About the Role:

We are building AI-powered, agentic workflows to transform how service operations scale, resolve customer needs, and maintain quality in high-stakes environments. At Gusto, that means designing systems that can earn the trust of small business owners — where a wrong answer or a missed escalation has real consequences.

As an AI Solutions Architect, you will own the end-to-end design and performance of these workflows in production — where models, tools, data, and human judgment come together to deliver outcomes. This is not a traditional architecture role. You will design, prototype, deploy, and continuously improve AI-driven systems that directly impact customer experience and operational efficiency. You will also play a key role in shaping the evolution of our AI platform by identifying capability gaps, prototyping solutions, and informing the primitives required to scale agentic systems effectively.

You will report into the Service Transformation org and work at the intersection of AI governance, service quality, and operational transformation — operating as the connective tissue between Engineering, CX, Legal, and Compliance as Gus, Gusto's AI assistant, scales.

About the Team:

The mission of our Service Transformation (CXT) team is to quickly evolve and scale how Gusto delivers outstanding service experiences and leverages AI to do so. Our team designs the systems, governance frameworks, and feedback loops that allow Gusto's service model to improve continuously, operate reliably, and earn the trust of the customers and employees who depend on it.

Here’s what you’ll do day-to-day:

• Architect, prototype, and own end-to-end agentic service workflow frameworks, from scoping through production deployment and iteration — including solve and assist targets, HITL protocols, override logic, and downstream quality safeguards
• Analyze SOPs, operational metrics and interaction data to identify and prioritize high-impact automation opportunities based on volume, risk, and customer impact
• Design and implement multi-agent orchestration patterns across tools, data sources, and decision steps within a single end-to-end workflow
• Apply and influence AI platform capabilities in partnership with CoreX (Gusto's AI Platform team) — including orchestration, retrieval, and evaluation — helping define what needs to be built to support production workflows at scale
• Identify platform gaps, prototype workflow-level solutions, and partner with engineering to shape the primitives required for reliable, scalable AI systems
• Serve as the primary CX voice in Legal, Security, Compliance, and CoreX forums — translating CX quality stakes and workflow risk into terms each audience acts on, and ensuring governance requirements are embedded in design, not retrofitted after launch
• Strengthen evaluation frameworks and feedback loops to ensure quality, compliance, and continuous improvement; contribute to Gusto's human evaluation programs and AI governance practices through deep partnership with our internal CX Labs team
• Partner with Data teams to define and track workflow performance — including solve and assist rate, AHT, rework rate, and customer effort score — clearly distinguishing between model-level, workflow-level, and operational drivers
• Build ROI models to quantify workflow impact across efficiency, quality, and cost before and after deployment
• Represent workflow performance and risk to senior stakeholders with appropriate precision and brevity; communicate in a way that drives action, not overwhelm
• Lead through ambiguity and rapid change: the function is still being defined, and you will help define it

Here’s what we're looking for:

• 8+ years in operations, product, or AI roles — with at least 2 years designing and deploying AI-assisted or agentic workflows
• Strong fluency with LLM systems, including prompt design, evaluation, and production behavior at scale
• Hands-on experience with agentic tooling, orchestration frameworks, or MCP-style integrations — conceptual familiarity is not sufficient at this level
• Experience designing human-in-the-loop (HITL) systems with clear escalation logic, override controls, and compliance-aware checkpoints
• Working knowledge of multi-agent systems and tool coordination
• Strong operational judgment: able to define and diagnose workflow metrics 
• Proven track record influencing cross-functional stakeholders — including Product, Engineering, Legal, Security, and Compliance — in writing, in design reviews, and in high-stakes forums
• Familiarity with Responsible AI practices, governance, and risk management in production environments
• Proven ability to operate in high ambiguity, create clarity, and drive alignment across technical and non-technical audiences
• Strong systems thinking with a bias toward execution and measurable outcomes
• Deep empathy for small business customers and the employees who serve them

Our cash compensation amount for this role is $133,470/yr to $173,511/yr in Denver & most major metro locations, and $157,145/yr to $204,289/yr for San Francisco & New York. Final offer amounts are determined by multiple factors including candidate location, experience and expertise and may vary from the amounts listed above.

About the Role:

We are seeking a highly motivated and licensed Property & Casualty (P&C) Insurance Broker to join our team as part of a critical pilot to launch a P&C broker model at Gusto. You will be essential in evolving Gusto's business insurance channel by acting as a licensed agent to quote and issue business insurance policies with our NEXT Insurance carrier partner. You will use your expertise to provide direct support and an improved experience for small business customers with complex insurance needs, helping to capture meaningfully higher revenue and accelerating the development of our AI Insurance Advisor.

About the Team:

This team is crucial to solving customer experience gaps and optimizing our offline insurance channels. You will be a SME who is part of the "human-in-the-loop" workflows required to train and optimize Gus as an AI insurance advisor. Our collective vision is to be an expert advisor that supports small businesses through every stage of growth, with this pilot being key to establishing our digital insurance agency and licensed agent integration.

Here’s what you’ll do day-to-day:

• Make outbound dials to prospective and existing small business clients to assess their complex P&C insurance needs and recommend suitable coverage options.
• Quote and issue Property & Casualty policies, primarily with the NEXT Insurance carrier, in our offline sales channel.
• Achieve required daily, weekly, and monthly sales activity expectations. 
• Provide human-in-the-loop support to optimize the AI Insurance Advisor, Gus, and assist customers with more complex needs.
• Maintain client relationships, manage policy renewals, and facilitate changes or endorsements to existing policies.
• Act as a trusted liaison between clients and carriers, including assisting clients with reports of losses and claims settlement when necessary.
• Actively work to cross-sell and up-sell additional P&C lines of coverage and strive to achieve monthly production goals for units and/or revenue.
• Maintain accurate and up-to-date client records and policy documentation within CRM systems (SFDC workflow).
• Use AI-powered workflows as a core part of how you sell: running assigned tools daily, surfacing friction and inefficiencies as you find them, and collaborating with your team to influence what gets built or improved next.
• Stay current on industry trends, products, regulations, and underwriting guidelines to provide accurate advice and ensure compliance.

Here’s what we're looking for:

• Experience in the field: Proven experience in insurance sales or brokerage, with coverage level knowledge of commercial P&C products (e.g., Workers' Compensation, BOP, Commercial Auto, E&O). [4+ years]
• Licensing: An active Property & Casualty insurance producer’s license
• Communication & Interpersonal Skills: Excellent verbal and written communication, active listening, and strong interpersonal skills to build rapport and explain complex concepts clearly.
• Sales & Negotiation: Strong sales and negotiation abilities with a proven ability to meet sales targets.
• Technical Proficiency: Working knowledge of carrier quoting systems, proficiency in insurance software, and familiarity with CRM systems like Salesforce (SFDC). 
• Comfortable using AI tools and automation to enhance productivity, decision-making, and problem-solving.
• Mindset: A demonstrated passion for delivering an incredible customer experience and genuine empathy for small business owners.
• Attributes: Highly self-motivated, goal-oriented, and an entrepreneurial ownership mentality to thrive in a fast-paced, high-energy environment.
• AI Fluency: Proven, day-to-day experience integrating AI into how you work - across writing, research, prep, and summarization as a core part of your workflow, with a track record of giving clear, useful feedback that helps improve your tools and processes.

Our cash compensation amount for this role is $109,390 to $134,000 OTE for Denver, Atlanta, Chicago & Las Vegas. $102,855 to $126,000 OTE for Phoenix. Final offer amounts are determined by multiple factors including candidate location, experience and expertise and may vary from the amounts listed above.

Job Title: IT Field Services Technician

Location: Las Vegas, NV

Job Type: Full-time

Job Summary:

The IT Field Services Technician will be responsible for delivering white-glove support to employees in their office/region and across the firm’s 6000+ employees nationwide. This role includes providing both in-person and remote support as well as maintaining, installing, and configuring all IT hardware within their assigned region. Additionally, the Technician will ensure that all IT-managed spaces, including conference rooms, printer stations, and IT storage areas, are organized, secure, and well-maintained. As the person responsible for one or more office sites, be aware and familiar with other systems and company groups to resolve or escalate office related issues.

This role also requires travel within the assigned region and, when necessary, to other firm locations to provide on-site support. The Technician will act as smart hands on-site for other IT towers and initiatives, assisting with deployments, troubleshooting, and implementations as needed.

Responsibilities:

• Provide friendly, professional on-site support to users in their assigned region(s).
• Create, monitor, track, schedule, update, and close tickets within SLA.
• Act as a Tier 3 level agent responding to and resolving tickets escalated from the Service Delivery teams.
• Proactive support of IT related projects, including coordination of all local technology solutions as the SME and the IT point of contact.
• Collaborate with vendors to resolve issues as necessary.
• Maintain, organize, and order stock of IT hardware within their region.
• Establish and build relationships with local leadership and staff and seek solutions to improve their daily workflow.
• Ensure proper cable management and organization of IT-managed spaces, including conference rooms, printer stations, and IT storage areas.
• Regularly inspect and maintain the physical appearance of IT workspaces to ensure a neat, professional, and secure environment.
• Implement and enforce best practices for IT equipment storage, labeling, and organization.
• Ensure IT closets and storage areas are well-kept, accessible, and securely managed.
• Travel within the assigned region and to other firm locations as needed to provide on-site support.
• Act as smart hands on-site for other IT towers and initiatives, assisting with deployments, troubleshooting, and implementations.

Qualifications:

• 2+ years of experience in an IT Service Desk or Field Services role.
• Experience in Office 365 and Active Directory Services.
• Basic understanding of networking and wiring configurations.
• Preferred experience working with Freshservice, Salesforce, and Microsoft Office 365.
• Ability to assist others with complex issues in a professional manner.
• Strong ability to manage and prioritize incidents, requests, and tasks.
• Strong problem analysis and problem-solving skills.
• Excellent written and verbal communication skills.
• Highly resourceful, well-organized, dependable, efficient, and detail oriented.
• Strong desire to learn and grow both IT and office support skills to deliver high quality results for our clients and partners
• Commitment to maintaining a professional and orderly IT work environment, ensuring IT-managed spaces are neat, secure, and well-maintained.

If you are customer-focused, technically adept, and thrive in a collaborative environment, we encourage you to apply for this exciting opportunity.

#LI-MB1

For more than 20 years, AEG has played a pivotal role in transforming sports and live entertainment. Annually, we host more than 160 million guests, promote more than 10,000 shows and present more than 22,000 events around the world. We are committed to innovation, artistry, and community, and leverage the power of our 300+ venues, leading sports franchises, marquee music brands, integrated entertainment districts, premier ticketing platform and global sponsorship activations, to create memorable moments that give the world reason to cheer. 

Our business is interwoven with the human mind and heart, and we strive to build a diverse and inclusive company that reflects the artists, athletes, and fans that we host; reach beyond traditional boundaries to support the communities in which we operate; and minimize our impact on the environment by adopting sustainable practices throughout our business operations. 

If you want to be challenged to up your game and make a difference, then join us in giving the world reason to cheer!

Position Summary:

The Box Office Agent is responsible for communicating information regarding the location, event, seating options, price structures, and other details to help guests select the best event ticket option. The incumbent will process ticket orders and collects payments.

Essential Functions:

• The Box Office Ticket Agent is responsible for communicating information regarding the location, event, seating options, price structures, and other details to help guests select the best event ticket option. The incumbent will process ticket orders and collects payments.

• Follow cash handling and inventory procedures to ensure security of assets and inventory.
• Greet customers with a positive and friendly demeanor.  Assist guests by providing information, answering questions and processing requests.
• Provides upselling opportunities to similar events in the genre by demonstrating a strong knowledge of upcoming events.
• Contributes to the team dynamic by assisting coworkers, maintaining the facilities’ cleanliness and helping to develop and maintain a positive work environment.
• Resolve customer concerns by providing superior customer service, utilizing common practices for resolution and escalating to supervisor when needed.

Required Qualifications:

• A minimum education level of: High School Diploma or its equivalency       
• A minimum of 0-1 years of related work experience
• Excellent customer service skills
• Must be able to work independently and in a team setting
• Good communication skills to effectively communicate with customers and co-workers
• Basic Math skills
• Must be responsible and professional
• Effective decision-making skills  
• Demonstrated ability to work in a fast-paced environment
• Available to work flexible hours, including nights and weekends

Pay Scale: $16.00 - 18.00

Bonus: This position is not eligible for a bonus under the current bonus plan requirements.

Benefits: Full-time: We offer a comprehensive benefits package that includes: medical, dental and vision insurance, paid holidays, vacation and sick time, company paid basic life insurance, voluntary life insurance, parental leave, 401k Plan (with a current employer match of 3%), flexible spending and health savings account options, and wellness offerings.

AEG reserves the right to change or modify the employee’s job description whether orally or in writing, at any time during the employment relationship. AEG may require an employee to perform duties outside his/her normal description.

For more than 20 years, AEG has played a pivotal role in transforming sports and live entertainment. Annually, we host more than 160 million guests, promote more than 10,000 shows and present more than 22,000 events around the world. We are committed to innovation, artistry, and community, and leverage the power of our 300+ venues, leading sports franchises, marquee music brands, integrated entertainment districts, premier ticketing platform and global sponsorship activations, to create memorable moments that give the world reason to cheer. 

Our business is interwoven with the human mind and heart, and we strive to build a diverse and inclusive company that reflects the artists, athletes, and fans that we host; reach beyond traditional boundaries to support the communities in which we operate; and minimize our impact on the environment by adopting sustainable practices throughout our business operations. 

If you want to be challenged to up your game and make a difference, then join us in giving the world reason to cheer!

Position Summary:

The Box Office Agent is responsible for communicating information regarding the location, event, seating options, price structures, and other details to help guests select the best event ticket option. The incumbent will process ticket orders and collects payments.

Essential Functions:

• The Box Office Ticket Agent is responsible for communicating information regarding the location, event, seating options, price structures, and other details to help guests select the best event ticket option. The incumbent will process ticket orders and collects payments.

• Follow cash handling and inventory procedures to ensure security of assets and inventory.
• Greet customers with a positive and friendly demeanor.  Assist guests by providing information, answering questions and processing requests.
• Provides upselling opportunities to similar events in the genre by demonstrating a strong knowledge of upcoming events.
• Contributes to the team dynamic by assisting coworkers, maintaining the facilities’ cleanliness and helping to develop and maintain a positive work environment.
• Resolve customer concerns by providing superior customer service, utilizing common practices for resolution and escalating to supervisor when needed.

Required Qualifications:

• A minimum education level of: High School Diploma or its equivalency       
• A minimum of 0-1 years of related work experience
• Excellent customer service skills
• Must be able to work independently and in a team setting
• Good communication skills to effectively communicate with customers and co-workers
• Basic Math skills
• Must be responsible and professional
• Effective decision-making skills  
• Demonstrated ability to work in a fast-paced environment
• Available to work flexible hours, including nights and weekends

Pay Scale: $16.00 - $18.00

Bonus: This position is not eligible for a bonus under the current bonus plan requirements.

Benefits: Full-time: We offer a comprehensive benefits package that includes: medical, dental and vision insurance, paid holidays, vacation and sick time, company paid basic life insurance, voluntary life insurance, parental leave, 401k Plan (with a current employer match of 3%), flexible spending and health savings account options, and wellness offerings.

AEG reserves the right to change or modify the employee’s job description whether orally or in writing, at any time during the employment relationship. AEG may require an employee to perform duties outside his/her normal description.

Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.

The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.

Mission Summary:

The Autonomy Subsystems team at Motional is focused on designing and evaluating modules of the autonomy software. We are seeking a talented senior engineer to contribute to evaluation of our machine learning subsystems. Our team performs a variety of evaluations of machine learning models, including offline model eval, evaluation of open and closed-loop re-simulations, and assessment of on-road performance. Our goal is to establish metrics that describe autonomy subsystem performance, evaluate against those metrics to validate performance, and provide meaningful insight to ML developers and teams, working closely alongside them to improve the performance of ML models on the car.

We are looking for a highly-technical systems engineer with experience designing and evaluating safety critical systems and machine learning models. Bring your passion for autonomy, robotics, and machine learning to our team to help build a production-ready system and prepare for our scaled robotaxi service deployment.

Responsibilities:

• Define, prototype, and validate advanced metrics that bring new insights to model performance evaluation for autonomy subsystems (mainly focused on perception, prediction, and planning).
• Assess coverage of existing training and testing, then curate test sets that sufficiently capture Motional’s intended deployment operational design domain, across many axes (agent types, interaction types, map/spatial, etc.).
• Evaluate machine learning model performance against these metrics and tests.
• Assess system-level performance and subsystem contribution to system behavior through large-scale data analysis of on-road and simulation events.
• Define performance requirements for autonomy subsystems, and supporting analyses required to establish these targets.
• Coordinate subsystem-level evaluation with other system-level testing efforts across the systems team in support of the safety case and safety claims.
  
  

Qualifications:

• An engineer who has demonstrated strong cross-functional collaborative skills and is highly self-starting. This is a highly cooperative role across systems, autonomy, infrastructure, and other parts of the organization.
• Proven engineer with 5+ years of experience working on high-tech safety critical systems or robotics, ideally from a systems, robotics, or similar background.
• Master’s degree in relevant fields (systems, robotics, ML, CS, etc.) or Bachelor’s degree plus significant relevant in-field experience.
• Skilled Python developer, familiarity with analyzing the large scale data required to train and test ML models.
• Experience designing unique metrics that capture key aspects of system behavior and are used to enhance model development.
  
  

Bonus Skills:

• Experience training machine learning models, familiarity with state-of-the-art ML model architectures.
• Deep experience with a specific aspect of machine learning for autonomous robotics (perception, prediction, or planning).
• Knowledge of C++, especially applied to safety critical systems.
• Experience with systems verification and validation techniques
• Experience with regression testing updates to already-deployed software in a safety-critical environment.
• Experience with automotive standards (E.g: ISO 12207, ISO 26262, ISO 21448)
• Experience with software quality management and assurance activities (E.g: IATF 16949, ISO 9001)
• Thorough understanding of robotics systems including sensors, actuators, mechatronics and software systems
• Work in cross collaboration teams to address problems and find solutions
  
  

Physical Demands:

While performing the duties of this job, the employee is frequently required to sit, talk, or hear. The employee is occasionally required to stand and at times for long periods; walk; use hands to finger, handle, or feel; reach with hands and arms. The employee must occasionally lift and move up to 50 pounds.

Travel Requirements (greater than 20%):
Expected to travel for 1-2 weeks each quarter visiting all of our testing sites - mostly to LV, but also domestically as needed for the business.

Working Environment

The work environment characteristics described here represent those a team member encounters while performing the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and/or airborne particlesThe noise level in the environment is low to moderate. 

Motional AD LLC is an Equal Employment Opportunity employer and we welcome all qualified applicants.  All applicants will receive impartial consideration without regard to race, sex, color, national origin, age, disability, veteran status, genetic data, religion, gender identity, sexual orientation or other legally protected status.  Motional AD LLC is a Drug-free workplace.

Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.

The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.

Mission Summary:

The Autonomy Subsystems team at Motional is focused on designing and evaluating modules of the autonomy software. We are seeking a talented senior engineer to contribute to evaluation of our machine learning subsystems. Our team performs a variety of evaluations of machine learning models, including offline model eval, evaluation of open and closed-loop re-simulations, and assessment of on-road performance. Our goal is to establish metrics that describe autonomy subsystem performance, evaluate against those metrics to validate performance, and provide meaningful insight to ML developers and teams, working closely alongside them to improve the performance of ML models on the car.

We are looking for a highly-technical systems engineer with experience designing and evaluating safety critical systems and machine learning models. Bring your passion for autonomy, robotics, and machine learning to our team to help build a production-ready system and prepare for our scaled robotaxi service deployment.

Responsibilities:

• Define, prototype, and validate advanced metrics that bring new insights to model performance evaluation for autonomy subsystems (mainly focused on perception, prediction, and planning).
• Assess coverage of existing training and testing, then curate test sets that sufficiently capture Motional’s intended deployment operational design domain, across many axes (agent types, interaction types, map/spatial, etc.).
• Evaluate machine learning model performance against these metrics and tests.
• Assess system-level performance and subsystem contribution to system behavior through large-scale data analysis of on-road and simulation events.
• Define performance requirements for autonomy subsystems, and supporting analyses required to establish these targets.
• Coordinate subsystem-level evaluation with other system-level testing efforts across the systems team in support of the safety case and safety claims.
  
  

Qualifications:

• An engineer who has demonstrated strong cross-functional collaborative skills and is highly self-starting. This is a highly cooperative role across systems, autonomy, infrastructure, and other parts of the organization.
• Proven engineer with 5+ years of experience working on high-tech safety critical systems or robotics, ideally from a systems, robotics, or similar background.
• Master’s degree in relevant fields (systems, robotics, ML, CS, etc.) or Bachelor’s degree plus significant relevant in-field experience.
• Skilled Python developer, familiarity with analyzing the large scale data required to train and test ML models.
• Experience designing unique metrics that capture key aspects of system behavior and are used to enhance model development.
  
  

Bonus Skills:

• Experience training machine learning models, familiarity with state-of-the-art ML model architectures.
• Deep experience with a specific aspect of machine learning for autonomous robotics (perception, prediction, or planning).
• Knowledge of C++, especially applied to safety critical systems.
• Experience with systems verification and validation techniques
• Experience with regression testing updates to already-deployed software in a safety-critical environment.
• Experience with automotive standards (E.g: ISO 12207, ISO 26262, ISO 21448)
• Experience with software quality management and assurance activities (E.g: IATF 16949, ISO 9001)
• Thorough understanding of robotics systems including sensors, actuators, mechatronics and software systems
• Work in cross collaboration teams to address problems and find solutions
  
  

Physical Demands:

While performing the duties of this job, the employee is frequently required to sit, talk, or hear. The employee is occasionally required to stand and at times for long periods; walk; use hands to finger, handle, or feel; reach with hands and arms. The employee must occasionally lift and move up to 50 pounds.

Travel Requirements (greater than 20%):
Expected to travel for 1-2 weeks each quarter visiting all of our testing sites - mostly to LV, but also domestically as needed for the business.

Working Environment

The work environment characteristics described here represent those a team member encounters while performing the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and/or airborne particlesThe noise level in the environment is low to moderate. 

Motional AD LLC is an Equal Employment Opportunity employer and we welcome all qualified applicants.  All applicants will receive impartial consideration without regard to race, sex, color, national origin, age, disability, veteran status, genetic data, religion, gender identity, sexual orientation or other legally protected status.  Motional AD LLC is a Drug-free workplace.

Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.

The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.

Mission Summary:

The Autonomy Subsystems team at Motional is focused on designing and evaluating modules of the autonomy software. We are seeking a talented senior engineer to contribute to evaluation of our machine learning subsystems. Our team performs a variety of evaluations of machine learning models, including offline model eval, evaluation of open and closed-loop re-simulations, and assessment of on-road performance. Our goal is to establish metrics that describe autonomy subsystem performance, evaluate against those metrics to validate performance, and provide meaningful insight to ML developers and teams, working closely alongside them to improve the performance of ML models on the car.

We are looking for a highly-technical systems engineer with experience designing and evaluating safety critical systems and machine learning models. Bring your passion for autonomy, robotics, and machine learning to our team to help build a production-ready system and prepare for our scaled robotaxi service deployment.

Responsibilities:

• Define, prototype, and validate advanced metrics that bring new insights to model performance evaluation for autonomy subsystems (mainly focused on perception, prediction, and planning).
• Assess coverage of existing training and testing, then curate test sets that sufficiently capture Motional’s intended deployment operational design domain, across many axes (agent types, interaction types, map/spatial, etc.).
• Evaluate machine learning model performance against these metrics and tests.
• Assess system-level performance and subsystem contribution to system behavior through large-scale data analysis of on-road and simulation events.
• Define performance requirements for autonomy subsystems, and supporting analyses required to establish these targets.
• Coordinate subsystem-level evaluation with other system-level testing efforts across the systems team in support of the safety case and safety claims.
  
  

Qualifications:

• An engineer who has demonstrated strong cross-functional collaborative skills and is highly self-starting. This is a highly cooperative role across systems, autonomy, infrastructure, and other parts of the organization.
• Proven engineer with 5+ years of experience working on high-tech safety critical systems or robotics, ideally from a systems, robotics, or similar background.
• Master’s degree in relevant fields (systems, robotics, ML, CS, etc.) or Bachelor’s degree plus significant relevant in-field experience.
• Skilled Python developer, familiarity with analyzing the large scale data required to train and test ML models.
• Experience designing unique metrics that capture key aspects of system behavior and are used to enhance model development.
  
  

Bonus Skills:

• Experience training machine learning models, familiarity with state-of-the-art ML model architectures.
• Deep experience with a specific aspect of machine learning for autonomous robotics (perception, prediction, or planning).
• Knowledge of C++, especially applied to safety critical systems.
• Experience with systems verification and validation techniques
• Experience with regression testing updates to already-deployed software in a safety-critical environment.
• Experience with automotive standards (E.g: ISO 12207, ISO 26262, ISO 21448)
• Experience with software quality management and assurance activities (E.g: IATF 16949, ISO 9001)
• Thorough understanding of robotics systems including sensors, actuators, mechatronics and software systems
• Work in cross collaboration teams to address problems and find solutions
  
  

Physical Demands:

While performing the duties of this job, the employee is frequently required to sit, talk, or hear. The employee is occasionally required to stand and at times for long periods; walk; use hands to finger, handle, or feel; reach with hands and arms. The employee must occasionally lift and move up to 50 pounds.

Travel Requirements (greater than 20%):
Expected to travel for 1-2 weeks each quarter visiting all of our testing sites - mostly to LV, but also domestically as needed for the business.

Working Environment

The work environment characteristics described here represent those a team member encounters while performing the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and/or airborne particlesThe noise level in the environment is low to moderate. 

Motional AD LLC is an Equal Employment Opportunity employer and we welcome all qualified applicants.  All applicants will receive impartial consideration without regard to race, sex, color, national origin, age, disability, veteran status, genetic data, religion, gender identity, sexual orientation or other legally protected status.  Motional AD LLC is a Drug-free workplace.

Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.

The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.

Mission Summary:

The Autonomy Subsystems team at Motional is focused on designing and evaluating modules of the autonomy software. We are seeking a talented senior engineer to contribute to evaluation of our machine learning subsystems. Our team performs a variety of evaluations of machine learning models, including offline model eval, evaluation of open and closed-loop re-simulations, and assessment of on-road performance. Our goal is to establish metrics that describe autonomy subsystem performance, evaluate against those metrics to validate performance, and provide meaningful insight to ML developers and teams, working closely alongside them to improve the performance of ML models on the car.

We are looking for a highly-technical systems engineer with experience designing and evaluating safety critical systems and machine learning models. Bring your passion for autonomy, robotics, and machine learning to our team to help build a production-ready system and prepare for our scaled robotaxi service deployment.

Responsibilities:

• Define, prototype, and validate advanced metrics that bring new insights to model performance evaluation for autonomy subsystems (mainly focused on perception, prediction, and planning).
• Assess coverage of existing training and testing, then curate test sets that sufficiently capture Motional’s intended deployment operational design domain, across many axes (agent types, interaction types, map/spatial, etc.).
• Evaluate machine learning model performance against these metrics and tests.
• Assess system-level performance and subsystem contribution to system behavior through large-scale data analysis of on-road and simulation events.
• Define performance requirements for autonomy subsystems, and supporting analyses required to establish these targets.
• Coordinate subsystem-level evaluation with other system-level testing efforts across the systems team in support of the safety case and safety claims.
  
  

Qualifications:

• An engineer who has demonstrated strong cross-functional collaborative skills and is highly self-starting. This is a highly cooperative role across systems, autonomy, infrastructure, and other parts of the organization.
• Proven engineer with 5+ years of experience working on high-tech safety critical systems or robotics, ideally from a systems, robotics, or similar background.
• Master’s degree in relevant fields (systems, robotics, ML, CS, etc.) or Bachelor’s degree plus significant relevant in-field experience.
• Skilled Python developer, familiarity with analyzing the large scale data required to train and test ML models.
• Experience designing unique metrics that capture key aspects of system behavior and are used to enhance model development.
  
  

Bonus Skills:

• Experience training machine learning models, familiarity with state-of-the-art ML model architectures.
• Deep experience with a specific aspect of machine learning for autonomous robotics (perception, prediction, or planning).
• Knowledge of C++, especially applied to safety critical systems.
• Experience with systems verification and validation techniques
• Experience with regression testing updates to already-deployed software in a safety-critical environment.
• Experience with automotive standards (E.g: ISO 12207, ISO 26262, ISO 21448)
• Experience with software quality management and assurance activities (E.g: IATF 16949, ISO 9001)
• Thorough understanding of robotics systems including sensors, actuators, mechatronics and software systems
• Work in cross collaboration teams to address problems and find solutions
  
  

Physical Demands:

While performing the duties of this job, the employee is frequently required to sit, talk, or hear. The employee is occasionally required to stand and at times for long periods; walk; use hands to finger, handle, or feel; reach with hands and arms. The employee must occasionally lift and move up to 50 pounds.

Travel Requirements (greater than 20%):
Expected to travel for 1-2 weeks each quarter visiting all of our testing sites - mostly to LV, but also domestically as needed for the business.

Working Environment

The work environment characteristics described here represent those a team member encounters while performing the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and/or airborne particlesThe noise level in the environment is low to moderate. 

Motional AD LLC is an Equal Employment Opportunity employer and we welcome all qualified applicants.  All applicants will receive impartial consideration without regard to race, sex, color, national origin, age, disability, veteran status, genetic data, religion, gender identity, sexual orientation or other legally protected status.  Motional AD LLC is a Drug-free workplace.

Mission Summary:

At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery.

As a Senior Machine Learning Engineer on the Data Mining team, your mission is to build the "Brain" of this engine: designing massive multimodal Teacher models that understand the world, and distilling them into hyper-efficient Student models that can scour exabytes of data in near real-time. You will work at the intersection of large-scale representation learning, retrieval optimization, and reasoning systems. Your work will directly influence how we compress knowledge into efficient encoders for fast search, and how we apply reinforcement learning to optimize data discovery workflows and intelligent querying. By building smarter mining tools, you will accelerate the entire model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation.

What You'll Do:

• Architect and Train Distilled Models: Design and implement teacher-student model frameworks for multimodal sensor data. Develop training pipelines for knowledge distillation. Ensure student models maintain high accuracy while drastically reducing inference latency and memory footprint.
• Reinforcement Learning for Data Discover: Build RL-based policy learning and reasoning systems for autonomous driving applications. Implement and scale RL training workflows (e.g., PPO, DQN, actor-critic methods) for simulation and real-world interaction. Explore reward shaping, environment modeling, and multi-agent RL where applicable.
• Optimize Model Deployment for Real-Time Inference: Collaborate with backend engineers to deploy distilled and RL models into production. Optimize for latency, throughput, and hardware efficiency across GPU/CPU clusters. Implement model versioning, A/B testing, and monitoring for performance regressions.
• Research and Integrate Agentic Systems: Explore and prototype agentic workflows for autonomous reasoning, chain-of-thought prompting, and goal-directed behavior. Integrate such systems into our broader autonomy stack as experimental or production components.
• Drive Production Reliability: Establish patterns for graceful degradation, fault tolerance, and cost optimization. Operate Omnitag as a mission-critical data platform serving the entire ML organization, with a focus on reliability, debuggability, and operational excellence.
• Mentor and Collaborate: Work closely with ML scientists, data engineers, and autonomy teams to translate research advances into scalable engineering solutions. Guide junior engineers in best practices for model training, evaluation, and deployment.

What We're Looking For:

• BS in Computer Science, Machine Learning, or related field, or equivalent professional experience.
• 6+ years of hands-on experience in machine learning engineering, with a focus on model post training, optimization, and deployment.
• Strong experience with model distillation or teacher-student training - practical knowledge of loss functions, training strategies, and evaluation of compressed models.
• Proven experience with reinforcement learning in production or research settings: policy optimization, reward design, simulation environments, and RL-based reasoning.
• Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX).
• Strong software engineering fundamentals: testing, CI/CD, containerization, and system design.
• Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for inference.
• Demonstrated ability to ship production-grade ML systems and mentor team members.
• Demonstrated track record of shipping robust, well-tested, production-grade systems and mentoring junior engineers

Bonus Points (Nice-to-Haves):

• MS/PhD in Computer Science, Machine Learning, or related field.
• Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning.
• Background in autonomous driving, robotics, or real-time decision-making systems.
• Familiarity with multimodal learning, sensor fusion, or embodied AI.
• Experience building active learning loops, using the model to find the data that breaks the model.
• Experience with ML-based data mining, active learning, or contrastive learning.
• Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms.
• Publications or open-source contributions in RL, distillation, or efficient ML.
  
  

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

Motional’s Las Vegas office is located less than 10 miles from the Las Vegas strip at 730 E Pilot Road and is home to one of the largest fleets of self-driving vehicles. The city’s grid system of roads and being one of America’s “smart cities” allows for extensive research and development testing.

Mission Summary:

The Remote Vehicle Assistance Agent monitors live data and provides remote assistance to Motional vehicles in autonomous mode when they encounter unknown situations. Using proprietary software tools, agents interact with the AV and provide context and assistance to allow the vehicle to continue its mission - no steering wheel required. 

What you'll be doing:

• Monitor Motional autonomous vehicles (AV) operating on closed courses and public roads
• Assist in the AV decision making with real world events to ensure safe and efficient paths of travel
• Monitor AV camera feed to ensure the cameras and AV are functioning properly
• Monitor AV systems to ensure AV and systems are functioning properly
• Provide support to AV in real time to assist with direction or safety of travel
• Work closely with various engineering teams for system testing and testing of new scenarios
• Work closely with design teams to support development of functions and performance of AV
• Interact with AV to resolve tickets and issues through various software and hardware
• Reporting of system functionality issues to management in a timely manner
• Other duties as assigned
  
  

What we're looking for:

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily.  Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.  The requirements listed below are representative of knowledge, skill and/or ability required.

• Strong collaboration skills
• Proficiency in G-suite applications
• Independent, detail-oriented and exemplary organizational and time management skills
• Strong capability in analytical/ problem solving 
• Excellent written and verbal communication skills
• Prior experience as an Operator/Driver for Autonomous Vehicles, including some type of internal or external training on Autonomous Vehicle technology is preferred
• Basic working-knowledge of Autonomous Vehicle technology
• Experience and training on providing subjective feedback on vehicle behaviors and environment
• Local knowledge of city of streets, geography and environmental features that may be challenging for Autonomous Vehicles
• High school diploma or equivalency
• Able to work days, nights and weekends
• Must be able to use company communication systems and communicate clearly and effectively both written and verbal
• Must be able to read a map and possess and/or learn traffic laws for locations where AV operate
  
  

Physical Demands:

While performing the duties of this job, the employee is frequently required to sit, talk, or hear. The employee is occasionally required to stand; walk; use hands to finger, handle, or feel; reach with hands and arms. The employee must occasionally lift and/or move up to 50 pounds.

• Requires near/far/depth and color vision to safely assist Autonomous Vehicles and computer screens
• Able to stay awake and alert on shift at all times
• Able to sit/stand for up to 10 hours at a desk
  
  

Working Environment:

The work environment characteristics described here are representative of those a team member encounters while performing the essential functions of this job.  Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions.

The job operates in a combination of a professional office environment and the garage where company vehicles are stored and repaired.  This role routinely uses standard office equipment such as computers, phones, photocopiers and filing cabinets.  While performing some duties of this job, the employee is occasionally exposed to vehicle related fumes or airborne particles, moving vehicles and noise levels vary depending on the location within the building.  This position will also spend time outside as well as at our training tracks.

Motional AD LLC is an Equal Employment Opportunity employer and we welcome all qualified applicants.  All applicants will receive impartial consideration without regard to race, sex, color, national origin, age, disability, veteran status, genetic data, religion, gender identity, sexual orientation or other legally protected status.  Motional AD LLC is a Drug-free workplace.

This role is based in our Las Vegas office and requires on-site days each week.

Mission Summary:

At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery.

As a Senior Machine Learning Engineer on the Data Mining team, your mission is to build the "Brain" of this engine: designing massive multimodal Teacher models that understand the world, and distilling them into hyper-efficient Student models that can scour exabytes of data in near real-time. You will work at the intersection of large-scale representation learning, retrieval optimization, and reasoning systems. Your work will directly influence how we compress knowledge into efficient encoders for fast search, and how we apply reinforcement learning to optimize data discovery workflows and intelligent querying. By building smarter mining tools, you will accelerate the entire model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation.

What You'll Do:

• Architect and Train Distilled Models: Design and implement teacher-student model frameworks for multimodal sensor data. Develop training pipelines for knowledge distillation. Ensure student models maintain high accuracy while drastically reducing inference latency and memory footprint.
• Reinforcement Learning for Data Discover: Build RL-based policy learning and reasoning systems for autonomous driving applications. Implement and scale RL training workflows (e.g., PPO, DQN, actor-critic methods) for simulation and real-world interaction. Explore reward shaping, environment modeling, and multi-agent RL where applicable.
• Optimize Model Deployment for Real-Time Inference: Collaborate with backend engineers to deploy distilled and RL models into production. Optimize for latency, throughput, and hardware efficiency across GPU/CPU clusters. Implement model versioning, A/B testing, and monitoring for performance regressions.
• Research and Integrate Agentic Systems: Explore and prototype agentic workflows for autonomous reasoning, chain-of-thought prompting, and goal-directed behavior. Integrate such systems into our broader autonomy stack as experimental or production components.
• Drive Production Reliability: Establish patterns for graceful degradation, fault tolerance, and cost optimization. Operate Omnitag as a mission-critical data platform serving the entire ML organization, with a focus on reliability, debuggability, and operational excellence.
• Mentor and Collaborate: Work closely with ML scientists, data engineers, and autonomy teams to translate research advances into scalable engineering solutions. Guide junior engineers in best practices for model training, evaluation, and deployment.

What We're Looking For:

• BS in Computer Science, Machine Learning, or related field, or equivalent professional experience.
• 6+ years of hands-on experience in machine learning engineering, with a focus on model post training, optimization, and deployment.
• Strong experience with model distillation or teacher-student training - practical knowledge of loss functions, training strategies, and evaluation of compressed models.
• Proven experience with reinforcement learning in production or research settings: policy optimization, reward design, simulation environments, and RL-based reasoning.
• Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX).
• Strong software engineering fundamentals: testing, CI/CD, containerization, and system design.
• Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for inference.
• Demonstrated ability to ship production-grade ML systems and mentor team members.
• Demonstrated track record of shipping robust, well-tested, production-grade systems and mentoring junior engineers

Bonus Points (Nice-to-Haves):

• MS/PhD in Computer Science, Machine Learning, or related field.
• Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning.
• Background in autonomous driving, robotics, or real-time decision-making systems.
• Familiarity with multimodal learning, sensor fusion, or embodied AI.
• Experience building active learning loops, using the model to find the data that breaks the model.
• Experience with ML-based data mining, active learning, or contrastive learning.
• Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms.
• Publications or open-source contributions in RL, distillation, or efficient ML.
  
  

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

Mission Summary:

At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery.

As a Senior Machine Learning Engineer on the Data Mining team, your mission is to build the "Brain" of this engine: designing massive multimodal Teacher models that understand the world, and distilling them into hyper-efficient Student models that can scour exabytes of data in near real-time. You will work at the intersection of large-scale representation learning, retrieval optimization, and reasoning systems. Your work will directly influence how we compress knowledge into efficient encoders for fast search, and how we apply reinforcement learning to optimize data discovery workflows and intelligent querying. By building smarter mining tools, you will accelerate the entire model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation.

What You'll Do:

• Architect and Train Distilled Models: Design and implement teacher-student model frameworks for multimodal sensor data. Develop training pipelines for knowledge distillation. Ensure student models maintain high accuracy while drastically reducing inference latency and memory footprint.
• Reinforcement Learning for Data Discover: Build RL-based policy learning and reasoning systems for autonomous driving applications. Implement and scale RL training workflows (e.g., PPO, DQN, actor-critic methods) for simulation and real-world interaction. Explore reward shaping, environment modeling, and multi-agent RL where applicable.
• Optimize Model Deployment for Real-Time Inference: Collaborate with backend engineers to deploy distilled and RL models into production. Optimize for latency, throughput, and hardware efficiency across GPU/CPU clusters. Implement model versioning, A/B testing, and monitoring for performance regressions.
• Research and Integrate Agentic Systems: Explore and prototype agentic workflows for autonomous reasoning, chain-of-thought prompting, and goal-directed behavior. Integrate such systems into our broader autonomy stack as experimental or production components.
• Drive Production Reliability: Establish patterns for graceful degradation, fault tolerance, and cost optimization. Operate Omnitag as a mission-critical data platform serving the entire ML organization, with a focus on reliability, debuggability, and operational excellence.
• Mentor and Collaborate: Work closely with ML scientists, data engineers, and autonomy teams to translate research advances into scalable engineering solutions. Guide junior engineers in best practices for model training, evaluation, and deployment.

What We're Looking For:

• BS in Computer Science, Machine Learning, or related field, or equivalent professional experience.
• 6+ years of hands-on experience in machine learning engineering, with a focus on model post training, optimization, and deployment.
• Strong experience with model distillation or teacher-student training - practical knowledge of loss functions, training strategies, and evaluation of compressed models.
• Proven experience with reinforcement learning in production or research settings: policy optimization, reward design, simulation environments, and RL-based reasoning.
• Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX).
• Strong software engineering fundamentals: testing, CI/CD, containerization, and system design.
• Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for inference.
• Demonstrated ability to ship production-grade ML systems and mentor team members.
• Demonstrated track record of shipping robust, well-tested, production-grade systems and mentoring junior engineers

Bonus Points (Nice-to-Haves):

• MS/PhD in Computer Science, Machine Learning, or related field.
• Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning.
• Background in autonomous driving, robotics, or real-time decision-making systems.
• Familiarity with multimodal learning, sensor fusion, or embodied AI.
• Experience building active learning loops, using the model to find the data that breaks the model.
• Experience with ML-based data mining, active learning, or contrastive learning.
• Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms.
• Publications or open-source contributions in RL, distillation, or efficient ML.
  
  

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

Mission Summary:

At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery.

As a Senior Machine Learning Engineer on the Data Mining team, your mission is to build the "Brain" of this engine: designing massive multimodal Teacher models that understand the world, and distilling them into hyper-efficient Student models that can scour exabytes of data in near real-time. You will work at the intersection of large-scale representation learning, retrieval optimization, and reasoning systems. Your work will directly influence how we compress knowledge into efficient encoders for fast search, and how we apply reinforcement learning to optimize data discovery workflows and intelligent querying. By building smarter mining tools, you will accelerate the entire model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation.

What You'll Do:

• Architect and Train Distilled Models: Design and implement teacher-student model frameworks for multimodal sensor data. Develop training pipelines for knowledge distillation. Ensure student models maintain high accuracy while drastically reducing inference latency and memory footprint.
• Reinforcement Learning for Data Discover: Build RL-based policy learning and reasoning systems for autonomous driving applications. Implement and scale RL training workflows (e.g., PPO, DQN, actor-critic methods) for simulation and real-world interaction. Explore reward shaping, environment modeling, and multi-agent RL where applicable.
• Optimize Model Deployment for Real-Time Inference: Collaborate with backend engineers to deploy distilled and RL models into production. Optimize for latency, throughput, and hardware efficiency across GPU/CPU clusters. Implement model versioning, A/B testing, and monitoring for performance regressions.
• Research and Integrate Agentic Systems: Explore and prototype agentic workflows for autonomous reasoning, chain-of-thought prompting, and goal-directed behavior. Integrate such systems into our broader autonomy stack as experimental or production components.
• Drive Production Reliability: Establish patterns for graceful degradation, fault tolerance, and cost optimization. Operate Omnitag as a mission-critical data platform serving the entire ML organization, with a focus on reliability, debuggability, and operational excellence.
• Mentor and Collaborate: Work closely with ML scientists, data engineers, and autonomy teams to translate research advances into scalable engineering solutions. Guide junior engineers in best practices for model training, evaluation, and deployment.

What We're Looking For:

• BS in Computer Science, Machine Learning, or related field, or equivalent professional experience.
• 6+ years of hands-on experience in machine learning engineering, with a focus on model post training, optimization, and deployment.
• Strong experience with model distillation or teacher-student training - practical knowledge of loss functions, training strategies, and evaluation of compressed models.
• Proven experience with reinforcement learning in production or research settings: policy optimization, reward design, simulation environments, and RL-based reasoning.
• Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX).
• Strong software engineering fundamentals: testing, CI/CD, containerization, and system design.
• Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for inference.
• Demonstrated ability to ship production-grade ML systems and mentor team members.
• Demonstrated track record of shipping robust, well-tested, production-grade systems and mentoring junior engineers

Bonus Points (Nice-to-Haves):

• MS/PhD in Computer Science, Machine Learning, or related field.
• Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning.
• Background in autonomous driving, robotics, or real-time decision-making systems.
• Familiarity with multimodal learning, sensor fusion, or embodied AI.
• Experience building active learning loops, using the model to find the data that breaks the model.
• Experience with ML-based data mining, active learning, or contrastive learning.
• Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms.
• Publications or open-source contributions in RL, distillation, or efficient ML.
  
  

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

Join Horace Mann: Empower Educators, Achieve Financial Success

Ready to Make a Difference?

Join Horace Mann today and take the first step toward achieving your career and financial goals while making a meaningful impact on the educators you serve. Together, we can help educators secure their future while empowering you to achieve your own.

As an Insurance Producer at Horace Mann, you’ll receive mentorship from an experienced agent while gaining hands-on experience in the industry. Our insurance products are tailored to meet the unique needs of educators, and we provide outstanding training, competitive rates, and flexible work options. With an unparalleled compensation structure, exciting incentives, and bonus opportunities, top performers have the chance to earn all-expenses-paid trips to amazing destinations.

Why Join Us?

• Performance-Based Compensation [1099] with a 36-month incentive plan and enhanced commissions
• Monthly incentives based on sales volume for the first 36 months
• Quarterly production bonuses for the first 36 months
• Leverage established books of business while building your own practice
• Access to a niche market that increases your potential for success
• Value-added services to connect you with ideal clients
• Simple, streamlined products and sales processes for quick success
• Networking, community, and industry events to expand your connections
• A comprehensive, multi-line product portfolio in a ‘One-Stop Shop’ model

What You Will Do:

• Solve financial challenges faced by educators through tailored solutions
• Present with confidence—one-on-one or in large groups—to educate potential clients on products
• Engage in community and networking events, expanding your professional connections
• Stay current with industry trends and apply new knowledge to help clients
• Cultivate strong market relationships and build a solid client base
• Invest time and resources in ensuring the success and growth of your business

What We’re Looking For:

• A commitment to helping educators achieve financial prosperity
• Strong interpersonal and presentation skills
• Self-motivation and the ability to manage your own business
• The ability to obtain or currently hold state licenses in Life & Health and Property & Casualty

Compensation and Benefits:

• Sign-On Bonus
• Uncapped Earnings/Commission
• Structured Incentive & Bonus Pay to reward your hard work
• Work Environment—work in-person, in the field, and/or from an office setting

Support and Accountability:

As an Insurance Producer, you'll be guided by a mentor agent who will support you every step of the way to ensure your success.

We make a difference!

At Horace Mann, we are driven by our mission to support the educators who shape the future of our children. We believe that educators deserve someone who looks after their financial well-being just as they do for their students. Our passion lies in providing tailored solutions that protect what educators have today and help them achieve long-term financial security and happiness.

#LI-WW1

#VIZI#

Since 1946, Kimball Equipment Company has been a trusted leader in the aggregate mining and supply industry. As an authorized dealer for globally recognized brands such as Terex Cedarapids, Terex Finlay, and Superior Industries, we have built our reputation on technical expertise, outstanding service, and long-term customer partnerships. With strong growth and continued expansion ahead, we are seeking a strategic and detail-oriented Purchasing Agent to join our corporate team.

This is an exciting opportunity for an experienced purchasing professional—or a former purchasing manager—who is looking for a stable, growing company where their expertise will make an immediate impact.

What You’ll Do

• Develop, maintain, and manage strong supplier relationships that ensure quality, reliability, and cost-effectiveness
• Monitor and forecast inventory requirements to align purchasing decisions with operational needs
• Source, negotiate, and secure favorable terms on parts, materials, and equipment
• Oversee the purchase order process, ensuring accuracy, timeliness, and compliance with negotiated agreements
• Track and evaluate supplier performance; identify and resolve issues to maintain high standards
• Research emerging products, materials, and technologies to strengthen our competitive edge
• Partner closely with internal teams (operations, sales, and service) to support company-wide goals

What We’re Looking For

• Proven purchasing/procurement experience (manufacturing, distribution, or heavy equipment industry preferred)
• Experience in vendor management, sourcing strategies, and contract negotiation
• Proficiency in Microsoft Office; ERP system experience is highly desirable
• Strong analytical ability to forecast needs, evaluate cost drivers, and manage budgets
• Excellent communication and relationship-building skills
• A self-starter who can work independently yet thrives in a team-oriented environment
• Leadership potential or prior experience at a manager level is a plus

Why Join Kimball?

• Competitive compensation package, commensurate with experience
• Comprehensive benefits, including 401(k) with company match, PTO, health, dental, vision, and life insurance
• The stability of a company with nearly 80 years of industry leadership—and the energy of a team that’s growing and innovating
• A chance to make a visible impact in a role that directly contributes to company success
• Career advancement opportunities for those who want to take on greater responsibility in the future

If you’re ready to bring your purchasing expertise to a company that values experience, initiative, and long-term growth, we’d love to talk with you. 

Please note that the position is available at our Salt Lake City or Las Vegas Corporate locations.

Apply today and build your career with Kimball Equipment Company.