote

Redmond, WA

1d ago

Full time Backend Developer AI Amazon Web Services

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Job Description

Hudson Manpower is seeking a Senior AWS AI Engineer to design and deploy production AI and ML applications on AWS, with a focus on retrieval-augmented generation, fine-tuning large language models, and AWS-native microservices. This role is based in Redmond, Washington, with remote work options, and combines hands-on cloud engineering with advanced ML deployment to deliver scalable, secure AI solutions.

Responsibilities

Engage hands-on with AWS services such as Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3 to build and operate production workflows.
Lead the design and implementation of AWS cloud infrastructure and AI platform services, spanning infrastructure, ML pipelines, and AI tooling.
Develop LLM-based applications, including Retrieval-Augmented Generation (RAG) solutions using LangChain and alternative frameworks.
Create cloud-native microservices, APIs, and serverless functions to enable intelligent automation and real-time data processing.
Collaborate with internal stakeholders to translate business goals into secure, scalable AI systems.
Own the software release lifecycle, including CI/CD pipelines, GitHub-based SDLC, and infrastructure as code with Terraform.
Support the development and evolution of reusable platform components for AI/ML operations.
Produce and maintain technical documentation for the team and internal customers.
Demonstrate excellent verbal and written communication skills in English.

Requirements

Minimum of 7 years of hands-on software engineering experience with a strong emphasis on Python.
Proficiency with AWS services, particularly Bedrock or SageMaker.
Experience fine-tuning large language models or building datasets and deploying ML models to production.
Solid experience with AWS Organizations and policy guardrails such as SCP and AWS Config.
Demonstrated expertise in implementing RAG architectures and using LangChain.
Strong background in Infrastructure as Code best practices and building Terraform modules for AWS.
Proven ability with Git-based version control, code reviews, and DevOps workflows.
Track record delivering production-ready software with integrated release pipelines.

Technologies

Python
AWS Bedrock, SageMaker, Lambda, Step Functions, DynamoDB, S3
LangChain, Transformers
PyTorch, TensorFlow
Terraform, Terraform Sentinel, AWS Config, AWS Organizations
Git, GitHub, Hugging Face
Node.js, Golang, ECS

Benefits

Competitive base salary
Medical, dental, and vision insurance coverage
Optional life and disability insurance
401(k) with company match and optional profit sharing
Paid vacation time
Paid bench time
Training allowance
Referral bonuses

Top Skills

Proficiency with AWS services including Bedrock, SageMaker, ECS, and Lambda
Experience with AWS Organizations and policy guardrails (SCP, AWS Config)
Hands-on experience implementing RAG architectures and using ML tooling such as Transformers, PyTorch, TensorFlow, and LangChain
Breadth in Infrastructure as Code and building Terraform modules for AWS
Fine-tuning LLMs, building datasets, and deploying ML models to production
Git-based version control, code reviews, and DevOps workflows

Nice to Have

AWS or other cloud certifications
Data privacy and compliance practices (PII handling, secure model deployment)
Data science background or experience with structured and unstructured data
Exposure to FinOps and cloud cost optimization
Experience with Hugging Face, Node.js
Policy as Code development (e.g., Terraform Sentinel)

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1d ago

AWS AI Engineer

Hudson Manpower Sunnyvale, CA 🇺🇸 Remote

Sunnyvale, CA

1d ago

Full time AI Artificial Intelligence Automation

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Job Description

The role is for a senior AWS AI Engineer at Hudson Manpower, based in Sunnyvale, California with remote working options. The position centers on developing cloud-native AI/ML applications, with a focus on retrieval-augmented generation, fine-tuning large language models, and deploying AWS-based microservices for an enterprise production environment.

Responsibilities

Hands-on development with AWS services such as Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3 to build and operate AI/ML workloads.
Lead the implementation of AWS cloud services spanning infrastructure, machine learning, and AI platform capabilities.
Work with LLM-based applications, including Retrieval-Augmented Generation (RAG) using LangChain and related frameworks.
Develop cloud-native microservices, APIs, and serverless functions to support intelligent automation and real-time data processing.
Collaborate with internal stakeholders to translate business goals into secure, scalable AI systems.
Own the software release lifecycle, including CI/CD pipelines, GitHub-based SDLC, and infrastructure as code with Terraform.
Support the development and evolution of reusable platform components for AI/ML operations.
Create and maintain technical documentation for the team and internal customers.
Demonstrate strong verbal and written communication skills in English.

Requirements

Minimum of 7 years of hands-on software engineering experience with a strong emphasis on Python.
Experience with AWS services, particularly Bedrock or SageMaker.
Familiarity with fine-tuning large language models and deploying ML models to production, including dataset creation.
Proven experience with AWS Organizations and policy guardrails such as SCP and AWS Config.
Solid background in implementing Retrieval-Augmented Generation (RAG) architectures and LangChain.
Proficiency in Infrastructure as Code practices and building Terraform modules for AWS cloud environments.
Strong background in Git-based version control, code reviews, and DevOps workflows.
History of delivering production-ready software with integrated release pipelines.

Technologies

AWS Bedrock
AWS SageMaker
AWS Lambda
AWS Step Functions
DynamoDB
S3
LangChain
Transformers
PyTorch
TensorFlow
Terraform
Terraform Sentinel
Git
Python
Golang
Node.js
Hugging Face
AWS Organizations
AWS Config
SCP

Benefits

Competitive base salary
Medical, dental, and vision insurance coverage
Optional life and disability insurance
401(k) with company match and optional profit sharing
Paid vacation time
Paid bench time
Training allowance offering
Eligibility for referral bonuses

Supervisory Responsibilities

None

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2d ago

Machine Learning Engineer - Document Digitization (LLMs)-Vice President

JPMorganChase Jersey City, NJ

Jersey City, NJ

2d ago

$164k - $260k/yr Full time Ai Ml Amazon Eks Artificial Intelligence

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Job Description

Senior Vice President level Machine Learning Engineer focused on designing, building, and deploying AI powered document digitization solutions using large language models to transform document processing and governance.

Responsibilities

Lead end-to-end design, development, and integration of AI powered document digitization solutions to extract data and insights from diverse document formats.
Manage the full AI/ML lifecycle: training, validation, deployment, monitoring, and ongoing improvements in production environments.
Apply generative AI and LLMs to automate and optimize document workflows.
Build and maintain scalable document digitization pipelines using Python, AI frameworks, and cloud technologies.
Provision and manage cloud resources with infrastructure as code tools (Terraform) and AWS services (SageMaker, Bedrock).
Ensure scalability, reliability, security, and governance compliance of AI/ML solutions.
Collaborate with cross functional teams to reimagine legacy document processing with generative AI and LLMs.
Develop and maintain dashboards and reporting tools to monitor digitization accuracy, workflow efficiency, and business impact.
Mentor junior engineers and promote best practices across AI/ML, software engineering, and testing.
Conduct model validation, human in the loop review, and implement continuous improvement strategies for digitization accuracy.
Contribute to communities of practice and explore new and emerging technologies.

Requirements

Bachelor's or Master's in Computer Science, Data Science, Machine Learning, or related field, with relevant industry experience.
Strong proficiency in Python for building production grade AI services and data/document pipelines.
Strong working proficiency in Java, including API and microservice development with Spring Boot; familiarity with front end technologies (React.js, AngularJS) is a plus.
Hands-on experience delivering LLM powered GenAI applications in production (document understanding, retrieval augmented generation, workflow automation), including evaluation, observability, guardrails, and continuous improvement.
Experience with MLOps / LLMOps practices in production (CI/CD, automated testing, deployment strategies, monitoring, incident response).
Working knowledge of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, PyTorch Lightning) with emphasis on integrating models into scalable systems.
Experience with AWS and cloud native delivery including SageMaker and/or Bedrock, containerization (Docker, Kubernetes, Amazon EKS), and infrastructure as code (Terraform).
Familiarity with NoSQL / search / graph technologies (MongoDB Atlas, Elasticsearch/OpenSearch, Neo4j) for document search and knowledge retrieval.
Experience with agentic coding approaches, autonomous/assisted code agents, orchestration patterns, and tool-use/agent frameworks to accelerate document digitization workflows.
Strong understanding of SDLC, CI/CD, resiliency, and security practices; proven problem solving, communication, and collaboration skills.
Proven ability to accelerate development using AI technologies while maintaining engineering rigor (testing, code quality, governance).

Technologies

Python
Terraform
AWS SageMaker
AWS Bedrock
Docker
Kubernetes
Amazon EKS
Java
Spring Boot
React.js
AngularJS
TensorFlow
PyTorch
Scikit-learn
PyTorch Lightning
MongoDB Atlas
Elasticsearch/OpenSearch
Neo4j
LLMs

Benefits

Equity/stock-based compensation
Competitive base salary
Commission-based pay and/or discretionary incentive compensation
Comprehensive health care coverage
On-site health and wellness centers
Retirement savings plan
Backup childcare
Tuition reimbursement
Mental health support
Financial coaching

About Us

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

About the Team

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.

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2d ago

Lead Applied AI Engineer II

Deloitte Washington, DC

Washington, DC

2d ago

$119k - $244k/yr Full time Artificial Intelligence AWS Aws Bedrock

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Job Description

Deloitte is seeking a Lead Applied AI Engineer II for an onsite role in Washington, DC. The position centers on hands-on software engineering across high-visibility initiatives, with an emphasis on delivering customer outcomes and tangible business value. The role also invites you to model technical leadership and mentor cross-functional teams to design, build, and deploy advanced solutions. Salary ranges from USD 118,700 to 243,700 per year. A bachelor’s degree and at least six years of relevant experience are required.

Responsibilities

Outcome driven accountability: uphold a culture focused on customer and business outcomes, delivering engineering solutions that solve complex problems with measurable value while maintaining lean, high‑quality designs and implementations.
Technical leadership and advocacy: act as the product’s technical champion, validating code quality and feasibility and aligning work with business and customer goals. lead requirements analysis, low‑level architecture and component design, development, testing, integrations, and support.
Engineering craftsmanship: safeguard architecture integrity and the enterprise standards across the tech stack. manage dependencies, design, implementation, quality, data, and ongoing maintenance. remain hands-on, continuously learn new approaches, and create technical specifications; produce high‑quality, scalable code and review peers’ code while mentoring them to ensure quality.
Customer centric engineering: develop lean solutions through rapid, low‑cost experimentation to address customer needs. engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time.
Incremental and iterative delivery: adopt a forward‑leaning mindset that emphasizes action and evidence over heavy planning, delivering lean, maintainable solutions that navigate complexity.
Cross-functional collaboration and integration: work with empowered product management, experience, and delivery teams; integrate diverse perspectives to balance feasibility, viability, usability, and value, fostering a collaborative environment that drives innovation.
Advanced technical proficiency: demonstrate deep expertise in modern software engineering practices, including AI and Agentic SSDLC, delivering daily product deployments with full automation from discovery to production to operations and quality checks throughout the SSDLC lifecycle. be a role model and apply these techniques to optimize solutioning and delivery, while focusing on the full lifecycle of product development and continuous improvement.
Domain expertise: rapidly acquire domain knowledge relevant to the business or product; translate business needs, architectures, and UX/UI designs into technical specifications and code; contribute as a flexible, quality‑driven teammate mindful of tech debt payoff.
Effective communication and influence: communicate complex technical concepts clearly and persuasively, inspiring teammates and product teams through well‑structured arguments and evidence‑based trade‑offs; craft narratives that align technical solutions with business objectives.
Engagement and collaborative co‑creation: collaborate with product engineering teams at all levels, including customers when needed; build constructive relationships and foster a culture of co‑creation and shared momentum toward product goals; align diverse perspectives to reach feasible solutions.

Requirements

Bachelor’s degree in computer science, software engineering, data science, machine learning, or a related discipline.
Six or more years of experience with technologies such as Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, and relevant unit testing frameworks.
Three or more years building AI/ML applications, with hands-on GenAI experience across LLM integration (OpenAI, Anthropic, or open‑source models), RAG pipelines, prompt engineering, and vector databases.
Three or more years of cloud‑native engineering using FaaS, PaaS, or microservices on Azure, AWS, or GCP, including AI/ML services such as Azure OpenAI, AWS Bedrock, or Vertex AI.
One or more years establishing engineering standards, including actively leading, mentoring, and guiding team members in adopting and improving these standards.
Prior software engineering experience with Business Context Diagrams, sequence/activity/state/entity relationship/data flow diagrams, OOP/OOD, data structures, algorithms, code instrumentation, and AI augmented, spec‑driven development.
Experience using XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow, and agentic AI frameworks (for example LangFuse, LangSmith, or similar multi‑agent orchestration tools) to deliver high quality products rapidly.

Technologies

Angular, React, NodeJS, Python, C#, .NET, Java
SQL/NoSQL, PyTorch, TensorFlow
LangChain, LangGraph
OpenAI, Anthropic, LangFuse, LangSmith
Azure, AWS, GCP; Azure OpenAI, AWS Bedrock, Vertex AI
FaaS, PaaS, MLflow
ADO, GitHub, SonarQube

The Successful Candidate Will Possess

Excellent interpersonal and organizational skills, with the ability to handle diverse situations, manage complex projects, and adapt to changing priorities with professionalism and empathy.

Other

Travel availability of approximately 10 percent, depending on project requirements.
Limited immigration sponsorship may be available.
The stated wage range reflects a broad range of factors considered in compensation decisions, including skill, experience, and business needs; geographic differentials may apply.
You may be eligible for a discretionary annual incentive program, subject to program rules and individual and organizational performance.