generative ai engineer

American business solutions inc

<div><h2 class="jobSectionHeader">Required Skills</h2>
Undergraduate degree in computer science, data science, artificial intelligence or related field required.
1 year of proven experience with establishing proof of concept success criteria and evaluating AI solutions against criteria
2 years of hands-on experience with ChatGPT, Microsoft Copilot, and comparable generative AI platforms
2 years of experience designing and implementing AI agents and retrieval-augmented generation (RAG) solutions.
1 year of experience using AI-assisted coding tools to accelerate development, testing, debugging, and documentation.
1 year of experience defining AI use case success criteria, key performance indicators (KPIs) and production monitoring measures for AI use cases.
1 year of experience building dashboards and reporting for AI adoption, performance, cost, risk, and operational outcomes.
1 year of hands-on experience integrating AI capabilities with Azure and AWS.
<h2 class="jobSectionHeader">Preferred Skills</h2>
Background in a variety of programming languages and principals.
Familiarity with the foundations of artificial neural networks (ANNs), transformers, natural language processing, image classification and time-series data.
Experience with data tools and techniques for storing, retrieving, and cleaning data.</div>

Generative AI Engineer(Local to SC)

Datamatics Technologies

<div>
 Job Description: AI / ML Engineer
 
 
 Job Title:
 
 AI / ML Engineer
 
 
 Experience:
 
 3&ndash;11 Years
 
 
 Location:
 
 &nbsp;
 
 
 Riyadh (Onsite)
 
 
 
 
 Employment Type:
 
 Full-Time
 
 Job Overview
 
 We are seeking a skilled
 
 AI / ML Engineer
 
 with
 
 3&ndash;11 years of experience
 
 to design, develop, deploy, and optimize machine learning and generative AI solutions. The ideal candidate will have hands-on expertise in building scalable AI/ML models, working with cloud-native AI platforms, and implementing production-ready machine learning pipelines. Experience with modern AI frameworks, large language models (LLMs), and MLOps practices is highly desirable.
 
 Key Responsibilities
 <ul>
 <li>
 Design, develop, train, and deploy machine learning and deep learning models for enterprise applications
 </li>
 <li>
 Build and optimize end-to-end ML pipelines for data ingestion, model training, evaluation, and deployment
 </li>
 <li>
 Develop Generative AI and LLM-powered applications using modern AI frameworks
 </li>
 <li>
 Collaborate with data engineers, software developers, and business stakeholders to deliver AI-driven solutions
 </li>
 <li>
 Deploy and monitor ML models on cloud platforms while ensuring scalability, reliability, and security
 </li>
 <li>
 Optimize model performance through feature engineering, hyperparameter tuning, and continuous evaluation
 </li>
 <li>
 Implement MLOps best practices including model versioning, monitoring, and CI/CD automation
 </li>
 <li>
 Stay current with advancements in AI, machine learning, and cloud AI services
 </li>
 </ul>
 Required Technical SkillsCloud AI Platforms
 <ul>
 <li>
 Hands-on experience with
 
 GCP Vertex AI or Azure Machine Learning or AWS SageMaker
 
 </li>
 <li>
 Experience with
 
 Azure OpenAI or AWS Bedrock
 
 for Generative AI solutions
 </li>
 <li>
 Experience with
 
 BigQuery ML and Dataflow
 
 for data processing and machine learning workflows
 </li>
 </ul>
 Programming &amp; Machine Learning
 <ul>
 <li>
 Strong proficiency in
 
 Python
 
 </li>
 <li>
 Experience developing machine learning solutions using
 
 TensorFlow or PyTorch
 
 </li>
 <li>
 Strong understanding of supervised, unsupervised, reinforcement learning, and deep learning concepts
 </li>
 </ul>
 Generative AI &amp; LLM Frameworks
 <ul>
 <li>
 Experience with
 
 Hugging Face and LangChain
 
 for building LLM-powered applications
 </li>
 <li>
 Knowledge of prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, and vector databases is preferred
 </li>
 </ul>
 Data Engineering &amp; Analytics
 <ul>
 <li>
 Experience with
 
 Databricks
 
 for data engineering, model development, and analytics workflows
 </li>
 <li>
 Strong understanding of data preprocessing, feature engineering, and large-scale data processing
 </li>
 </ul>
 MLOps &amp; Deployment
 <ul>
 <li>
 Experience deploying machine learning models into production
 </li>
 <li>
 Knowledge of Docker, Kubernetes, CI/CD pipelines, and model monitoring is an advantage
 </li>
 </ul>
 Qualifications
 <ul>
 <li>
 Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field
 </li>
 <li>
 
 3&ndash;11 years
 
 of professional experience in AI, Machine Learning, or Data Science
 </li>
 <li>
 Strong analytical, mathematical, and problem-solving skills
 </li>
 <li>
 Experience working in Agile development environments
 </li>
 <li>
 Excellent communication and collaboration skills
 </li>
 </ul>
 Preferred Skills
 <ul>
 <li>
 Experience with Large Language Models (LLMs) and Generative AI applications
 </li>
 <li>
 Knowledge of Retrieval-Augmented Generation (RAG), vector databases, and AI agents
 </li>
 <li>
 Experience with distributed model training and cloud-native AI architectures
 </li>
 <li>
 Cloud certifications in AWS, Azure, or Google Cloud are a plus
 </li>
 </ul>
 Key Technology Stack
 <ul>
 <li>
 
 Cloud AI:
 
 
 GCP Vertex AI or Azure Machine Learning or AWS SageMaker
 
 </li>
 <li>
 
 Generative AI:
 
 
 Azure OpenAI or AWS Bedrock
 
 
 and
 
 Large Language Models (LLMs)
 </li>
 <li>
 
 Data Processing:
 
 
 BigQuery ML and Dataflow
 
 
 and
 
 Databricks
 </li>
 <li>
 
 Programming:
 
 Python
 </li>
 <li>
 
 Machine Learning Frameworks:
 
 
 TensorFlow or PyTorch
 
 </li>
 <li>
 
 LLM Frameworks:
 
 
 Hugging Face or LangChain
 
 </li>
 <li>
 
 MLOps:
 
 Docker
 
 and
 
 Kubernetes
 
 and
 
 CI/CD (Preferred)
 </li>
 </ul>
</div>

AI / ML Engineer

Capgemini

<div><div><div><div>Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you&rsquo;d like, where you&rsquo;ll be supported and inspired by a collaborative community of colleagues around the world, and where you&rsquo;ll be able to reimagine what&rsquo;s possible. Join us and help the world&rsquo;s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
<div><div><div><h2 class="jobSectionHeader">Location</h2>
</div><div>San Francisco CA
</div></div><div><div><h2 class="jobSectionHeader">Your Role</h2>
</div><div>The GenAI Engineer / Data Scientist is responsible for designing, developing, deploying, and maintaining Generative AI (GenAI) and Predictive AI solutions that deliver business value. The role requires expertise in AI/ML, cloud platforms, APIs, data engineering, MLOps, and AI agent workflows, with a strong focus on production-grade AI implementation. 
 
Key Responsibilities 
 
Develop and deploy Generative AI solutions (GPT, Claude, Stable Diffusion) and Predictive AI models (regression, classification, clustering).
 
Design and integrate AI applications using REST APIs, authentication mechanisms, JSON services, and cloud-based architectures.
 
Build and support AI agents, autonomous systems, and agentic workflows.
 
Deploy, monitor, and optimize AI models in production using MLOps practices.
 
Design and maintain data pipelines, data lakes, and data warehouses.
 
Monitor model performance, troubleshoot issues, and manage data/model drift.
 
Collaborate with business and technical teams to align AI solutions with organizational objectives.
 
Create reusable assets, demos, and proof-of-concepts to support innovation and business development. 
 
 
</div></div><div><div><h2 class="jobSectionHeader">Required Skills and Experience
</h2></div><div>A hands-on AI professional with strong expertise in Generative AI, Machine Learning, Python, Cloud Technologies, APIs, MLOps, Data Engineering, and AI Agents, capable of building and scaling enterprise-grade AI solutions from development to production.
 
Bachelor's degree or higher in AI, Machine Learning, Computer Science, or related field.
 
3-5 years of experience in AI, Machine Learning, Data Science, or Application Development.
 
Experience with production AI deployments, MLOps, model monitoring, and cloud platforms.
GPT, Claude LLM, Stable Diffusion
 
LangChain
 
TensorFlow
 
PyTorch
 
Scikit-learn
 
RAG (Retrieval-Augmented Generation)
 
AI Agents &amp; Agentic Workflows
 
API Development
 
REST APIs
 
JSON
 
HTTP Requests
 
Authentication &amp; Tokens
 
Error Handling &amp; Debugging 
 
 
 
 
</div></div></div>The base compensation range for this role in the posted location is $90,000- $160,000
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
<ul><li>Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave</li>
</ul><ul><li>Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)</li>
<li>Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)</li>
<li>Life and disability insurance</li>
<li>Employee assistance programs</li>
<li>Other benefits as provided by local policy and eligibility</li>
</ul>Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini&rsquo;s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.
Disclaimers
Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.
This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.
Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.
Click the following link for more information on your rights as an Applicant in the United States. http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law
Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.</div></div></div></div>

Data Scientist/ AI Engineer

MOZN

<div>
 
 
 About Mozn
 
 
 
 
 
 MOZN is a leading Enterprise AI company enabling organizations to make informed decisions in two critical domains: Financial Crime Prevention and Enterprise Knowledge Intelligence.
 
 
 We're a diverse, collaborative team of innovators united by a shared purpose: to build AI that delivers tangible business value, builds trust, and empowers people and organizations with augmented intelligence. Our culture is built on the relentless pursuit of excellence and meaningful impact.
 
 
 If you're passionate about working alongside exceptional talent on world-class AI, and you want the autonomy and runway to do the best work of your career, join us in shaping the future of intelligent enterprises.
 
 
 
 About the role
 
 
 
 
 
 We are looking for a AI Engineer to lead the design, deployment, and optimization of machine learning and generative AI solutions. The role focuses on applying advanced ML techniques to solve real-world challenges across government and enterprise clients in Saudi Arabia.
 
 
 What you'll do
 
 
 
 
 <ul>
 <li>
 Designing, building, and scaling machine learning models and infrastructure
 </li>
 <li>
 Deploying deep learning and generative models into production for public and private sector projects
 </li>
 <li>
 Optimizing ML training and inference for performance, latency, and scalability
 </li>
 <li>
 Monitoring, retraining, and improving deployed ML models
 </li>
 <li>
 Driving consultation efforts, providing expert guidance to client stakeholders
 </li>
 <li>
 Own the end-to-end delivery of AI solutions, including data pipelines, model development, backend services, APIs, integrations, user interfaces, deployment, and operations
 </li>
 <li>
 Design and build data ingestion, transformation, and processing pipelines for structured and unstructured data
 </li>
 <li>
 Develop backend services and APIs to expose AI capabilities securely and reliably
 </li>
 <li>
 Build or contribute to frontend applications, dashboards, and interfaces for AI-powered solutions
 </li>
 <li>
 Integrate AI solutions with enterprise systems, databases, authentication services, and third-party platforms
 
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 <ul>
 <li>
 Bachelor's or master's degree in computer science or related field
 </li>
 <li>
 3-5 years of experience across software engineering, ML engineering, data science, data engineering and generative AI
 </li>
 <li>
 Strong track record of projects across public and private sectors
 </li>
 <li>
 Expertise in Python, TensorFlow, PyTorch, ONNX, and ML deployment frameworks
 </li>
 <li>
 Expertise in containerization and orchestration technologies (Docker, Kubernetes), with hands-on experience in ML lifecycle management (MLflow) and local LLM deployment frameworks (Ollama)
 </li>
 <li>
 Skilled in on-premise infrastructure design and enterprise architecture frameworks, with strong adherence to security and compliance best practices
 </li>
 <li>
 Deep understanding of hardware provisioning for local LLM deployments (GPU, RAM, and storage optimization) and secure network configurations for internal AI services
 </li>
 <li>
 Experience with cloud ML environments (SageMaker, Vertex AI, OCI Data Science)
 </li>
 <li>
 Familiarity with MLOps practices and automation pipelines
 </li>
 <li>
 Strong end-to-end engineering capabilities across AI, data engineering, backend development, APIs, integrations, and application deployment
 </li>
 <li>
 Experience building data ingestion, transformation, and processing pipelines
 </li>
 <li>
 Familiarity with backend frameworks such as FastAPI, Flask, Django, Node.js, or equivalent technologies
 </li>
 <li>
 Experience designing and consuming REST APIs, webhooks, and enterprise integration interfaces
 </li>
 <li>
 Working knowledge of frontend technologies such as React, Next.js, JavaScript, TypeScript, HTML, and CSS
 </li>
 <li>
 Experience integrating AI solutions with databases, enterprise applications, identity and access management systems, and third-party services
 </li>
 <li>
 Ability to independently build functional AI applications from prototype through production
 </li>
 <li>
 Experience effectively using AI-assisted software development tools to accelerate prototyping and delivery
 
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 
 <ul>
 <li>
 You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space
 </li>
 </ul>
 <ul>
 <li>
 You will be given a lot of responsibility and trust. We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best
 </li>
 </ul>
 <ul>
 <li>
 The fundamentals will be taken care of: competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best
 </li>
 </ul>
 <ul>
 <li>
 You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI
 </li>
 </ul>
 <ul>
 <li>
 We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves
 </li>
 </ul>
</div>

AI Engineer

Volga Partners

<div>Location 
Islamabad, Islamabad Capital Territory, Pakistan
Office Location 
House #571, Street #35, E-11/3, Islamabad, Pakistan
Monthly Salary 
PKR 250,000 - PKR 400,000 per month (commensurate with experience and technical expertise)
Work Setup: Hybrid<ul><li>
3 days in office</li><li>
2 days remote</li></ul>
Working Hours 
07:00 PM to 04:00 AM PKT 
About Volga Partners
Volga Partners is a global leader in Generative AI (GenAI) innovation, building intelligent systems, custom LLM applications, and advanced automation solutions for organizations worldwide. We design, develop, and deploy AI-powered technologies that help organizations solve complex business challenges across industries including finance, healthcare, legal, and technology.
With a global workforce of 3,000+ professionals across multiple countries, Volga Partners combines diverse expertise, innovation, and technical excellence to deliver impactful AI solutions at scale.
We are seeking an experienced AI &amp; Backend Engineer to help build and scale production-grade AI applications used by global clients. This role is ideal for engineers who have already worked on AI-powered solutions and are comfortable taking ownership of technical initiatives from architecture through deployment.
You will work directly with leadership, product teams, and engineering stakeholders to develop scalable backend systems, Retrieval-Augmented Generation (RAG) pipelines, LLM-powered applications, and intelligent automation solutions.
This role is designed for experienced engineers who can contribute independently and are seeking long-term growth, ownership, and exposure to cutting-edge AI technologies. 
Why Join Volga Partners<ul><li>
Build real-world AI applications used by global organizations.</li><li>
Work with modern LLM technologies and AI orchestration frameworks.</li><li>
Own projects from design through production deployment.</li><li>
Influence technical architecture and product direction.</li><li>
Collaborate directly with leadership and engineering teams.</li><li>
Join a growing organization focused on the future of Generative AI.</li></ul>
Key Responsibilities<ul><li>
Design and implement scalable backend services and microservices using Python and/or Node.js.</li><li>
Build and deploy production-ready AI solutions, including copilots, chatbots, and workflow automation systems.</li><li>
Develop and optimize Retrieval-Augmented Generation (RAG) pipelines.</li><li>
Integrate and manage large language models, including OpenAI, Anthropic, and open-source models.</li><li>
Design secure, performant APIs and backend infrastructure.</li><li>
Process and structure enterprise data for AI workflows.</li><li>
Improve reliability, performance, latency, and cost efficiency of AI systems.</li><li>
Collaborate with product and engineering stakeholders to deliver quality solutions.</li></ul>
Qualifications
Required<ul><li>
4+ years of professional software engineering experience, with a documented track record of building and managing scalable backend architectures.</li><li>
At least 3 years of hands-on experience building AI or LLM-powered solutions into production environments.</li><li>
Demonstrated experience building and supporting scalable backend applications.</li><li>
Experience deploying AI or LLM-powered solutions into production environments.</li><li>
Strong proficiency in Python and/or JavaScript/TypeScript.</li><li>
Experience with RAG architectures, vector databases, embeddings, or AI orchestration frameworks.</li><li>
Experience working with APIs, cloud environments, and modern development practices.</li><li>
Ability to work independently and take ownership of technical solutions from design through deployment.</li></ul>
Preferred<ul><li>
Experience with OpenAI, Anthropic, LangChain, or LlamaIndex.</li><li>
Experience with Pinecone, Chroma, or other vector databases.</li><li>
AWS experience.</li><li>
Experience building agentic AI workflows or automation systems.</li><li>
Experience working with complex enterprise data environments.</li></ul>
Important
This is not an entry-level AI role. We are seeking engineers who have prior experience building AI-powered solutions and can contribute independently in a fast-paced environment with minimal supervision. 
What We Offer<ul><li>
Monthly salary of PKR 250,000 - PKR 400,000 based on experience and technical expertise.</li><li>
Opportunity to build and own production of AI applications used by global clients.</li><li>
Direct exposure to Generative AI, LLM systems, RAG frameworks, and intelligent automation solutions.</li><li>
High-impact role with visibility to leadership and influence over technical decisions.</li><li>
A collaborative and fast-paced environment focused on execution and innovation.</li><li>
90-day probationary period.</li></ul>
Benefits Eligibility
Upon successful completion of the statutory probationary period, employees become eligible for:<ul><li>
Company-sponsored medical insurance, subject to company policy.</li><li>
Paid Time Off (PTO) in accordance with the company's service-based PTO policy.</li><li>
Holiday pay for designated company-observed holidays, subject to company policy.</li><li>
Career growth opportunities, increased ownership, and continued professional development within a rapidly growing AI-focused organization.</li></ul></div>

AI & Backend Engineer - Production AI & LLM Systems | Pakistan

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Do you want to join an innovative team of scientists and engineers who use terabytes of data and create state-of-the-art Generative AI algorithms to push the boundaries of AI creativity? We are building foundational behavioral models for Amazon Stores using Generative AI, LLMs and Large Model training techniques that fuses general world knowledge, customer shopping behavior and Amazon e-commerce domain knowledge. We are looking for scientists who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry using intelligent and transformative AI applications. Working closely with cross-functional teams, you will be an essential part of every stage of AI development, from ideation and design to rigorous testing and successful deployment, ensuring our AI projects drive innovation and provide value for our customers. If you&rsquo;re fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey! 
 
Key job responsibilities 
In this role you will leverage your background and expertise to lead developing foundational behavioral model for Amazon Stores using Generative AI, LLM and Large Model training techniques. On a day-to-day basis, you will: 
<ul><li>Research and implement new algorithms and architectures for generative AI applications.</li><li>Optimize model performance and scalability for inference and deployment.</li><li>Collaborate with other talented applied scientists and engineers to gather and preprocess large datasets and develop an improved training infrastructure that accelerates innovation.</li><li>Experiment with SOTA methods to improve generative AI model quality.</li><li>Provide technical expertise and guidance to support the integration of generative AI solutions into various products and services.</li></ul></div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience</li><li>2+ years of building models for business application experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing</li><li>Experience in patents or publications at top-tier peer-reviewed conferences or journals</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Strong understanding of machine learning, deep learning, and generative AI principles and algorithms.</li><li>Proficiency with modeling and large-scale data processing tools such as Pytorch, scikit-learn, Spark MLLib, PySpark, MxNet, Tensorflow, numpy, scipy etc.</li><li>Ability to work with large datasets and knowledge of data preprocessing techniques such as Hadoop, Spark etc..</li><li>Familiarity with natural language processing (NLP) and computer vision for generative AI applications.</li><li>Strong problem-solving and critical thinking skills and excellent communication and teamwork abilities to collaborate with cross-functional teams.</li><li>Ability to stay updated with the latest advancements in generative AI and adapt to new techniques and methodologies.</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, San Diego - 142,800.00 - 193,200.00 USD annually 
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually</div>

Applied Scientist (GenAI/LLM), Sandstone

Capital One

<div>Lead Machine Learning Engineer
As a Capital One Lead Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing Generative AI and advanced agentic systems at scale. You&rsquo;ll lead the detailed technical design, development, and implementation of core agentic architectures and multi-agent workflows using emerging technologies. You&rsquo;ll focus on system-level architectural design, develop and review complex models and application code, and ensure the high availability, performance, and security of our generative AI applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in generative and agentic machine learning engineering.
What you&rsquo;ll do in the role:
<ul><li>Architect Agentic Platforms: Design, develop, and scale core agentic engines and multi-agent workflow solutions, enabling seamless composition of conversational and business automation workflows.
</li><li>Drive AI Evaluation &amp; Trust: Build and integrate scalable evaluation (Evals) and observability frameworks into solutions to ensure model predictability, performance monitoring, and mitigation of model risk.
</li><li>Deliver High-Impact Use Cases: Partner with cross-functional product and business teams to deploy production AI solutions, including next-generation consumer AI experiences, intelligent recommendation engines, and advanced conversational assistants.
</li><li>Enforce Enterprise Guardrails: Ensure all AI/ML applications strictly adhere to robust data privacy standards, regulatory postures, and framework auditability/explainability.
</li><li>Translate Practical Research: Stay abreast of practical advancements in LLM optimization, retrieval-augmented generation (RAG), and multi-agent design patterns, judiciously applying these novel techniques to production systems.
</li><li>Technical Leadership &amp; Code Excellence: Provide technical direction, architectural oversight, and rigorous code reviews for engineering teams, fostering a culture of modern engineering excellence.
</li></ul>Basic Qualifications:
<ul><li>Bachelor&rsquo;s Degree
</li><li>At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
</li><li>At least 4 years of experience programming with Python, Scala, or Java
</li></ul>Preferred Qualifications:
<ul><li>Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
</li><li>3+ years of experience with GenAI frameworks (e.g., LangChain, LangGraph, LlamaIndex) and Vector Databases
</li><li>3 years of experience building, scaling, and optimizing Large Language Model (LLM) or GenAI orchestration systems in production
</li><li>2+ years of experience building automated evaluations (Evals) and observability pipelines for LLMs
</li><li>3+ years of on-the-job experience with an industry-recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
</li><li>Experience deploying AI solutions within a strictly regulated environment, incorporating data privacy and model risk governance
</li><li>Demonstrated ability to lead technical architecture design and provide deep technical guidance to engineering teams
</li><li>Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
</li><li>ML industry impact through conference presentations, papers, blog posts, open-source contributions, or patents
</li></ul>At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
Plano, TX: $179,400 - $204,700 for Lead Machine Learning Engineer 
 
 
 
 
 
 
 
 
 
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.
No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</div>

Lead Machine Learning Engineer

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