conversational ai engineer

One Network

AI Engineer to lead the development of intelligent AI solutions, including chatbots, resume parsers, document automation tools, and conversational AI systems. You will own the end-to-end AI pipeline&mdash;from research and prototyping to deployment and optimization&mdash;delivering scalable, production-ready AI applications that improve efficiency and user experience..Duties &amp; Responsibilities<ul><li>Design and develop AI-powered chatbots and virtual assistants for customer support, internal workflows, and conversational interfaces.</li><li>Build intelligent document processing systems, including resume/CV parsers, contract analyzers, and automated data extraction pipelines.</li><li>Develop LLM-based agents for question-answering, compliance validation, sentiment analysis, and content summarization.</li><li>Create and optimize RAG (Retrieval-Augmented Generation) systems for accurate, context-aware information retrieval and generation.</li><li>Fine-tune and deploy open-source and proprietary LLMs (e.g., Llama, Mistral) for domain-specific applications.</li><li>Implement end-to-end AI solutions using Python and frameworks like PyTorch, TensorFlow, or equivalent.</li><li>Apply Computer Vision tools (YOLO, OpenCV) for document layout analysis and image-based data extraction.</li><li>Collaborate with cross-functional teams to integrate AI solutions into production systems.</li><li>Continuously research and adopt emerging AI technologies to enhance system capabilities.</li></ul>QualificationsBachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Artificial Intelligence, Data Science, or related field.Required Skills<ul><li>3&ndash;5 years of hands-on experience in AI/ML development, preferably in NLP, document automation, or conversational AI.</li><li>Strong proficiency in Python and AI/ML frameworks (PyTorch, TensorFlow, HuggingFace).</li><li>Experience with resume parsing, document automation, or information extraction systems.</li><li>Familiarity with LLM architectures, fine-tuning, and deployment.</li><li>Knowledge of Computer Vision techniques and tools for document or image processing.</li><li>Excellent problem-solving skills and ability to deliver production-ready AI applications.</li><li>Strong communication skills and ability to work collaboratively in a fast-paced environment.</li></ul>Job Type: Full-timePay: Rs130,000.00 - Rs160,000.00 per monthWork Location: In person

AI Lead Engineer

Openkyber

<div>Position Summary Looking for a strong Gen AI architect and hands on engineer who can work on advanced AWS Novasonic models for Conversational AI. this persons/s will directly report to me. Prefer Contract to hire. seeking onshore if you can look in Charlotte with banking expertise.
Required Skillset Resume Search Keywords (Short &amp; Strong):
Core GenAI &amp; LLM Skills 
Hands on expertise with Amazon Nova / Nova 2 foundation models on Amazon Bedrock, including multimodal and high reasoning variants. Experience customizing or fine tuning LLMs using Bedrock + SageMaker SFT pipelines. Strong LLM prompt engineering, optimization, prompt routing, and evaluation skills. Conversational AI (Chat + Voice)
Proven ability designing and building conversational agents with Amazon Lex V2 (Assisted NLU, multi turn dialogs, analytics). Hands on integration of Lex with Amazon Connect for IVR/voice bots and contact center automation.
Experience leveraging Bedrock Knowledge Bases to enable Retrieval Augmented Generation (RAG) for grounded responses.
Bedrock Agents / Agentic Systems 
Experience building Amazon Bedrock Agents with ReAct planning or custom orchestration strategies. Ability to configure action groups (API schema + Lambda functions) and design multi step task workflows. Understanding of Bedrock AgentCore for deterministic policy enforcement and safe autonomous execution.
Governance, Safety &amp; Security 
Implementation of Amazon Bedrock Guardrails , including harmful content filtering, denied topics, PII redaction, and grounding checks. Knowledge of AI governance for regulated industries (banking/finance), including safety policies and audit controls. Strong IAM, encryption, data isolation, and compliance patterns for enterprise AI.
RAG, Data &amp; Integrations 
Building RAG systems using Bedrock Knowledge Bases (document ingestion, chunking, embedding. Integrations using AWS Lambda, API Gateway, DynamoDB, S3, and event driven patterns to support conversational flows. Experience optimizing LLM latency and cost via model selection, caching, and cross region inference.
Experience with Connect + Lex + Bedrock Agent architectures for real time voice assistants. Understanding of near real time conversational patterns informed by Nova powered speech capabilities.
Operational Excellence (MLOps / LLMOps) 
Strong skills in LLM evaluation, monitoring, telemetry, and continuous quality measurement. Experience with Lex Analytics dashboards for intent/slot performance. Ability to version prompts, guardrails, agent instructions, and model configs.
Optional Search Keywords (Good-to-Have) 
&quot;Bedrock Agents custom orchestration&quot; &quot;Lex V2 Assisted NLU / QnAIntent generative AI&quot; &quot;Nova 2 reasoning model experience&quot; &quot;Amazon Connect AI integration&quot; &quot;AgentCore policy enforcement / governance&quot; &quot;Multi-agent orchestration frameworks&quot;
For applications and inquiries, contact: hirings@openkyber.com</div>

Generative AI Intern

Valence

<div>
 Valence has built the only AI native coaching platform for enterprise, offering personalized, expert, and human-like guidance and support to any leader or employee. We&rsquo;re not just talking about the future of work &mdash; we&rsquo;re building it now, with the most innovative Fortune 500 companies across healthcare, financial services, manufacturing, and technology.
 
 
 Our focus is on the problems that actually decide whether AI changes how organizations operate &mdash; the ones with no playbook, no obvious answers, and no guarantee of success. If you want to be part of the small group that defines how AI transforms the future at a global scale, this is your chance.
 
 
 And this isn&rsquo;t for everyone. We&rsquo;re not looking for people who want predictability or incremental progress. We only want those who are restless at the edge of what&rsquo;s possible, who get bored when things feel &ldquo;done,&rdquo; and who are driven to redefine what AI can mean for leaders, companies, and the world. Because at Valence, the work worth doing is the kind that redefines work itself.
 
 
 
 The Role
 
 
 
 This role is a Machine Learning Engineer role for our conversational AI coaching product designed for Fortune 500 enterprises, reporting into our Head of AI. In this role you will implement, and optimize machine learning models that power our coaching insights and recommendations. This role is focused on the development and optimization of machine learning models and algorithms, optimizing the underlying ML infrastructure and model development. This role will directly impact our product's core and shape the future of AI-driven leadership coaching for Fortune 500 enterprises.
 
 
 
 About Valence
 
 
 
 We're the only company pioneering leadership coaching for large enterprises in an AI-first way. Our mission is to transform how the world's biggest companies approach learning and development, helping teams work better together through AI-powered personalization that adapts to individual goals and organizational culture using the latest advances in machine learning and natural language processing.
 
 
 We've been featured in Harvard Business Review, TIME, World Economic Forum, Financial Times, Forbes and an Inc. 5000 fastest-growing private companies in America. Our clients represent the most diverse and sophisticated enterprise AI implementations globally, including Coca-Cola, Delta, Nestl&eacute;, General Mills, Schneider Electric, Deutsche Telekom, AstraZeneca, Prudential, CVS and Bristol Myers Squibb.
 
 
 Working at Valence means you'll work directly with Fortune 500 technology leaders, building expertise through the most complex enterprise deployments while gaining insight into diverse organizational approaches to AI transformation. These aren't just any enterprise clients - they're the companies defining what AI-first business transformation looks like across every major industry.
 
 
 
 What You'll Do
 
 
 
 <ul>
 <li>
 You will develop scalable data pipelines, optimize models for performance and accuracy, and evaluate them to ensure they are production-ready.
 </li>
 <li>
 Develop, design and implement improvements in user experience in conversational interactions leveraging LLMs in new ways to advance product goals.
 </li>
 <li>
 Work with the product team to analyze user behavior and prioritize evolving requirements.
 </li>
 <li>
 Experiment at a high velocity, conducting statistical analyses, to optimize the end user experience
 </li>
 <li>
 Research and development on new Conversational AI approaches leveraging cutting edge LLM/NLP advancements.
 </li>
 <li>
 Documentation of models, prompts, and processes to increase replicability and drive quality improvements.
 </li>
 <li>
 Stay current with the latest leading research advancements in ML, LLMs, and Conversational AI
 </li>
 <li>
 Support other coding and feature development where required
 
 
 </li>
 </ul>
 
 What We're Looking For
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Engineering, Mathematics, related field, or equivalent experience
 </li>
 <li>
 3+ years of professional experience (or equivalent) in software engineering, AI/ML development (ideally including a Master's or Ph.D. in Computer Science, ML, Data Science, or a related field)
 </li>
 <li>
 Practical experience and theoretical knowledge of language technologies such as: dialogue/conversational systems, NLP, and Information Retrieval
 </li>
 <li>
 Strong foundation in data structures, algorithms, and software engineering principles.
 </li>
 <li>
 Proficiency in Python and relevant deep learning frameworks; training (e.g. PyTorch, Tensorflow, JAX, Hugging Face Transformers/Adapters), serving (e.g., Hugging Face TGI//outlines, vLLM)
 </li>
 <li>
 Experience with LLM model development and deployment ideally including experience with model distillation, supervised fine-tuning using RLHF/DPO, and automatic prompt tuning (e.g. DSPy, TextGrad)
 </li>
 <li>
 Experience with cloud deployment of ML systems (e.g., AWS, GCP, Azure) including and open systems (e.g. Docker and Kubernetes) and associated ML services.
 </li>
 <li>
 Strong analytical and problem-solving skills
 </li>
 <li>
 Experience structuring and running data-backed experiments
 </li>
 <li>
 Strong written and verbal communication skills
 </li>
 <li>
 Exposure to early-stage startups, preferably B2B SaaS
 
 
 </li>
 </ul>
 
 What You'll Get
 
 
 
 <ul>
 <li>
 Ownership &amp; Rapid Growth
 </li>
 <li>
 Outsized missions from day one, with direct responsibility for company-defining projects
 </li>
 <li>
 Work alongside the executive team with transparency into strategy and decision-making
 </li>
 <li>
 Influence on direction through real-time customer feedback and market insights
 </li>
 <li>
 AI-First Operator
 </li>
 <li>
 Work directly with cutting-edge AI models and next-generation platforms
 </li>
 <li>
 Build expertise in enterprise AI implementation across Fortune 500 companies and multiple industries
 </li>
 <li>
 Establish yourself as a recognized leader among peers in shaping how AI transforms work at a global scale
 </li>
 <li>
 Compensation
 </li>
 <li>
 Competitive salary including base + bonuses
 </li>
 <li>
 Comprehensive health coverage (medical, dental, vision) from day one
 </li>
 <li>
 Generous PTO, company-wide R&amp;R shutdowns, and paid parental leave
 </li>
 <li>
 Retirement plan support for US and global employees
 </li>
 <li>
 Equity
 </li>
 <li>
 Meaningful ownership in a venture-backed company at a growth inflection point
 </li>
 <li>
 Financial upside that comes from scaling fast
 </li>
 <li>
 Top-up grants as we scale and you deliver exceptional performance &mdash; your compensation grows alongside your impact
 </li>
 <li>
 Top-Performing Culture
 </li>
 <li>
 A culture built for top talent: intensity to win, growth without limits, and a team that solves hard problems and celebrates big wins together
 
 
 </li>
 </ul>
 
 Learn more about us and meet our team
 
 
 here
 
 
 
 
 Location and Work Environment
 
 
 
 If candidates are based in NYC or Toronto they can work hybrid in our offices, otherwise this role can be remote. Candidates must be comfortable working with colleagues in different time zones (UK), and have valid travel documents without work authorization restrictions in the US.
 
 
 
 Diversity and Inclusion
 
 
 
 We are dedicated to creating a diverse and inclusive environment where everyone feels valued and supported. We encourage applications from candidates of all backgrounds and offer accommodations upon request throughout the hiring process. If you have any questions, please reach out to Allison Langille, Head of People, at jobs@valence.co.
 
 
 
 Employment Verification &amp; Commitment
 
 
 
 We use third-party services to verify employment history, education, and other information relevant to your candidacy. Employment is contingent upon the successful completion of these verification checks. This is a full-time role that requires a high level of focus, availability, and commitment. Employees may not hold concurrent full-time employment with another organization while employed at Valence. Any outside consulting, advisory, freelance, or other professional work must be disclosed and approved in advance and must not interfere with job responsibilities, availability, performance, or create a conflict of interest - including risks related to confidentiality, intellectual property, or competition.
 
 
</div>

Machine Learning Engineer

Zoom Communications

<div><div><ul><li>R17982
</li></ul></div><div><ul><li>Remote, United States
</li></ul></div><div><ul><li>Product
</li></ul></div><div><ul><li>Full time</li></ul></div></div>
 <div>What you can expect
We are looking for a Product Engineer focused on customer deployments for Agentic Voice AI to lead the deployment of next generation Zoom Virtual Agents. Leveraging LLMs and agentic frameworks to build highly automated conversational voice and chat agents for strategic customers.
About the Team
The Zoom Virtual Agent team is dedicated to building state-of-the-art conversational AI solutions that resolve customer issues quickly and efficiently. Play a critical role in developing metrics, intelligence, and evaluation systems that drive continuous improvement using advanced LLMs and data science.
Responsibilities<ul>
<li>
Leading multi-step conversational workflow design using agentic frameworks to enable LLM agents to execute complex multi-tool tasks, including database checks and transactions.</li>
<li>
Fine-tune the underlying Large Language Models (LLMs) to ensure optimal performance, low latency, and minimal hallucination in real-time voice conversations.</li>
<li>
Developing and deploy custom full-stack Python/JS to connect the agent's decision-making with customer back-end systems (CRM, ERP, knowledge bases) as external &quot;tools.&quot;</li>
<li>
Crafting and iterating advanced LLM prompts (e.g., chain-of-thought, few-shot) to guide conversation, maintain context, and ensure accurate tool use in live voice interactions.</li>
<li>
Prompt-engineer TTS components (e.g., ElevenLabs, Azure, Cartesia) to fine-tune tone, pacing, emphasis, and prosody to context and brand.</li>
<li>
Conducting A/B testing and performance monitoring on TTS output, ensuring high acoustic quality, latency requirements, and emotional appropriateness.</li>
<li>
Acting as the embedded technical expert, working directly with customer engineering and executive teams to map complex business goals to agentic solutions.</li>
<li>
Managing end-to-end production deployments with continuous optimization and performance tuning driven by real-world voice traffic data.</li>
<li>
Translating field challenges, LLM failure modes, and TTS needs into actionable input for Core Engineering and Product to drive platform innovation.</li>
</ul>
What we&rsquo;re looking for<ul>
<li>
Have 3+ years in a technical, customer-facing role (FDE, Solutions Architect, Technical Lead) focused on AI/ML or highly technical SaaS products.</li>
<li>
Possess proven hands-on experience designing and deploying LLM solutions using modern agentic frameworks (e.g., LangChain, LlamaIndex, internal tools).</li>
<li>
Have deep expertise in voice stacks and TTS integration, using prompt engineering to control prosody, tone, and pacing.</li>
<li>
Possess proven ability to write and manage iterative prompts guiding both generative text logic and speech synthesis quality (prosody and emotion).</li>
<li>
Have solid software development skills in Python for prototyping, API integration, and production deployment, coupled with familiarity with modern DevOps practices.</li>
<li>
Own exceptional ability to distill complex AI and engineering concepts into clear, actionable insights for both technical teams and C-level executives.</li>
</ul>
Salary Range or On Target Earnings:
Minimum:
$124,000.00
Maximum:
$271,200.00
In addition to the base salary and/or OTE listed Zoom has a Total Direct Compensation philosophy that takes into consideration; base salary, bonus and equity value.
Note: Starting pay will be based on a number of factors and commensurate with qualifications &amp; experience.
We also have a location based compensation structure; there may be a different range for candidates in this and other locations.
Ways of Working 
Our structured hybrid approach is centered around our offices and remote work environments. The work style of each role, Hybrid, Remote, or In-Person is indicated in the job description/posting.
Benefits 
As part of our award-winning workplace culture and commitment to delivering happiness, our benefits program offers a variety of perks, benefits, and options to help employees maintain their physical, mental, emotional, and financial health; support work-life balance; and contribute to their community in meaningful ways.
About Us 
Zoomies help people stay connected so they can get more done together. We set out to build the best collaboration platform for the enterprise, and today help people communicate better with products like Zoom Contact Center, Zoom Phone, Zoom Events, Zoom Apps, Zoom Rooms, and Zoom Webinars. 
We&rsquo;re problem-solvers, working at a fast pace to design solutions with our customers and users in mind. Find room to grow with opportunities to stretch your skills and advance your career in a collaborative, growth-focused environment. 
Our Commitment
At Zoom, we believe great work happens when people feel supported and empowered. We&rsquo;re committed to fair hiring practices that ensure every candidate is evaluated based on skills, experience, and potential. If you require an accommodation during the hiring process, let us know&mdash;we&rsquo;re here to support you at every step.
We welcome people of different backgrounds, experiences, abilities and perspectives including qualified applicants with arrest and conviction records and any qualified applicants requiring reasonable accommodations in accordance with the law.
If you need assistance navigating the interview process due to a medical disability, please submit an Accommodations Request Form and someone from our team will reach out soon. This form is solely for applicants who require an accommodation due to a qualifying medical disability. Non-accommodation-related requests, such as application follow-ups or technical issues, will not be addressed.
Think of this opportunity as a marathon, not a sprint! We're building a strong team at Zoom, and we're looking for talented individuals to join us for the long haul. No need to rush your application &ndash; take your time to ensure it's a good fit for your career goals. We continuously review applications, so submit yours whenever you're ready to take the next step.
#LI-Remote</div>

Forward Deployment Engineer

Wells Fargo

<div><div><h2 class="jobSectionHeader">About this role</h2>
Wells Fargo is seeking a senior engineering leader to support Fargo, the enterprise Virtual Assistant and GenAI platform, which powers conversational, AI‑driven experiences across multiple lines of business. This role will focus on large‑scale platform engineering, AI enablement, and cross‑enterprise integration, operating at the intersection of architecture, security, and business transformation.<h2 class="jobSectionHeader">
In this role, you will:</h2><ul><li>
Act as a technical and architectural advisor to senior leadership for an enterprise GenAI and conversational platform, influencing design and implementation of highly complex applications, APIs, AI/ML integrations, streaming technologies, security controls, and cloud‑native platforms across multiple enterprise teams</li><li>
Lead strategy and resolution of complex, cross‑domain challenges involving GenAI, conversational platforms, API enablement, authentication/authorization, data domains (EDE), and enterprise compliance, delivering scalable, long‑term solutions</li><li>
Translate advanced engineering experience and a deep understanding of enterprise AI strategy, platform roadmaps, and business objectives into pragmatic, production‑ready technical solutions</li><li>
Provide vision and direction on GenAI adoption, including LLM integration patterns, prompt orchestration, model governance, observability, and responsible AI controls within an enterprise AI platform</li><li>
Drive architectural alignment for real‑time and near‑real‑time experiences, including streaming (e.g., HTTP 1.1 SSE), event‑driven integrations, and performance optimization for conversational entry points</li><li>
Partner closely with product, security, platform, and data teams to ensure enterprise AI solutions meet security, privacy, resiliency, and regulatory standards</li><li>
Maintain awareness of industry best practices in AI platforms, conversational systems, and cloud‑native engineering, recommending innovations that improve customer experience, developer productivity, and operational efficiency</li><li>
Strategically engage with engineering leaders, architects, and executives across the enterprise, serving as a trusted expert and thought leader for enterprise GenAI initiatives</li></ul><h2 class="jobSectionHeader">
Required Qualifications:</h2><ul><li>
7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education</li><li>
3+ years of experience in AI/ML technologies, including Large Language Models (LLMs), prompt engineering, model integration, or applied machine learning in production environments</li><li>
3+ years of experience with distributed streaming and event‑driven architectures, using technologies such as Kafka, Flink, or similar real‑time data processing frameworks</li><li>
5+ years of experience in database design and data architecture, including relational and/or NoSQL systems, data modeling, and high‑throughput data access patterns</li><li>
7+ years of programming experience in Java and/or Python, building scalable, production‑grade backend systems and APIs</li><li>
3+ years of experience designing and integrating APIs and microservices, including REST/gRPC services and service orchestration patterns</li><li>
3+ years experience working with cloud‑native platforms and architectures, including containerization, distributed systems, and scalable deployment models</li><li>
5+ years experience with system design and architecture for high‑scale applications, including performance optimization, fault tolerance, and resiliency</li><li>
3+ years working and understanding of security, data privacy, and governance considerations, especially in regulated enterprise environments</li></ul><h2 class="jobSectionHeader">
Desired Qualifications:</h2><ul><li>
Experience with conversational platforms, chatbots, or virtual assistants at enterprise scale</li><li>
Hands‑on experience with GenAI / LLM integrations, including prompt management, orchestration layers, and AI safety or governance controls</li><li>
Knowledge of API security, OAuth, authentication/authorization platforms, and reverse‑proxy or gateway patterns</li><li>
Experience working with streaming or real‑time technologies to support low‑latency user experiences</li><li>
Familiarity with enterprise data domains (e.g., EDE) and data access patterns for AI‑driven applications</li><li>
Ability to operate effectively in highly matrixed organizations, influencing without direct authority</li></ul><h2 class="jobSectionHeader">
Job Expectations:</h2><ul><li>
Drive architectural consistency and technical excellence across Fargo integrations</li><li>
Balance innovation with risk management, compliance, and operational stability</li><li>
Communicate complex technical concepts clearly to executive and non‑technical stakeholders</li><li>
Support cross‑LOB onboarding and adoption of Fargo capabilities</li><li>
This position offers a hybrid work schedule</li><li>
This position is not eligible for Visa sponsorship or transfer of visa</li><li>
Relocation assistance is not available for this position</li></ul>
Location:<ul><li>
300 S. Brevard St., Charlotte, NC</li></ul>
Pay range:
Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to demonstrated examples of prior performance, skills, experience, or work location. Employees may also be eligible for incentive opportunities.
159,000.00 - 254,000.00 USD Annual
Benefits:<ul><li>
Information about Wells Fargo's US employee benefits</li><li>
Information about Wells Fargo's International employee benefits</li></ul>
Posting End Date:
03 Apr 2026<ul><li>Job posting may come down early due to volume of applicants.</li></ul></div></div>

Principal Engineer

YO IT CONSULTING

<div>Work Mode: Remote 
Engagement Type: Independent Contractor 
Schedule: Full-Time or Part-Time Contract
Language Requirement: Fluent English
Role :
Partners with leading AI teams to improve the quality, usefulness, and reliability of general-purpose conversational AI systems. These systems are used across a wide range of everyday and professional scenarios, and their effectiveness depends on how clearly, accurately, and helpfully they respond to real user questions.
In engineering-related contexts, conversational AI systems must demonstrate accurate applied reasoning, quantitative precision, and practical problem-solving aligned with real-world systems. This project focuses on evaluating and improving how models reason about and explain engineering concepts across multiple disciplines.
What You&rsquo;ll Do
<ul><li>Write and refine prompts to guide model behavior in engineering scenarios
</li><li>Evaluate LLM-generated responses to engineering-related queries for technical accuracy, applied reasoning, and completeness
</li><li>Conduct fact-checking and verify any technical claims using authoritative public sources and domain knowledge
</li><li>Annotate model responses by identifying strengths, areas of improvement, and factual or conceptual inaccuracies
</li><li>Assess clarity, structure, and appropriateness of explanations for different audiences
</li><li>Ensure model responses align with expected conversational behavior and system guidelines
</li><li>Apply consistent evaluation standards by following clear taxonomies, benchmarks, and detailed evaluation guidelines
</li></ul>Who You Are
<ul><li>You hold a PhD in Engineering or a closely related field
</li><li>You have deep expertise in one or more of the following sub-domains:
<ul><li>Mechanical &amp; Physical Systems Engineering
</li><li>Electrical, Electronic &amp; Computer Engineering
</li><li>Chemical, Materials &amp; Process Engineering
</li><li>Civil, Environmental &amp; Infrastructure Engineering
</li></ul></li><li>You have significant experience using large language models (LLMs) and understand how and why people use them
</li><li>You have excellent writing skills and can clearly explain complex engineering concepts
</li><li>You have strong attention to detail and consistently notice subtle issues others may overlook
</li><li>Experience reviewing or editing technical or academic writing
</li></ul>Nice-to-Have Specialties
<ul><li>Experience with applied research, industry engineering workflows, or systems design
</li><li>Prior experience with RLHF, model evaluation, or data annotation work
</li><li>Experience teaching, mentoring, or explaining engineering concepts to non-expert audiences
</li><li>Familiarity with evaluation rubrics, benchmarks, or structured review frameworks
</li></ul>What Success Looks Like
<ul><li>You identify technical inaccuracies, flawed assumptions, or incomplete reasoning in engineering-related model outputs
</li><li>Your feedback improves the rigor, clarity, and correctness of AI explanations
</li><li>You deliver consistent, reproducible evaluation artifacts that strengthen model performance</li></ul></div>

Civil Infrastructure Engineer (PhD) - Remote

The Home Depot

<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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