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ai researcher

wideanchor

Job Overview We are seeking a dynamic and innovative AI Researcher to join our cutting-edge technology team. In this role, you will drive the development of advanced artificial intelligence solutions, harnessing the power of machine learning, natural language processing, and big data analytics. Your expertise will help shape the future of intelligent systems, enabling transformative applications across diverse industries. This position offers an exciting opportunity to work with state-of-the-art tools and frameworks, contribute to impactful research projects, and collaborate with a talented team dedicated to pushing the boundaries of AI technology.Responsibilities<ul><li>Design, develop, and optimize machine learning models using frameworks such as TensorFlow and other AI tools.</li><li>Conduct research on unsupervised learning techniques to uncover hidden patterns in large datasets.</li><li>Implement data pipelines using ETL processes and tools like Talend to prepare data for analysis and model training.</li><li>Develop scalable solutions leveraging cloud platforms such as AWS for model deployment and management.</li><li>Collaborate with cross-functional teams to integrate natural language processing capabilities into products and services.</li><li>Perform data mining and database design to support analytics initiatives and enhance data accessibility.</li><li>Utilize big data technologies like Hadoop, Spark, and SQL to analyze complex datasets and extract actionable insights.</li></ul>Requirements<ul><li>Proven experience in machine learning, AI, and natural language processing with a strong understanding of relevant frameworks such as TensorFlow or similar.</li><li>Proficiency in programming languages including Python, Java, C, VBA, Bash (Unix shell), and R for data analysis and model development.</li><li>Hands-on experience with cloud services like AWS for model training, deployment, and scaling AI solutions.</li><li>Solid knowledge of big data tools such as Hadoop, Spark, SQL databases, and ETL processes for managing large-scale datasets.</li><li>Familiarity with database design principles and linked data concepts to facilitate efficient data retrieval and integration.</li><li>Experience in data mining, analytics, and applying unsupervised learning techniques to real-world problems.</li><li>Ability to work with diverse machine learning frameworks and tools while maintaining a focus on model accuracy and performance.</li><li>Strong analytical skills complemented by expertise in SAS or Looker for advanced reporting and visualization tasks.</li><li>Knowledge of quantum engineering is a plus but not required; enthusiasm for emerging technologies is encouraged. Join us as an AI Researcher to innovate at the forefront of technology! Bring your passion for research, your technical prowess across multiple programming languages and platforms, and your desire to make a meaningful impact through artificial intelligence solutions that transform industries worldwide.</li></ul>Pay: From $55,609.76 per yearBenefits:<ul><li>Employee assistance program</li><li>Flexible schedule</li><li>Professional development assistance</li><li>Referral program</li><li>Tuition reimbursement</li></ul>Work Location: In person

AI Researcher

Franklin Fitch

<div>
 
 The AI Adoption Manager is responsible for leading the enterprise-wide adoption, implementation, and evolution of artificial intelligence capabilities across the organization. Acting as both a strategist and hands-on builder, this role translates AI potential into practical solutions that improve operational efficiency, unlock the value of organizational data, and embed AI into the daily workflows of teams across the business.
 
 
 
 
 
 This role owns the full lifecycle of AI enablement - from identifying high-impact opportunities and designing AI strategies to configuring tools, training teams, managing governance, and measuring business outcomes.
 
 
 
 
 
 
 Key Outcomes &amp; Responsibilities
 
 
 <ul>
 <li>
 Identify and prioritize high-impact AI use cases across the enterprise.
 </li>
 <li>
 Assess AI readiness, current initiatives, and data maturity.
 </li>
 <li>
 Develop and communicate an enterprise AI strategy aligned to business goals.
 </li>
 <li>
 Deliver quick-win pilots to demonstrate early value and build momentum.
 </li>
 <li>
 Lead staged rollout and configuration of enterprise AI tools.
 </li>
 <li>
 Build and deploy AI solutions (e.g., knowledge assistants, automation workflows).
 </li>
 <li>
 Partner with IT for secure integration and system optimization.
 </li>
 <li>
 Manage pilot programs, refine use cases, and scale successful initiatives.
 </li>
 <li>
 Design and deliver role-based AI training programs.
 </li>
 <li>
 Build internal AI champion networks and user communities.
 </li>
 <li>
 Execute change management strategies to ensure adoption and reduce resistance.
 </li>
 <li>
 Communicate AI value, purpose, and responsible usage across teams.
 </li>
 <li>
 Assess and improve enterprise data quality, accessibility, and integration.
 </li>
 <li>
 Collaborate with data teams to strengthen governance and hygiene.
 </li>
 <li>
 Ensure AI initiatives are based on trusted and compliant data sources.
 </li>
 <li>
 Implement AI governance, privacy, and ethical standards.
 </li>
 <li>
 Conduct audits of AI outputs, usage, and data to mitigate risk.
 </li>
 <li>
 Balance innovation with security, compliance, and brand safety.
 </li>
 <li>
 Track AI adoption, utilization, and business impact.
 </li>
 <li>
 Optimize AI tool allocation and ROI.
 </li>
 <li>
 Capture success stories and continuously improve AI capabilities.
 </li>
 </ul>
 
 
 
 
 
 Qualifications
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Business, IT, Data Science, or related field.
 </li>
 <li>
 Experience in enterprise software implementation, digital transformation, AI enablement, or product ownership.
 </li>
 <li>
 Hands-on experience configuring or implementing AI tools, chatbots, automation platforms, or SaaS solutions.
 </li>
 <li>
 Strong understanding of change management and technology adoption practices.
 </li>
 <li>
 Knowledge of data governance, privacy, and security considerations related to AI.
 </li>
 <li>
 Experience working with platforms such as Microsoft Copilot, Azure AI, OpenAI, or similar technologies.
 </li>
 <li>
 Familiarity with data integration, analytics platforms, or master data management practices.
 </li>
 <li>
 Certifications in AI governance, change management, or enterprise architecture.
 </li>
 </ul>
 
 
</div>

AI Adoption Manager

The Home Depot

<div><div>Position Purpose:
The Sr Machine Learning Engineer is responsible for designing, building, integrating, optimizing, and maintaining AI-powered applications that leverage generative models and overall product lifecycle for a product that our users love. Generative AI Engineers are expected to collaborate closely with teammates as they develop and deliver user stories while supporting AI-powered products as they evolve. Generative AI Engineers may design and implement applications using large language models (LLMs) and other generative models to embed intelligent capabilities directly into software products. Activities may include prompt engineering, model integration, building Retrieval-Augmented Generation (RAG) pipelines, and developing scalable AI services. The role may interact with business stakeholders, infrastructure teams, and development teams to ensure business requirements are effectively addressed through generative AI solutions. The role may also support evaluation, performance optimization, testing, and monitoring of AI systems in production. Additional responsibilities may include working with domain data, improving prompts and AI workflows, and creating documentation or enablement materials for generative AI solutions. 
 
Sr Generative AI Engineers should be able to work independently with minimal guidance, while collaborating with cross-functional teams of varying skill levels to design, deploy, and maintain production AI applications. This role may review submitted code and prompt implementations, providing feedback and improvements based on engineering and responsible AI best practices. 
Key Responsibilities:<ul><li>
70% Delivery and Execution - Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions; Documents, reviews, and ensures that all quality and change control standards are met; Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable; Writes custom code or scripts to automate infrastructure, monitoring services, and test cases; Writes custom code or scripts to do &quot;destructive testing&quot; to ensure adequate resiliency in production; Configures commercial off the shelf solutions to align with evolving business needs; Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively</li><li>
10% Learning - Participates in learning activities around modern software design, machine learning, and development core practices (communities of practice); Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations</li><li>
20% Support and Enablement - Fields questions from other product teams or support teams; Monitors tools and participates in conversations to encourage collaboration across product teams; Provides application support for software running in production; Proactively monitors production Service Level Objectives for products; Proactively reviews the Performance and Capacity of all aspects of production: code, infrastructure, data, message processing, and prediction quality</li></ul> 
Direct Manager/Direct Reports:<ul><li>
This Position typically reports to Software Engineer Manager or Sr. Software Engineer Manager</li><li>
This Position has 0 Direct Reports</li></ul> 
Travel Requirements:<ul><li>
Typically requires overnight travel 5% to 20% of the time.</li></ul> 
Physical Requirements:<ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul> 
Working Conditions:<ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul> 
Minimum Qualifications:<ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul> 
Preferred Qualifications:<ul><li>
3 - 5 years of relevant work experience 
Experience in Python and modern AI development frameworks 
Experience building Generative AI applications using large language models (LLMs) 
Experience with prompt engineering, prompt optimization, and prompt evaluation techniques 
Experience integrating AI models through APIs from platforms such as Google, OpenAI or Anthropic 
Experience with GenAI frameworks such as Google Agent Development Kit (ADK) 
Experience implementing Retrieval-Augmented Generation (RAG) pipelines using vector databases 
Experience working with vector databases such as google Vertex AI Search 
Experience with building conversational AI systems, or AI assistants 
Experience with responsible AI practices including bias mitigation and safety guardrails 
Experience working with graph databases, knowledge ingestion pipelines, and data mesh architectures to enable scalable, connected, and queryable AI knowledge systems. 
Experience implementing CI/CD pipelines, monitoring, and automated workflows for reliable AI model deployment and lifecycle management. 
Experience with monitoring, evaluation, and optimization of production AI systems 
Experience in Google Cloud Platform and AI/ML related components such as Vertex AI, BigQueryML, and Experience in effective data engineering practices and big data platforms such as BigQuery, Data Store, etc- Experience in a modern scripting language (preferably Python) 
Experience with GPU acceleration (i.e. CUDA and cuDNN) 
Experience in a front-end technology and framework such as Node.js, HTML, CCS, JavaScript, ReactJS, D3 
Experience in writing SQL queries against a relational database 
Familiarity with production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security 
Familiarity with cloud computing platform and associated automation patterns and machine learning services they provide 
Familiarity with defensive coding practices and patterns for high Availability 
Familiarity with A/B testing and effective REST design for scalable web services architecture 
Familiarity with advanced machine learning techniques such as NLP, convolutional neural networks, autoencoders, and embeddings generation and utilization.</li></ul> 
Minimum Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.</li></ul> 
Preferred Education:<ul><li>
No additional education</li></ul> 
Minimum Years of Work Experience:<ul><li>
2</li></ul> 
Preferred Years of Work Experience:<ul><li>
No additional years of experience</li></ul> 
Minimum Leadership Experience:<ul><li>
None</li></ul> 
Preferred Leadership Experience:<ul><li>
None</li></ul> 
Certifications:<ul><li>
None</li></ul> 
Competencies:<ul><li>
Global Perspective</li><li>
Manages Ambiguity</li><li>
Nimble Learning</li><li>
Self-Development</li><li>
Collaborates</li><li>
Cultivates Innovation</li><li>
Situational Adaptability</li><li>
Communicates Effectively</li><li>
Drives Results</li><li>
Interpersonal Savvy</li></ul>
Benefits offered include health care benefits, 401K, ESPP, paid time off, and success sharing bonus. For a full list of the various benefits The Home Depot offers, visit https://careers.homedepot.com/our-benefits.</div> 
Apply End Date: 05/11/2026</div>

Senior Machine Learning Engineer – Generative AI (Remote)

<div><div>Position Purpose:
The Staff Machine Learning Engineer is responsible for joining cross-functional teams (product, design, Engineering, infrastructure) to build innovative GenAI application experiences and overall product lifecycle for a product that our users love. The engineering process is highly collaborative. Staff ML Engineers are expected to pair daily as they work through user stories and support products as they evolve. 
Generative AI Engineers may design and implement applications using large language models (LLMs) and other generative models to embed intelligent capabilities directly into software products. Activities may include prompt engineering, model integration, building Retrieval-Augmented Generation (RAG) pipelines, and developing scalable AI services. The role may interact with business stakeholders, infrastructure teams, and development teams to ensure business requirements are effectively addressed through generative AI solutions. The role may also support evaluation, performance optimization, testing, and monitoring of AI systems in production. Additional responsibilities may include working with domain data, improving prompts and AI workflows, and creating documentation or enablement materials for generative AI solutions. 
Key Responsibilities:<ul><li>
45% Delivery and Execution - Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions, Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable; Configures commercial off the shelf solutions to align with evolving business needs; Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively</li><li>
15% Learning - Participates in learning activities around modern software design, machine learning, and development core practices (communities of practice); Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations; Attends conferences and learns how to apply new innovations and technologies where appropriate</li><li>
20% Strategy and Planning - Researches and analyzes business trends and behavioral data to identify opportunities for improvement and new initiatives; Leads the evaluation development and recommendation of specific technology products and platforms to provide cost-effective solutions that meet business and technology requirements; Researches and designs best fit infrastructure, network, database, security, and machine learning architectures for products; Proactively creates and maintains tools for monitoring and support; Participates in project planning and management across multiple efforts; Develops formal training courses</li><li>
20% Support and Enablement - Fields questions from other product teams or support teams; Monitors tools and participates in conversations to encourage collaboration across product teams; Provides application support for software running in production; Proactively monitors production Service Level Objectives for products; Proactively reviews the Performance and Capacity of all aspects of production: code, infrastructure, data, message processing, and prediction quality</li></ul> 
Direct Manager/Direct Reports:<ul><li>
This Position typically reports to Software Engineer Manager or Sr Software Engineer Manager</li><li>
This Position has 0 Direct Reports</li></ul> 
Travel Requirements:<ul><li>
Typically requires overnight travel 5% to 20% of the time.</li></ul> 
Physical Requirements:<ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul> 
Working Conditions:<ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul> 
Minimum Qualifications:<ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul> 
Preferred Qualifications:<ul><li>
5 - 7 years of relevant work experience</li><li>
Experience in Python and modern AI development frameworks</li><li>
Experience building Generative AI applications using large language models (LLMs)</li><li>
Experience with prompt engineering, prompt optimization, and prompt evaluation techniques</li><li>
Experience integrating AI models through APIs from platforms such as Google, OpenAI or Anthropic</li><li>
Experience with GenAI frameworks such as Google Agent Development Kit (ADK)</li><li>
Experience implementing Retrieval-Augmented Generation (RAG) pipelines using vector databases</li><li>
Experience working with vector databases such as google Vertex AI Search</li><li>
Experience with building conversational AI systems, or AI assistants</li><li>
Experience with responsible AI practices including bias mitigation and safety guardrails</li><li>
Experience working with graph databases, knowledge ingestion pipelines, and data mesh architectures to enable scalable, connected, and queryable AI knowledge systems.</li><li>
Experience implementing CI/CD pipelines, monitoring, and automated workflows for reliable AI model deployment and lifecycle management.</li><li>
Experience with monitoring, evaluation, and optimization of production AI systems</li><li>
Experience in Google Cloud Platform and AI/ML related components such as Vertex AI, BigQueryML, and Experience in effective data engineering practices and big data platforms such as BigQuery, Data Store, etc- Experience in a modern scripting language (preferably Python)</li><li>
Experience with GPU acceleration (i.e. CUDA and cuDNN)</li><li>
Experience in a front-end technology and framework such as Node.js, HTML, CCS, JavaScript, ReactJS, D3</li><li>
Experience in writing SQL queries against a relational database</li><li>
Experience in advanced machine learning techniques such as NLP, convolutional neural networks, autoencoders, and embeddings generation and utilization</li><li>
Experience in training machine learning models with extremely large datasets</li><li>
Experience with Data Analysis and Machine Learning Tools and Libraries like Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, tensorflow, pytorch, etc.</li><li>
Familiarity with production systems design including High Availability, Disaster Recovery, Performance, Efficiency, and Security</li><li>
Familiarity with cloud computing platform and associated automation patterns and machine learning services they provide</li><li>
Familiarity with defensive coding practices and patterns for high Availability</li><li>
Familiarity with A/B testing and effective REST design for scalable web services architecture</li><li>
Familiarity with advanced machine learning techniques such as NLP, convolutional neural networks, autoencoders, and embeddings generation and utilization</li><li>
Familiarity with advanced machine learning architectures GANs, GRU, LSTMs, RNNs, CNNs, style transfer</li></ul> 
Minimum Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.</li></ul> 
Preferred Education:<ul><li>
No additional education</li></ul> 
Minimum Years of Work Experience:<ul><li>
3</li></ul> 
Preferred Years of Work Experience:<ul><li>
No additional years of experience</li></ul> 
Minimum Leadership Experience:<ul><li>
None</li></ul> 
Preferred Leadership Experience:<ul><li>
None</li></ul> 
Certifications:<ul><li>
None</li></ul> 
Competencies:<ul><li>
Global Perspective</li><li>
Manages Ambiguity</li><li>
Nimble Learning</li><li>
Self-Development</li><li>
Collaborates</li><li>
Cultivates Innovation</li><li>
Situational Adaptability</li><li>
Communicates Effectively</li><li>
Drives Results</li><li>
Interpersonal Savvy</li></ul>
Benefits offered include health care benefits, 401K, ESPP, paid time off, and success sharing bonus. For a full list of the various benefits The Home Depot offers, visit https://careers.homedepot.com/our-benefits.</div> 
Apply End Date: 05/11/2026</div>

Staff Machine Learning Engineer – Generative AI (Remote)

<div><div>Position Purpose:
As a Manager, AI Platform Engineering, you will lead the development and evolution of our enterprise Generative AI platform, enabling scalable, secure, and high-impact AI capabilities across the organization. This role combines technical delivery leadership with strategic thinking, overseeing a team of engineers to build and operate GenAI platform services, agentic workflows, and multi-model orchestration.
You will partner with product, data, legal, cybersecurity, and business stakeholders to translate AI use case needs into scalable, reusable platform capabilities that drive enterprise-wide adoption and efficiency. You will ensure alignment with security, privacy, and governance standards while enabling successful delivery and commercialization at scale. In addition, you will collaborate with strategic vendors and internal platform teams to accelerate innovation and support a growing portfolio of AI solutions.
This role is critical to scaling AI adoption across the enterprise, balancing rapid innovation with operational excellence and responsible AI practices. 
Key Responsibilities:<ul><li>
30% Delivery &amp; Execution:</li><li>
Collaborates and pairs with product team members (UX, engineering, and product management) to create secure, reliable, scalable software solutions</li><li>
Documents, reviews and ensures that all quality and change control standards are met</li><li>
Writes custom code or scripts to automate infrastructure, monitoring services, and test cases</li><li>
Works with vendors and partners for the successful implementation of critical tooling and platforms</li><li>
Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively</li><li>
Contributes to enterprise-wide tools to drive destructive testing, automation, and engineering empowerment</li><li>
Evaluates new technologies for adoption across the enterprise</li><li>
Participates in and leads review board sessions to drive consistency across the enterprise</li><li>
Fills in on product teams for engineers who are out of the office</li><li>
10% Support &amp; Enablement:</li><li>
Fields questions from engineers, product teams, or support teams</li><li>
Monitors tools and participates in conversations to encourage collaboration across product teams</li><li>
Provides application support for software running in production</li><li>
Acts as a technical escalation point for the engineers on the team</li><li>
50% People:</li><li>
Provides leadership, mentoring, and coaching to Software Engineers</li><li>
Attracts, retains, and develops top talent to build a world class Software Engineering Team</li><li>
Conducts annual and mid-year reviews by reviewing individual development plans and team feedback</li><li>
Fosters collaboration with team members to drive consistency across product teams, and finds opportunities to expose engineers to career interests</li><li>
Acts as a proponent of modern software development practices</li><li>
Guides team members in strategy, alignment, analysis, and execution tasks within and across product teams</li><li>
Participates in and contributes to learning activities around modern software design and development core practices (communities of practice)</li><li>
10% Learning:</li><li>
Learns, through reading, tutorials, and videos, new technologies and best practices being used within other technology organizations</li><li>
Builds relationships with technology leaders at other companies to learn best practices and elegant solutions to common problems</li></ul> 
Direct Manager/Direct Reports:<ul><li>
Typically reports to the Software Engineer Sr. Manager, Technology Director or Sr. Director.</li></ul> 
Travel Requirements:<ul><li>
Typically requires overnight travel 5% to 20% of the time.</li></ul> 
Physical Requirements:<ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul> 
Working Conditions:<ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul> 
Minimum Qualifications:<ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li><li>
Mastery of an object oriented programming language (preferably Java)</li><li>
Must be legally permitted to work in the United States</li></ul> 
Preferred Qualifications:<ul><li>
8+ years of related work experience in software engineering, with at least 2 years focused on AI/ GenAI projects for large enterprises.</li><li>
Experience with modern software delivery practices, including CI/CD pipelines, containerization, and orchestration technologies (e.g., Docker, Kubernetes), with a strong understanding of deploying and operating scalable, production-grade systems.</li><li>
Experience designing or building AI agents and agent-based workflows, including orchestration of LLMs, tools, and external systems in production environments.</li><li>
Strong understanding of AI, machine learning, and software engineering concepts, demonstrated through recent certifications or project experience</li><li>
Proven track record of managing complex technical projects and leading junior engineering teams</li><li>
Deep experience with ad tech, streaming media platforms, and digital content delivery</li><li>
Familiarity with agile methodologies and project management tools (e.g., Jira, Trello, Monday)</li><li>
Experience with cloud platforms (e.g. Azure, GCP) for scalable AI system deployment</li><li>
Excellent problem-solving and analytical skills</li><li>
Strong communication skills with ability to explain AI and software engineering concepts to both technical and non-technical audiences</li><li>
Knowledge of privacy and security considerations in AI applications</li><li>
Understanding of AI ethics and responsible AI practices</li><li>
Strong leadership and mentoring abilities</li><li>
Excellent interpersonal and team collaboration skills</li><li>
Ability to think strategically about AI applications and their business impact</li><li>
Proactive and self-motivated with a passion for emerging AI technologies and software engineering practices</li><li>
Adaptable and able to thrive in a fast-paced, rapidly evolving AI and software development landscape.</li><li>
Bachelor's degree in Computer Science, Software Engineering, or related field.</li></ul> 
Minimum Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.</li></ul> 
Preferred Education:<ul><li>
No additional education</li></ul> 
Minimum Years of Work Experience:<ul><li>
5</li></ul> 
Preferred Years of Work Experience:<ul><li>
No additional years of experience</li></ul> 
Minimum Leadership Experience:<ul><li>
None</li></ul> 
Preferred Leadership Experience:<ul><li>
None</li></ul> 
Certifications:<ul><li>
None</li></ul> 
Competencies:<ul><li>
Attracts Top Talent: Attracting and selecting the best talent to meet current and future business needs</li><li>
Balances Stakeholders: Anticipating and balancing the needs of multiple stakeholders</li><li>
Builds Effective Teams: Building strong-identity teams that apply their diverse skills and perspectives to achieve common goals</li><li>
Business Insight: Applying knowledge of business and the marketplace to advance the organization's goals</li><li>
Collaborates: Building partnerships and working collaboratively with others to meet shared objectives</li><li>
Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences</li><li>
Develops Talent: Developing people to meet both their career goals and the organization's goals</li><li>
Drives Engagement: Creating a climate where people are motivated to do their best to help the organization achieve its objectives</li><li>
Drives Vision and Purpose: Painting a compelling picture of the vision and strategy that motivates others to action</li><li>
Manages Ambiguity: Operating effectively, even when things are not certain or the way forward is not clear</li><li>
Organizational Savvy: Maneuvering comfortably through complex policy, process, and people-related organizational dynamics</li><li>
Situational Adaptability: Adapting approach and demeanor in real time to match the shifting demands of different situations</li></ul>
Benefits offered include health care benefits, 401K, ESPP, paid time off, and success sharing bonus. For a full list of the various benefits The Home Depot offers, visit https://careers.homedepot.com/our-benefits.</div> 
Apply End Date: 05/12/2026</div>

Manager, AI Platform Engineering (Remote)

<div>Position Purpose:
The Senior Analyst, Program Management - AI / Automation Enablement, is the functional lead and execution engine for high-impact AI-powered solutions. This role bridges the gap between business strategy and technical delivery, translating the needs of Online Merchants and Brand Advocates into scalable, automated workflows.
Reporting to the Senior Manager, this individual is responsible for the day-to-day management of a &quot;Balanced Team&quot; (Data Science, IT, and UX), ensuring that technical roadmaps are aligned with business realities. The Senior Analyst combines a strong grasp of data architecture and SQL/data warehousing with a product-centric mindset to drive the development, integration, and adoption of agentic systems across a 1&ndash;2 year program horizon.
Key Responsibilities:<ul><li>
25% Cross-Functional Coordination - Balanced Team Leadership: Lead the daily cadence and project rhythm for a matrixed team of Data Science, IT, and UX partners, ensuring high-performance and program rigor. Collaborative Best Practices: Actively contribute to the solution design process, voicing opinions on best practices and fostering a culture of continuous improvement within the technical team. Dependency Management: Proactively identify and resolve impediments across indirect support teams, ensuring that cross-functional roadmaps remain synchronized.</li><li>
30% Program Execution &amp; Sprint Delivery - Roadmap Management: Orchestrate the phased delivery of AI solutions, balancing immediate sprint needs with the long-term (1&ndash;2 year) strategic goals of the program. Execution Rigor: Manage program tracking against the roadmap, focusing on schedule, scope, and resource alignment while translating technical risks into potential business impacts. Integration Strategy: Coordinate the seamless embedding of AI tools into existing merchant workflows, ensuring that solutions are user-friendly and technically scalable.</li><li>
15% Stakeholder Alignment &amp; Value Realization - User Advocacy: Serve as the primary point of contact for Online Merchants and Brand Advocates, managing expectations and communicating transparent status updates. Adoption &amp; Change Management: Support the development of change management plans to ensure business teams effectively adopt and trust new AI-driven processes. Value Tracking: Monitor tool performance and report on business outcomes (e.g., efficiency gains, ROI, and decision-making accuracy) to leadership and executive stakeholders.</li><li>
30% Technical Product Ownership &amp; Solutioning - Workflow Translation: Partner with business users to deconstruct manual processes into structured logic, identifying where AI and automation can drive the most operational leverage. Data Fluency: Leverage SQL and data warehouse knowledge to understand underlying data structures, validate model inputs, and ensure technical solutions are built on a sound architectural foundation. Technical Requirement Definition: Translate ambiguous business &quot;pain points&quot; into high-quality technical requirements, user stories, and acceptance criteria for Data Science and Engineering teams. Product Quality Assurance: Act as a primary tester for AI outputs, ensuring the solution meets the rigorous accuracy and reliability standards required by the business.</li></ul>
Direct Manager/Direct Reports:
<ul><li>This Position typically reports to Senior Manager.
</li><li>This Position does not have direct reports.</li></ul>
Travel Requirements:<ul><li>
Typically requires overnight travel less than 5% of the time.
</li></ul>Physical Requirements:
<ul><li>Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions, there may be a need to move or lift light articles.</li></ul>
Working Conditions:
<ul><li>Located in a comfortable indoor area; any unpleasant conditions would be infrequent and not objectionable.</li></ul>
Minimum Qualifications:
<ul><li>Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li><li>
4+ years of professional experience in a Product Management, Business Analysis, or Technical Program Management capacity.</li><li>
2+ years of direct experience contributing to the implementation of AI, ML, or Automation solutions within business workflows.</li><li>
Demonstrated experience leading cross-functional &quot;Balanced Teams&quot; (Data Science, Engineering, UX) in an agile or sprint-based environment.</li><li>
Technical Data Proficiency: Proficiency in SQL and experience navigating cloud data warehouses to analyze data structures and validate solution inputs.</li><li>
Business Translation: Proven ability to translate ambiguous business &quot;pain points&quot; into structured technical requirements and user stories.</li><li>
Solution Lifecycle Management: Experience driving a technical product from initial requirements through UAT, deployment, and user adoption.</li></ul>
Preferred Qualifications:<ul><li>
Bachelor&rsquo;s degree in a relevant field (Computer Science, Data Analytics, Business Information Systems, or equivalent).</li><li>
Technical Product Ownership: Prior experience working as a Product Owner or Lead Analyst within a modern software design and development team.</li><li>
Process Optimization: Demonstrated experience re-engineering manual business processes into automated or AI-enabled workflows.</li><li>
AI Ecosystem Knowledge: Familiarity with the components of Generative AI systems, including an understanding of how models integrate with enterprise applications via APIs or orchestration layers.</li><li>
Data Architecture: Knowledge of data modeling concepts and how data flows from source systems to AI model endpoints.</li><li>
Retail or E-commerce Experience: Prior experience supporting Online Merchants, Brand Advocates, or similar business-side stakeholders in a large enterprise environment.</li><li>
Change Management: Experience developing training materials and documentation to drive the adoption of new technical tools.</li></ul>
Minimum Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.</li></ul>
Preferred Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.</li></ul>
Minimum Years of Work Experience:<ul><li>
2</li></ul>
Preferred Years of Work Experience:
<ul><li>4</li></ul>
Minimum Leadership Experience:<ul><li>
No previous leadership experience</li></ul>
Preferred Leadership Experience:
<ul><li>No previous leadership experience</li></ul>
Certifications:
<ul><li>Insurance licensing as required by state</li></ul>
Competencies:
<ul><li>Action Oriented</li><li>
Collaborates</li><li>
Drives Engagement</li><li>
Ensures Accountability</li><li>
Communicates Effectively</li><li>
Customer Focus</li><li>
Drives Results</li><li>
Manages Conflict</li></ul></div>

Sr Analyst, Program Management AI Automation Enablement

<div>Position Purpose:
The Data Scientist is responsible for supporting data science initiatives that drive business profitability, increased efficiencies, improve automation using AI and improved customer experience. This role applies industry-leading Agentic AI capabilities for creatively solve business problems in the Contact Center space. Data Scientists are also responsible for ensuring that developed codes are documented into a library of reusable algorithms. Based on the specific data science team, this role would need to be knowledgeable in one or more data science specializations, such as NLP, Conversational AI, Information Retrieval, Generative AI or search. 
As a Data Scientist, you will also be responsible for applying advanced analytics methods and algorithms for identifying trends and providing business solutions. This role is expected to present insights and recommendations to non-technical audiences and explain the benefits and impacts of the recommended solutions. In addition, Data Scientists collaborate with business partners and cross-functional teams, requiring effective communication skills, building relationships, and focus on understanding the overall business area being supported. 
Key Responsibilities:<ul><li>
55% Solution Development - Design and develop algorithms and models to use against large datasets to create business insights; Participates in large data analytics project teams by serving as a technical lead for analytics projects; May lead small projects and work independently on solution development; Execute tasks with high levels of efficiency and quality; Make appropriate selection, utilization and interpretation of advanced analytical methodologies</li><li>
20% Communicating Results - Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners; Present recommendations in a confident manner in order to influence execution of recommendation; Prepare reports, updates and/or presentations related to progress made on a project or solution; Clearly communicate impacts of recommendations to drive alignment and appropriate implementation</li><li>
10% Business Collaboration - Incorporate business knowledge into solution approach; Effectively develop trust and collaboration with internal customers and cross-functional teams; Work with project teams and business partners to determine project goals</li><li>
15% Technical Exploration &amp; Development - Seek further knowledge on key developments within data science, technical skill sets, and additional data sources; Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects; Build and maintain library of reusable algorithms for future use, ensuring developed codes are documented</li></ul> 
Direct Manager/Direct Reports:<ul><li>
This position typically reports to Manager or above</li><li>
This position has 0 Direct Reports</li></ul> 
Travel Requirements:<ul><li>
Typically requires overnight travel less than 10% of the time.</li></ul> 
Physical Requirements:<ul><li>
Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.</li></ul> 
Working Conditions:<ul><li>
Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.</li></ul> 
Minimum Qualifications:<ul><li>
Must be eighteen years of age or older.</li><li>
Must be legally permitted to work in the United States.</li></ul> 
Preferred Qualifications:<ul><li>
Masters in a quantitative field (Computer Science, Math, Statistics, etc.) or equivalent work experience</li><li>
4+ years of industry experience in Machine Learning and AI (specifically Conversational AI)</li><li>
Prior background and experience in building Generative AI based solutions for industry is a plus</li><li>
Working knowledge of Microsoft Excel and Power Point</li><li>
Experience in a modern scripting language (preferably Python)</li><li>
Proficient running queries against data (preferably with Google BigQuery or SQL)</li><li>
Proficient utilizing statistical techniques to identify key insights that help solve business problems</li><li>
Knowledgeable in Prescriptive Modeling like optimization, computer vision, recommendation, search or NLP</li><li>
Demonstrated experience in Machine Learning, Conversational AI, predictive modeling, data mining and data analysis</li></ul> 
Minimum Education:<ul><li>
The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.</li></ul> 
Preferred Education:<ul><li>
No additional education</li></ul> 
Minimum Years of Work Experience:<ul><li>
3</li></ul> 
Preferred Years of Work Experience:<ul><li>
No additional years of experience</li></ul> 
Minimum Leadership Experience:<ul><li>
None</li></ul> 
Preferred Leadership Experience:<ul><li>
None</li></ul> 
Certifications:<ul><li>
None</li></ul> 
Competencies:<ul><li>
Action Oriented: Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm</li><li>
Business Insight: Applying knowledge of the business and the marketplace to advance the organization's goals</li><li>
Collaborates: Building partnerships and working collaboratively with others to meet shared objectives</li><li>
Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences</li><li>
Customer Focus: Building strong customer relationships and delivering customer-centric solutions</li><li>
Drives Results: Consistently achieving results, even under tough circumstances</li><li>
Nimble Learning: Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder</li><li>
Optimizes Work Processes: Knowing the most efficient and effective processes to get things done, with a focus on continuous improvement</li><li>
Plans and Aligns: Planning and prioritizing work to meet commitments aligned with organizational goals</li><li>
Self-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels</li></ul></div>

Data Scientist, Contact Center AI

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