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staff data engineer scala spark gen ai

Disqo

<div><div><div>DISQO&rsquo;s mission is to build the world&rsquo;s most trusted ad measurement platform that fuels brand growth.</div><div>
The world&rsquo;s largest brands, agencies, and media companies trust DISQO for expert insight and AI-driven intelligence about their advertising performance across all platforms. We capture people&rsquo;s sentiments and journeys, connecting them with the brands they value and the media they consume. With this identity-based approach, brands gain more accurate and authentic insight so they can create more meaningful interactions.</div><div></div><div><br>
Joining DISQO Nation means becoming part of a community that champions speed, innovation, and continuous growth. We invest deeply in our talent, empowering our teams to reach their highest potential. Together, we are shaping the future of work at DISQO&mdash;defined by performance, purpose, and impact.</div><div></div><div><br>
We show up each day with curiosity and ambition, committed to learning, accelerating growth, and making a lasting difference. Grounded in our values and principles, we lead and collaborate to elevate performance, accountability, and excellence at every level of the organization. And through it all, we make sure to have fun along the way.</div><div></div><div><br>
This is a great opportunity to join a fun, highly motivated team and lead the development of intelligent data products that directly power how brands measure advertising effectiveness. At DISQO, we use modern cloud infrastructure, Generative AI, and expert-level data engineering to solve complex, real-world problems at scale.</div>
<div>
<p>We are looking for a visionary technical leader who is a master of distributed data processing (Scala/Spark) and passionate about the intersection of data engineering and Artificial Intelligence. You&rsquo;ll serve as a force multiplier, working closely with engineering leadership, product managers, and analysts in a collaborative environment where rapid innovation and systemic impact matter.</p>
<p>
We believe the best software is built by highly aligned, autonomous teams that take ownership and move quickly. We use agile development practices, modern tooling, and strong engineering discipline to deliver early and often. We care deeply about architectural excellence, data correctness, system reliability, and building intelligent systems the right way.</p>
<h3 class="jobSectionHeader"><b>
Position Description</b></h3>
<p>
As a Staff Data Engineer, you will set the technical direction for DISQO&rsquo;s ad measurement platform. You will architect, build, and scale our most complex data pipelines while spearheading the integration of Generative AI capabilities directly into our core data infrastructure and products. You will tackle our hardest scalability challenges, utilizing expert-level Spark and Scala to process massive datasets, while leveraging LLMs to unlock new value from unstructured and structured data.</p>
<p>
Operating with a high degree of autonomy, you will lead cross-functional technical initiatives, drive architectural decisions, and pioneer how we use AI to enrich data, automate pipelines, and improve data quality. You will mentor senior and mid-level engineers, raising the technical bar for the entire team while expanding DISQO's technical depth across big data systems, cloud infrastructure, and applied AI.</p><br>
<p></p>
</div></div>
<div><div><h3 class="jobSectionHeader"><b>What you will do:</b></h3><div><div><ul>
<li>
<p><b>Architect and Lead:</b> Design, build, and maintain highly scalable, fault-tolerant data pipelines using expert-level Scala and Apache Spark.</p>
</li>
<li><p><b>Gen AI Integration:</b> Pioneer the use of Generative AI within our data ecosystem&mdash;incorporating LLMs to enrich datasets, extract value from unstructured data, automate metadata generation, and build intelligent data products.</p>
</li>
<li><p><b>Cross-Functional Strategy:</b> Partner with Product and Engineering leadership to translate complex business requirements into forward-looking data and AI-augmented architectures.</p>
</li>
<li><p><b>Optimize Systems:</b> Architect and aggressively optimize large-scale ETL/ELT workflows. Dive deep into Spark internals to resolve complex performance bottlenecks, memory issues, and data skew.</p>
</li>
<li><p><b>Modern AI Tooling:</b> Implement and manage infrastructure to support AI integration, including vector databases, embeddings pipelines, and Retrieval-Augmented Generation (RAG) architectures.</p>
</li>
<li><p><b>Set the Standard:</b> Write clean, highly optimized, and maintainable code, while establishing standards for code quality, testing, and system architecture across the organization.</p>
</li>
<li><p><b>Ensure Operational Excellence:</b> Champion data quality, observability, and system health to consistently meet enterprise SLAs and customer commitments.</p>
</li>
<li><p><b>Mentorship:</b> Actively mentor engineers, lead technical design reviews, and foster a culture of continuous learning and technical rigor.</p>
</li>
</ul></div></div></div></div><div><div><h3 class="jobSectionHeader"><b>What we're looking for:</b></h3><div><div><div>
<ul>
<li><p><b>8+ years of experience</b> building, architecting, and supporting complex production data pipelines, distributed systems, and backend infrastructure.</p>
</li>
<li><p><b>Expert-Level Scala &amp; Spark:</b> Deep, hands-on expertise in Scala and Apache Spark. You must understand Spark internals, query plans, memory management, and advanced performance tuning for massive-scale batch processing.</p>
</li>
<li><p><b>Applied Generative AI Experience:</b> Proven experience integrating Gen AI / LLMs (e.g., OpenAI APIs, Anthropic, Bedrock) into data products or data engineering workflows. Hands on experience developing with AI dev tools such as Claude code, etc</p>
</li>
<li><p><b>Strong Python Skills:</b> Proficiency in Python specifically to interface with modern AI ecosystems, data APIs, and orchestration tools.</p>
</li>
<li><p><b>Cloud Mastery:</b> Extensive architectural experience within the AWS ecosystem (EMR, Glue, Athena, S3, Bedrock, etc.).</p>
</li>
<li><p><b>Core Data Foundations:</b> Deep understanding of advanced ETL/ELT concepts, complex data modeling, and performance-tuning SQL.</p>
</li>
<li><p><b>Orchestration:</b> Expert-level experience with workflow orchestration tools such as Airflow.</p>
</li>
<li><p><b>Leadership:</b> Proven track record of leading technical initiatives, making architectural decisions, and mentoring teams in an agile, fast-moving environment.</p>
</li>
</ul></div></div></div></div></div><div><div><h3 class="jobSectionHeader"><b>Nice to have:</b></h3><div><div><div>
<ul>
<li><p>Experience with Snowflake or other modern cloud data warehouses.</p>
</li>
<li><p>Deep exposure to streaming or real-time event processing (Kafka, Flink, Kinesis, etc.).</p>
</li>
<li><p>Experience utilizing AI for automated data observability, anomaly detection, or data quality tooling.</p>
</li>
<li><p>Background in ad tech, measurement, attribution modeling, or specialized analytics platforms.</p>
</li>
</ul></div></div></div></div></div><div><div><h3 class="jobSectionHeader"><b>Why DISQO?</b></h3><div><div><div>
<ul>
<li><p>Lead the architecture of intelligent data products that directly influence how the world's top brands measure advertising impact.</p>
</li>
<li><p>Work with bleeding-edge data and Gen AI infrastructure at a highly meaningful scale.</p>
</li>
<li><p>Shape the technical culture and elevate a talented engineering organization while owning massive-scale production systems.</p>
</li>
</ul></div></div></div></div></div><div><div>$210,000 - $230,000 a year</div><div><b>
Your pay will be determined by your experience, work location, and other applicable factors.</b></div></div>
<div><div><div>#LI-MV1</div></div><div></div><div><br>
</div><div>
At DISQO, we pride ourselves on having a positive, performance-oriented workplace that includes a flexible hybrid approach, competitive medical benefits, and an amazing vacation policy.</div><div></div><div><b><br>
Perks &amp; Benefits:</b></div><div></div><ul><li><br>
100% covered Medical/Dental/Vision for employee, competitive dependent coverage</li><li>Stock options</li><li>401K</li><li>Generous PTO policy</li><li>Team offsites, social events &amp; happy hours</li><li>Life Insurance</li><li>Health FSA</li><li>Commuter FSA (for hybrid employees)</li><li>Catered lunch and fully stocked kitchen</li><li>Paid Maternity/Paternity leave</li><li>Disability Insurance</li><li>Travel Assistance Program</li><li>24/7 Counseling Services offered to Employees</li></ul><div></div><div><b><i><br>
Note: The benefits noted above are for full time US based employees only.</i></b></div><div></div><div><b><br>
DISQO is an equal opportunity employer. Discovery, innovation, and growth are possible when we open ourselves to new possibilities, perspectives, and approaches. That&rsquo;s why, at DISQO, we welcome, support, and empower individuals from diverse backgrounds. Exceptional teams are rooted in extraordinary people, each with a unique story and a compelling set of skills. DISQO does not discriminate against employees based on race, color, religion, sex, national origin, gender identity or expression, age, disability, pregnancy (including childbirth, breastfeeding, or related medical condition), genetic information, protected military or veteran status, sexual orientation, or any other characteristic protected by applicable federal, state or local laws.</b></div><div></div><ul><li><br>
<b><i>Recruiting firms that submit resumes to DISQO without first entering into a written contract will not be entitled to any compensation on candidates referred by that firm.</i></b></li></ul></div>
<div><div>We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.</div></div></div>

Staff Data Engineer (Scala, Spark, & Gen AI)

Tinder

<div>
 <p>
  <strong>
   Our Mission
  </strong>
 </p>
 <br/>
 <p>
  &nbsp;
 </p>
 <br/>
 <p>
  <span>
   As humans, there are few things more exciting than meeting someone new. At Tinder, we&rsquo;re inspired by the challenge of keeping the magic of human connection alive. With tens of millions of users, hundreds of millions of downloads, 2+ billion swipes per day, 20+ million matches per day, and a presence in 190+ countries, our reach is expansive&amp;mdash;and rapidly growing.
  </span>
 </p>
 <br/>
 <p>
  &nbsp;
 </p>
 <br/>
 <p>
  <span>
   We work together to solve complex problems. Behind the simplicity of every match, we think deeply about human relationships, behavioral science, network economics, AI and ML, online and real-world safety, cultural nuances, loneliness, love, sex, and more.
  </span>
 </p>
 <br/>
 <p>
  &nbsp;
 </p>
 <br/>
 <p>
  <br/>
  <p>
   <strong>
    Our Values
   </strong>
  </p>
  <br/>
  <p>
   <br/>
   <p>
    <em>
     <strong>
      Take the Lead
      <br/>
     </strong>
    </em>
    We don't ghost our work or each other. Just as users don't leave their matches hanging, we don't let each other down.
   </p>
   <br/>
   <p>
    <em>
     <strong>
      Move Fast
      <br/>
     </strong>
    </em>
    We have a bias for action and urgency. Something that could be done tomorrow would be better if done today.
   </p>
   <br/>
   <p>
    <em>
     <strong>
      Better Together
      <br/>
     </strong>
    </em>
    We keep connection at the heart of dating and at the heart of how we work. Just as our users are better when they connect with others, so are we when we collaborate.
   </p>
   <br/>
   <p>
    <em>
     <strong>
      Real Talk
      <br/>
     </strong>
    </em>
    We say the hard thing the human way. Just as we ask our users to behave with kindness and candor in our community, we expect Team Tinder to do the same.
   </p>
   <br/>
   <p>
    <em>
     <strong>
      Safety First
      <br/>
     </strong>
    </em>
    We act with integrity, transparency, and consistency so people feel safe&amp;mdash;whether they're swiping, matching, or working alongside us.
   </p>
   <br/>
   <p>
    <em>
     <strong>
      Spark Fun
      <br/>
     </strong>
    </em>
    We have fun to unlock creativity, fuel innovation, and help us build better experiences for daters.
   </p>
   <br/>
  </p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Program Duration
  </strong>
 </p>
 <br/>
 <p>
  <span>
   The internship program will run from June 1 through August 28, 2026.
  </span>
 </p>
 <br/>
 <p>
  &nbsp;
 </p>
 <br/>
 <p>
  <strong>
   Where you&rsquo;ll work
  </strong>
 </p>
 <br/>
 <p>
  <span>
   This is a hybrid role that requires in-office collaboration three days per week in either Los Angeles or Palo Alto, California.
  </span>
 </p>
 <br/>
 <p>
  &nbsp;
 </p>
 <br/>
 <p>
  <strong>
   About the Role
  </strong>
 </p>
 <br/>
 <p>
  <span>
   As a Backend Engineer Intern at Tinder, you will partner directly with senior members of the engineering team and be empowered to contribute solutions to Tinder&rsquo;s backend system. We are deeply invested in improving architecture design, exploring and leveraging new technologies in interesting ways to deliver an app that continues to shape how people connect globally.
  </span>
 </p>
 <p>
  <p>
   <br/>
  </p>
  <strong>
   What you'll do:
  </strong>
  <br/>
  <li>
   Collaborate across Tinder Engineering on the expansion of our service platform
  </li>
  <br/>
  <li>
   Develop and operate scalable and resilient distributed services that run on Amazon Web Services (AWS)
  </li>
  <br/>
  <li>
   Build large scale distributed systems that handle billions of data events a day
  </li>
  <br/>
  <li>
   Write unit and integration tests.&nbsp;
  </li>
  <br/>
  <li>
   Access to cutting-edge Generative AI tools and the opportunity to apply them in real-world engineering work
  </li>
  <br/>
  <p>
   <br/>
  </p>
  <strong>
   What we're looking for:
  </strong>
  <br/>
  <li>
   Aspiring backend developer who&rsquo;s excited to work on large scale challenges with cutting-edge technology
  </li>
  <br/>
  <li>
   Proficiency in coding with at least one language (Java, Scala, Python,Typescript, Nodejs, etc.)
  </li>
  <br/>
  <li>
   Foundational knowledge of basic Computer Science principles: data structures and algorithms
  </li>
  <br/>
  <li>
   Curiosity and creativity in leveraging Generative AI to reimagine feature building and development workflows
  </li>
  <br/>
  <li>
   Currently pursuing a BS/BA, MS, or PhD in Computer Science or a related field
  </li>
  <br/>
  <p>
   <br/>
  </p>
  <strong>
   Nice to have:
  </strong>
  <br/>
  <li>
   Prior internship or work experience on backend systems
  </li>
  <br/>
  <li>
   Completed relevant project experience (i.e. hackathons, personal projects, GitHub, Open Source, volunteer coding experience etc.)
  </li>
  <br/>
  <li>
   Knowledge of technologies such as; Protocol Buffers, gRPC, Apache Kafka, Apache Flink, ElasticSearch, Redis
  </li>
  <br/>
  <li>
   Aware of AWS technologies like; DynamoDB, S3, RDS, ElastiCache
  </li>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <br/>
 <p>
  <span>
   Commitment to Inclusion
  </span>
 </p>
 <br/>
 <p>
  &nbsp;
 </p>
 <br/>
 <p>
  <span>
   At Tinder, we don&rsquo;t just accept difference, we celebrate it. We strive to build a workplace that reflects the rich diversity of our members around the world, and we value unique perspectives and backgrounds. Even if you don&rsquo;t meet all the listed qualifications, we invite you to apply and show us how your skills could transfer. Tinder is proud to be an equal opportunity workplace where we welcome people of all sexes, gender identities, races, ethnicities, disabilities, and other lived experiences. Learn more here:&nbsp;
  </span>
  <span>
   https://www.lifeattinder.com/dei
  </span>
 </p>
 <br/>
 <p>
  &nbsp;
 </p>
 <br/>
 <p>
  <em>
   If you require reasonable accommodation to complete a job application, pre-employment testing, or a job interview or to otherwise participate in the hiring process, please speak to your Talent Acquisition Partner directly.
  </em>
 </p>
 <br/>
 <p>
  &nbsp;
 </p>
 <br/>
 <p>
  <em>
   #Tinder
  </em>
 </p>
 <br/>
 <p>
  .
 </p>
 <br/>
 <br/>
 <span>
  The compensation range listed above is representative of the hourly rate offered.
 </span>
 <br/>
 &nbsp;
 <br/>
 <em>
  Factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary range is reflective of a position based in Los Angeles, and Palo Alto, California. This hourly rate will be subject to a geographic adjustment (according to a specific city, state, and country), if an authorization is granted to work outside of the location listed in this posting.
 </em>
</div>


Backend Engineer Intern

Kforce Inc

<div>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 Kforce has a client that is seeking a Machine Learning Engineer in Los Angeles, CA.
 <br/>
 <br/>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's degree in Computer Science, Artificial Intelligence, Informatics or closely related field; Master's degree in computer science, engineering or closely related field preferred
  </li>
  <li>
   3 or more years relevant Machine Learning Engineer Experience
  </li>
  <li>
   Experience in managing end-to-end ML lifecycle
  </li>
  <li>
   Experience in managing automation with Terraform
  </li>
  <li>
   Containerization technologies (e.g., Docker) or container orchestration platforms (e.g., Kubernetes)
  </li>
  <li>
   CI/CD tools (e.g., Github Actions)
  </li>
  <li>
   Programming languages and frameworks (e.g., Python, R, SQL)
  </li>
  <li>
   Deep understanding of coding, architecture, and deployment processes
  </li>
  <li>
   Strong understanding of critical performance metrics
  </li>
  <li>
   Extensive experience in predictive modeling, LLMs, and NLP
  </li>
  <li>
   Exhibit the ability to effectively articulate the advantages and applications of the RAG framework with LLMs
  </li>
  <li>
   Proven experience with: Artificial intelligence and machine learning platforms (e.g., AWS, Azure or GCP); Containerization technologies (e.g., Docker) or container orchestration platforms (e.g., Kubernetes); CI/CD tools (e.g., GitHub Actions); Programming languages and frameworks (e.g., Python, R, SQL). MLOps engineering principles, agile methodologies, and DevOps life-cycle management; Technical writing and documentation for AI/ML models and processes; Healthcare data and machine learning use cases
  </li>
  <li>
   Healthcare Expertise: Understanding of healthcare regulations and standards, and familiarity with Electronic Health Records (EHR) systems, including integrating machine learning models with these systems
  </li>
  <li>
   Production Deployment and Model Engineering: Proven experience in deploying and maintaining production-grade machine learning models, with real-time inference, scalability, and reliability
  </li>
  <li>
   Scalable ML Infrastructures: Proficiency in developing end-to-end scalable ML infrastructures using on-premise cloud platforms such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Azure
   <br/>
   <br/>
  </li>
 </ul>
 The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
 <br/>
 <br/>
 We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability &amp; ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
 <br/>
 <br/>
 Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
 <br/>
 <br/>
 This job is not eligible for bonuses, incentives or commissions.
 <br/>
 <br/>
 Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
 <br/>
 <br/>
 By clicking &ldquo;Apply Today&rdquo; you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.
</div>


Machine Learning Engineer

VXI Global Solutions

<div><p>Job Description</p><div>
It's fun to work in a company where people truly BELIEVE in what they are doing!<br>
<br>
We're committed to bringing passion and customer focus to the business.
<br>
<br>
<b>AI Specialist, Support Financial Planning &amp; Analysis</b><br>
<br>
<b>Location:</b> Fully Onsite, Monday through Friday, at 515 S. Figueroa St., Suite 600, Los Angeles 90071<br>
<br>
<b>Position Type:</b> Full-Time<br>
<b>Department:</b> Finance / Digital Transformation
<br>
<b>Reports To:</b> VP, General Accounting
<br>
<br>
<b>Compensation:</b> Base compensation range is between $60,000 - $80,000 USD annually, and is commensurate with experience.<br>
<br>
<b>Position Overview</b>
<br>
<br>
We are seeking a motivated and technically curious early-career professional to support the integration of artificial intelligence into our internal operations, with an initial focus on finance. This role will contribute to designing, implementing, and scaling AI-driven solutions that improve accuracy, efficiency, and insight across financial processes.
<br>
<br>
The ideal candidate has a foundational understanding of AI tools and an interest in finance workflows such as FP&amp;A, invoicing, and data validation. You will work closely with senior team members to help transform how financials operate by embedding automation and intelligence into day-to-day processes, leveraging tools such as Claude, Gemini, and Copilot.
<br>
<br>
<b>Key Responsibilities</b>
<br>
<ul><li>Support the design and implementation of AI-powered solutions to optimize internal financial operations</li></ul><ul><li>
Assist in configuring and deploying AI tools (including Claude, Gemini, and Copilot) to automate workflows across FP&amp;A, invoicing, and reporting</li></ul><ul><li>
Contribute to building intelligent automation for financial planning &amp; analysis, including:</li></ul><ul><li>
Supporting automated variance analysis based on operational and financial data</li></ul><ul><li>
Assisting in generating initial commentary and insights tied to key business drivers</li></ul><ul><li>
Help develop systems to validate invoicing processes, including:</li></ul><ul><li>
Checking formula consistency across models and spreadsheets</li></ul><ul><li>
Verifying accuracy from raw data inputs through final outputs</li></ul><ul><li>
Supporting invoice checks against contract terms for completeness and compliance</li></ul><ul><li>
Collaborate with finance, operations, and IT teams to identify opportunities for automation and efficiency improvements</li></ul><ul><li>
Assist in prototyping and testing AI-driven tools, including Generative AI and LLM-based solutions</li></ul><ul><li>
Support workflow automation efforts across accounts payable/receivable, invoice processing, and reconciliation</li></ul><ul><li>
Participate in building and maintaining data pipelines and integrations between financial systems under guidance</li></ul><ul><li>
Help monitor performance of AI solutions and contribute to ongoing improvements</li></ul><ul><li>
Document processes and assist in training internal teams on effectively using AI tools in daily work</li></ul><br>
<b>
Qualifications</b>
<br>
<ul><li>Bachelor's degree in Computer Science, Finance, Data Science, or related field
<br>
0-2 years of relevant experience (internships, academic projects, or coursework acceptable)</li></ul><ul><li>
Basic understanding of finance processes such as FP&amp;A, invoicing, or accounting workflows</li></ul><ul><li>
Familiarity with AI tools or platforms (e.g., Claude, Gemini, Copilot)</li></ul><ul><li>
Foundational programming skills (preferably Python) and interest in data and automation</li></ul><ul><li>
Ability to translate business needs into structured problem-solving approaches</li></ul><ul><li>
Strong analytical thinking and attention to detail</li></ul><ul><li>
Effective communication skills and ability to collaborate across teams</li></ul><br>
<b>
Preferred Skills</b>
<br>
<ul><li>Internship or project experience applying AI, automation, or data analysis</li></ul><ul><li>
Exposure to ERP systems (e.g., NetSuite, SAP, Oracle) or CRM platforms</li></ul><ul><li>
Basic knowledge of SQL or data querying concepts</li></ul><ul><li>
Familiarity with prompt engineering concepts or working with LLMs</li></ul><ul><li>
Understanding of data validation, reporting, or audit processes</li></ul><ul><li>
Interest in financial systems, data pipelines, or business process automation</li></ul><br>
<b>
What Success Looks Like</b>
<br>
<ul><li>Increased automation of finance workflows with reduced manual effort</li></ul><ul><li>
Faster and more consistent variance analysis and reporting support</li></ul><ul><li>
Improved accuracy in invoicing and financial data validation processes</li></ul><ul><li>
Successful adoption of AI tools (Claude, Gemini, Copilot) across finance teams</li></ul><ul><li>
Growth in technical and business skills, contributing to larger AI initiatives over time</li></ul><br>
<b>
Why Join Us</b>
<br>
<ul><li>Opportunity to begin your career in AI and finance transformation</li></ul><ul><li>
Hands-on experience with cutting-edge AI tools and real-world business applications</li></ul><ul><li>
Collaborative environment with mentorship from experienced professionals</li></ul><ul><li>
Exposure to cross-functional teams and enterprise systems</li></ul><ul><li>
Competitive compensation and benefits</li></ul><br>
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!</div><div><div>
Original Title: AI Specialist, Support Financial Planning &amp; Analysis</div><div>
Req Id: R26_02724</div><div>
Posted At: Thu May 07 2026 00:00:00 GMT+0000 (Coordinated Universal Time)</div></div></div>
<br><div></div><div><div><div>Accounting &amp; Finance</div></div><div></div><div><div>
Full Time</div></div><div></div><div><div>
Los Angeles, California, United States</div></div></div>

AI Specialist, Support Financial Planning & Analysis

Gibson Homewares

<div>
 <strong>
  Gibson Homewares
 </strong>
 is the nation's leading producer of dinnerware, cookware, cutlery, tools, and gadgets - all the essentials needed for prep, cooking, dining, and entertaining.
 <br/>
 <br/>
 For over 40 years and spanning four generations as a respected and trusted family-owned company, Gibson Homewares has developed a portfolio of brands across multiple categories.
 <strong>
  Based in Los Angeles,
 </strong>
 Gibson is known for delivering product lines with style and value for the global retail marketplace. Exporting to Latin America and Mexico. Gibson's legacy brands include Laurie Gates, Gibson Elite, Gibson Home, Ultra by Gibson, and Soho Lounge. In addition, Gibson is a driving force behind global brands such as Martha Stewart, Calphalon, Sur La Table, Babish, Kenmore, Crockpot, Oster, Mr. Coffee, and Peanuts.
 <br/>
 <br/>
 At Gibson,
 <strong>
  PEOPLE ARE THE #1 PRIORITY
 </strong>
 and the company is always looking for new talent to join our growing team.
 <br/>
 <br/>
 For more information, visit us at http://www.gibsonhomewares.com
 <br/>
 <br/>
 <strong>
  Job Title: AI Adoption Specialist
  <br/>
  <br/>
 </strong>
 <strong>
  Full-Time, In-Office, M-F, in Los Angeles
  <br/>
  <br/>
 </strong>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 We're looking for a hands-on AI Adoption Specialist to help our Sales, Marketing, and Operations teams work smarter with AI. You'll report to our Director and SVP Information Technology and own the day-to-day execution of AI initiatives-finding bottlenecks, running pilots, training employees, and making sure AI tools actually get used and deliver results.
 <br/>
 <br/>
 This isn't a strategy role and it isn't a data science role. It's a doer role. You'll be the person who turns leadership's AI vision into something teams can touch, use, and benefit from every day.
 <br/>
 <br/>
 What You'll Do
 <br/>
 <br/>
 <ul>
  <li>
   Run discovery workshops across departments to identify time sinks, process bottlenecks, and AI opportunities.
  </li>
  <li>
   Run AI pilot projects: scoping, timelines, vendor coordination, testing, and results tracking.
  </li>
  <li>
   Set up, configure, and test AI tools (Copilot, Claude, Oracle AI Agents, automation platforms) for business teams.
  </li>
  <li>
   Write prompts, build AI workflows, and QA outputs before rolling tools out to end users.
  </li>
  <li>
   Create training materials, run hands-on sessions, and support employees as they adopt new AI tools.
  </li>
  <li>
   Help maintain approved AI tools policy
  </li>
  <li>
   Monitor AI agent performance, token usage, and flag governance or compliance issues.
  </li>
  <li>
   Research new AI vendors and tools; coordinate demos and POC logistics.
  </li>
  <li>
   Map cross-departmental handoffs (Marketing &rarr; Sales &rarr; Ops) to find friction points AI can solve.
  </li>
  <li>
   Build a reusable playbook of templates, checklists, and best practices for future AI rollouts.
   <br/>
   <br/>
  </li>
 </ul>
 What We're Looking For
 <br/>
 <br/>
 <strong>
  Required
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   3-6 years in business analysis, operations, project management, or process improvement.
  </li>
  <li>
   1+ years using AI tools (ChatGPT, Claude, Copilot, Gemini, Oracle GenAI) in a professional setting.
  </li>
  <li>
   Strong project management skills-you can juggle multiple workstreams and keep things on track.
  </li>
  <li>
   Data-literate: comfortable with spreadsheets, CRM exports, and basic data quality checks.
  </li>
  <li>
   Excellent documentation and communication skills-can turn messy findings into clear summaries.
  </li>
  <li>
   Experience working cross-functionally with Sales, Marketing, or Operations teams.
  </li>
  <li>
   Self-starter who's comfortable with ambiguity and figuring things out.
  </li>
  <li>
   Bachelor's degree in Business, Information Systems, or related field (or equivalent experience).
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Nice To Have
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience with prompt engineering or building AI workflows (Zapier, Power Automate, Make).
  </li>
  <li>
   Familiarity with CRM platforms (Salesforce, HubSpot) or marketing automation tools.
  </li>
  <li>
   Background in change management, training development, or user adoption programs.
  </li>
  <li>
   Understanding of AI concepts: LLMs, RAG, agentic AI, tokens, and governance.
  </li>
  <li>
   Experience with data visualization tools (Tableau, Power BI, Looker).
  </li>
  <li>
   Certifications in PM (PMP, Scrum), AI fundamentals, or process improvement (Lean/Six Sigma).
  </li>
  <li>
   Hands-on experience with ERP systems such as Oracle Fusion, SAP S/4HANA, NetSuite, or similar cloud-based ERP/SaaS platforms.
  </li>
  <li>
   Understanding of ERP business processes (order-to-cash, procure-to-pay, record-to-report) and how AI can streamline or augment them.
  </li>
  <li>
   Experience extracting, cleaning, or reporting on data from ERP systems to support AI pilots or automation projects.
  </li>
 </ul>
</div>


AI Adoption Specialist

Prolific

<div>
 Neuroscience Specialist - AI Training
 <br/>
 <br/>
 <strong>
  About Prolific
  <br/>
  <br/>
 </strong>
 Prolific is not just another player in the AI space &ndash; we are building the biggest pool of quality human data in the world.
 <br/>
 <br/>
 Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills.
 <br/>
 <br/>
 <em>
  The role
  <br/>
  <br/>
 </em>
 We are seeking
 <strong>
  Neuroscience Experts
 </strong>
 to act as evaluators for a high-level AI verification project. AI models are now generating complex technical summaries, and we need specialists to ensure these outputs maintain scientific integrity and factual accuracy.
 <br/>
 <br/>
 We need experts who can navigate dense scientific literature to judge the accuracy and structural integrity of AI-generated graphical abstracts. This is a flexible, ad hoc project paying
 <strong>
  $40+/h
 </strong>
 where your technical expertise directly influences how AI understands and summarizes complex research.
 <br/>
 <br/>
 <em>
  What you'll bring
  <br/>
  <br/>
 </em>
 <ul>
  <li>
   Specialized knowledge: Deep expertise in Neuroscience
  </li>
  <li>
   Advanced Academic Credentials: you must hold a Master's or PhD in Neuroscience or a related field.
  </li>
  <li>
   Analytical Skills: history with fact-checking tasks and strong attention to detail
  </li>
  <li>
   Nice to have: Previous experience with AI-related training or evaluation tasks and a background in scientific publishing or peer review.
   <br/>
   <br/>
  </li>
 </ul>
 <em>
  What you'll be doing in the role
  <br/>
  <br/>
 </em>
 <ul>
  <li>
   <strong>
    Scientific Review:
   </strong>
   review scientific papers alongside LLM-generated graphical abstracts.
  </li>
  <li>
   <strong>
    Fact-Checking:
   </strong>
   identify issues and inaccuracies where the graphical abstract does not faithfully represent the source scientific paper.
  </li>
  <li>
   <strong>
    Expert Verification:
   </strong>
   use your domain knowledge to ensure that technical concepts are visually and textually summarized correctly.
   <br/>
   <br/>
  </li>
 </ul>
 <em>
  Please note that to qualify for this study you will be required to pass a paid skills assessment with a sample paper and graphical abstract
  <br/>
  <br/>
 </em>
 <em>
  Why Prolific is a great platform to join as a Participant
  <br/>
  <br/>
 </em>
 Joining our platform as a Prolific participant will give you the chance to influence the AI models of the future using professional legal expertise. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home.
 <br/>
 <br/>
 We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems.
 <br/>
 <br/>
 We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation &ndash; one that reflects the breadth and the best of humanity.
 <br/>
 <br/>
 <em>
  Links to more information on Prolific
  <br/>
  <br/>
 </em>
 Website
 <br/>
 <br/>
 Youtube
 <br/>
 <br/>
 <em>
  Privacy Statement
  <br/>
  <br/>
 </em>
 By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.
</div>


Neuroscience - AI Training - Los Angeles

<div><h2 class="jobSectionHeader"><b>Description</b></h2>
<div>
<p><b>The Role</b></p>
<div><p>
The AI Product Manager is a pivotal connector between business strategy and intelligent product delivery&mdash;translating complex organisational needs into clear, prioritised requirements and driving coordinated execution across Product Owners and cross-functional teams. This role sits at the intersection of business analysis and AI enablement, accountable for requirements gathering, stakeholder alignment, and ensuring that every product initiative is well-defined, technically feasible, and tied to measurable outcomes.</p></div>
<div>
<p>The AI Product Manager shapes how AI and data-driven capabilities move from concept to production. Where the portfolio includes machine learning models, generative AI features, or intelligent automation, this role is the critical bridge&mdash;translating real-world business problems into modelling requirements, assessing data readiness and technical feasibility, and defining success metrics that capture both model performance and business impact.</p>
<p><b>
The Requirements</b></p>
<div>
<div><p><b>Business Requirements &amp; Discovery</b></p></div>
<div><ul><li><p>
Leads requirements discovery across stakeholders through workshops, interviews, and process reviews.</p></li></ul></div>
<div><ul><li><p>
Elicits, documents, and validates business needs, user needs, pain points, and desired outcomes; translate into clear problem statements and requirements.</p></li></ul></div>
<div><ul><li><p>
Develops artifacts such as business requirement documents (BRDs), epics/features, use cases, user journeys, acceptance criteria, and process flows.</p></li></ul></div>
<div><ul><li><p>
Ensures requirements reflect regulatory, legal, privacy, security, and operational considerations; engaging the right SMEs early.</p></li></ul></div>
<div><p><b>
Analysis, Prioritization Support &amp; Decision Enablement</b></p></div>
<div><ul><li><p>
Analyzes qualitative and quantitative inputs (client feedback, operational metrics, adoption/usage data, defect trends) to refine requirements and recommendations.</p></li></ul></div>
<div><ul><li><p>
Supports the Product Leader with data-backed insights, business cases, and trade-off options (scope, timeline, cost, risk).</p></li></ul></div>
<div><ul><li><p>
Helps assess value, impact, dependencies, and feasibility; propose sequencing and release groupings for roadmap planning.</p></li></ul></div>
<div><p><b>
Coordination with Product Owner &amp; Delivery Teams</b></p></div>
<div><ul><li><p>
Partners with Product Owners to convert business requirements into well-groomed backlog items and sprint-ready work.</p></li></ul></div>
<div><ul><li><p>
Maintains continuous alignment between stakeholders and the delivery team; manage requirement clarifications, changes, and approvals.</p></li></ul></div>
<div><ul><li><p>
Participates in agile ceremonies as needed (backlog refinement, sprint planning, demos, retros) to ensure intent and acceptance criteria are understood.</p></li></ul></div>
<div><ul><li><p>
Coordinates UAT readiness and execution with business stakeholders; confirm delivered functionality meets defined requirements.</p></li></ul></div>
</div>
<div><div><p><b>Stakeholder Management &amp; Communication</b></p></div>
<div><ul><li><p>
Serves as a primary point of contact for product leaders and other relevant stakeholders on in-flight requirements and upcoming deliverables.</p></li></ul></div>
<div><ul><li><p>
Creates and maintain clear communication materials (requirements traceability, release notes inputs, decision logs, status updates).</p></li></ul></div>
<div><ul><li><p>
Proactively surface risks, gaps, and cross-team dependencies; drive timely resolution.</p></li></ul></div>
<div><p><b>
Quality, Adoption &amp; Continuous Improvement</b></p></div>
<div><ul><li><p>
Defines and track requirement-level success measures (e.g., process efficiency gains, reduced call drivers, improved completion rates, error reduction).</p></li></ul></div>
<div><ul><li><p>
Gathers post-release feedback, triage issues/enhancements, and feed learnings back into the backlog.</p></li></ul></div>
<div><ul><li><p>
Champions usability, data quality, and operational fit&mdash;ensuring solutions are intuitive, trusted, and supportable.</p></li></ul></div>
<div><p><b>
AI &amp; Data Product Management</b></p></div>
<div><ul><li><p>
Leads feasibility framing for AI-enabled features: assess data availability, model complexity, and ROI before requirements are finalised.</p></li></ul></div>
<div><ul><li><p>
Translates business problems into clear data and modelling needs; define what 'good' looks like for model outputs in terms of accuracy, fairness, and explainability.</p></li></ul></div>
<div><ul><li><p>
Defines AI-specific success metrics alongside business metrics&mdash;including model performance indicators (e.g. precision/recall, lift, false positive rates, latency) and outcome metrics tied to revenue or retention.</p></li></ul></div>
<div><ul><li><p>
Works closely with data scientists, ML engineers, and designers to align on experimentation approaches.</p></li></ul></div>
<div><ul><li><p>
Oversees post-launch monitoring requirements: define thresholds for model drift, bias, and performance decay; ensure feedback loops are built into the product.</p></li></ul></div>
<div><ul><li><p>
Applies AI ethics and governance principles and ensures privacy and compliance obligations are embedded into requirements&mdash;particularly in regulated HWC contexts.</p></li></ul></div>
<div><ul><li><p>
Communicates AI trade-offs clearly to non-technical stakeholders; bridging the gap between technical teams and business decision-makers.</p></li></ul></div>
<div><ul><li><p>
Leads enterprise-scale GenAI roadmap planning, including prioritisation of knowledge management, conversational AI, document intelligence, and analytics use cases in alignment with organisational strategy and executive stakeholders.</p></li></ul></div>
<div><ul><li><p>
Embeds responsible AI lifecycle management into product requirements, including governance frameworks, bias and fairness reviews, and iterative oversight mechanisms throughout model deployment.</p></li></ul></div>
<div><ul><li><p>
Scopes and drives R&amp;D initiatives for emerging AI patterns such as Retrieval-Augmented Generation (RAG) and autonomous AI Agents, translating innovation lab findings into scalable product capabilities.</p></li></ul></div><div><div><br>
<ul>
<li><p>
</p></li><li><p><b>Success Metrics</b></p></li>
<li><p>
Requirements quality: completeness, clarity, testability; reduced rework and churn in delivery.</p></li>
</ul></div>
<div><ul><li><p>On-time readiness: backlog items 'definition of ready' met for planned sprints/releases.</p></li></ul></div>
<div><ul><li><p>
Stakeholder satisfaction with requirement process and communication cadence.</p></li></ul></div>
<div><ul><li><p>
UAT outcomes: reduced defect leakage; acceptance criteria met.</p></li></ul></div>
<div><ul><li><p>
Post-release outcomes tied to the requirement intent (adoption, efficiency, reduced issues).</p></li></ul></div>
<div><ul><li><p>
Adoption of AI-enabled features across the portfolio, with clear, measurable, evidence of client and operational impact (e.g. time saved, decision quality, process automation rates).</p></li></ul></div>
<div><ul><li><p>
Proportion of the product roadmap incorporating AI/GenAI capabilities, with tracked progression from pilot to scaled deployment.</p></li></ul></div>
<div><ul><li><p>
For AI features: model performance metrics (accuracy, fairness, latency) meet defined thresholds at launch; post-launch monitoring in place with documented drift and bias review cadence.</p></li></ul></div>
<div><ul><li><p>
Measurable business value delivered from AI platform investments, evidenced by quantified ROI (e.g. hours saved, revenue influenced, cost reduction) tied to specific product capabilities.</p></li></ul></div>
<div><ul><li><p>
Product governance compliance rate: AI use cases reviewed against responsible AI framework prior to deployment; lifecycle management checkpoints met on schedule.</p></li></ul></div></div></div><br>
</div>
</div><p></p><h2 class="jobSectionHeader"><b>Qualifications</b></h2>
<div>
<p><b>The Qualifications</b></p>
<div>
<div><ul><li><p>7+ years of experience in product management, business analysis, or digital product delivery roles.</p></li></ul></div>
<div><ul><li><p>
Demonstrated strength in requirements elicitation, documentation, and stakeholder facilitation (workshops, interviews, process mapping).</p></li></ul></div>
<div><ul><li><p>
Strong analytical skills&mdash;able to synthesize data into insights, define measurable requirements, and support prioritization decisions.</p></li></ul></div>
<div><ul><li><p>
Excellent written and verbal communication skills; able to translate technical AI trade-offs (cost, latency, accuracy) into clear terms for non-technical stakeholders.</p></li></ul></div>
<div><ul><li><p>
Experience working in regulated environments and coordinating with compliance/legal/risk</p></li></ul></div>
<div><ul><li><p>
Highly organized, detail-oriented, and comfortable managing multiple stakeholders and competing priorities.</p></li></ul></div>
</div>
<div><div><ul><li><p>Familiarity with product tools (e.g., Jira/Azure DevOps, Confluence, Miro) and requirements documentation practices.</p></li></ul></div>
<div><ul><li><p>
Experience supporting data/analytics or AI-enabled product features, including: defining requirements for model outputs; understanding ML pipelines (training, validation, inference); working with model evaluation concepts such as precision/recall, ROC-AUC, and calibration; and establishing governance, monitoring, and iteration plans.</p></li></ul></div>
<div><ul><li><p>
Understanding of AI ethics considerations: bias and fairness, transparency and explainability, privacy, and compliance&mdash;especially in regulated industries.</p></li></ul></div>
<div><ul><li><p>
Data literacy: comfortable with statistics fundamentals, distributions, and sampling sufficient to ask the right questions of data science and ML teams.</p></li></ul></div>
<div><ul><li><p>
Demonstrated experience building and owning end-to-end enterprise AI roadmaps, including knowledge management, conversational AI, and document intelligence platforms at scale.</p></li></ul></div>
<div>
<ul><li><p>Track record of quantifying and communicating AI product value to executive stakeholders, including ROI framing, AUM growth attribution, and operational efficiency metrics.</p></li></ul><br>
<p></p>
<p><b>
This position will remain posted for a minimum of three business days from the date posted or until a sufficient/appropriate candidate slate has been identified</b></p>
<p>
Note: Employment-based non-immigrant visa sponsorship and/or assistance is not offered for this specific job opportunity.</p><br>
<p></p>
<p><b>
Compensation and Benefits</b></p>
<p>
Base salary range and benefits information for this position are being included in accordance with requirements of various state/local pay transparency legislation. Please note that base salaries may vary for different individuals in the same role based on several factors, including but not limited to location of the role, individual competencies, education/professional certifications, qualifications/experience, performance in the role and potential for revenue generation.</p>
<p><b>
Compensation</b></p>
<p>
The base salary compensation range being offered for this role is $225,000-$300,000 USD per year.</p>
<p>
This role is also eligible for an annual short-term incentive bonus</p>
<p><b>
Company Benefits</b></p>
<p>
WTW provides a competitive benefit package which includes the following (eligibility requirements apply):</p>
<ul>
<li><b>Health and Welfare Benefits:</b> Medical (including prescription coverage), Dental, Vision, Health Savings Account, Commuter Account, Health Care and Dependent Care Flexible Spending Accounts, Group Accident, Group Critical Illness, Life Insurance, AD&amp;D, Group Legal, Identify Theft Protection, Wellbeing Program and Work/Life Resources (including Employee Assistance Program)</li>
<li><b>Leave Benefits:</b> Paid Holidays, Annual Paid Time Off (includes paid state/local paid leave where required), Short-Term Disability, Long-Term Disability, Other Leaves (e.g., Bereavement, FMLA, ADA, Jury Duty, Military Leave, and Parental and Adoption Leave), Paid Time Off
</li><li><b>Retirement Benefits:</b> Contributory Pension Plan and Savings Plan (401k). All Level 38 and more senior roles may also be eligible for non-qualified Deferred Compensation and Deferred Savings Plans.</li>
</ul>
<p>Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles County Fair Chance Ordinance for Employers, we will consider for employment qualified applicants with arrest and conviction records.</p>
<p>
EOE, including disability/vets</p></div></div></div></div>

AI Product Manager

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