THE ROLE:

Are you passionate about driving innovation in the data storage industry? Are you skilled in crafting technical solutions that exceed customer expectations? If so, we have an exciting opportunity for you! Everpure (formerly Pure Storage), a leader in the data storage and flash technology space, is seeking a talented and motivated Senior Pre-Sales Systems Engineer to join our dynamic team. 

As a Senior Pre-Sales Systems Engineer, you will play a crucial role in understanding our customers' unique challenges and tailoring Everpure solutions to meet their specific needs. Collaborating closely with the sales team, you will act as a technical expert during the sales process, helping to showcase the value of our products and services.

WHAT YOU’LL DO:

• Develop an exhaustive understanding of what drives a customer’s business and what motivates their decision making
• Connect the dots from technology solutions, inclusive of the Everpure portfolio and others from the ecosystem, to measurable customer business outcomes
• Partner closely with account managers, specialists and channel partners to create a seamless and holistic customer experience and strategy to drive revenue growth and net new business
• Delight customers and teammates with your technical leadership and domain expertise on storage products, distributed storage architectures, file systems, and competitive storage offerings in the DAS, NAS and SAN product spaces
• Take control of evaluations,  benchmarks and system configurations
• Build and deliver technical product and architecture presentations with vigor to customers and lock in the technical win with clients and prospective accounts
• Capture requirements and translate Customer’s business needs into innovative solutions to accelerate their growth and capacity
• Seek out and spur new opportunities for interoperability, functional, and performance testing/validation
• Promote mutual roadmap and planning exchanges
• Liaise with product and technical marketing to produce materials (i.e. whitepaper, web presentations) that support overall alliance plans and objectives
• Stay current with the competition and ensure that materials accurately reflect the latest, differentiated solution positioning
• Move with market trends and competitive landscape to promote thought leadership within our organization
• Lead by example living the Everpure Values:  Persistence, Creativity, Teamwork, Ownership and Customer-first  

WHAT YOU BRING:

• Pre-sales experience is required
• 5 or more years of relevant experience, mixed among technology, design, and communications required. Experience supporting the sales of enterprise storage, networking, systems, cloud, or software to enterprise accounts preferred
• Deep understanding of the architecture, design and implementation of multi-tiered client/server and web-based computing solutions
• Must have a familiarity with modern web architecture a plus (LAMP stack, scale-out vs scale-up architectures, AWS well-architected framework, microservices architecture)
• Prior experience in targeting new prospects and converting them into clients
• Contribute significant portions and/or lead responses to RFPs, RFQs and RFIs
• Superior knowledge of current and emerging storage architectures (FC, iSCSI, NAS, OSD, SAN)
• Previous experience with Linux, NFS file systems and Linux distributed network environment
• Installation/configuration of distributed computing, multiprocessing, virtual memory subsystem, storage subsystems architecture, shared memory architectures, cache architectures, windowing systems
• Strong knowledge of digital transformation to a Cloud Native architecture, On-Prem, Public Cloud, Provisioning Automation, and Containers
• Knowledge of VMware, Local Area Networking, Ethernet, TCP/IP and general networking
• Familiarity with AWS, Azure, GCP, containers, k8s and microservices architectures a plus
• Curiosity and passion around technology and explaining and showing new technology platforms and concepts to customers
• Familiarity with storage-intensive applications and their requirements such as structured databases (SQL, Oracle) is highly desirable
• Excellent verbal and written interpersonal skills

#LI-REMOTE

#LI-JL4

About the Role

The Revenue Operations team at Gusto is a full-stack team responsible for data, analytics, and operational excellence in pursuit of scaling our revenue growth. The Go-To-Market Analytics team is one functional area, responsible for defining and owning the metrics for scaling our Sales teams. 

Gusto is looking for a Revenue Analytics Engineer to build and maintain foundational data infrastructure that is crucial to growing and scaling our Sales efforts. In this role, you will partner with our GTM analysts to scope and deliver data products for an audience ranging from company and revenue leadership to operational and frontline sales. In doing so, you will own significant portions of our sales data from end-to-end, focusing on the transformation, design, and visualization workflows. In addition, you will establish best practices for systems design and workflows to maximize usefulness of AI at scale. 

This role will report to the Head of Go-To-Market analytics, and partner closely with Data Science, Data Platform, and Business Technology teams. 

Here’s what you’ll do day-to-day:

• Establish relationships with internal stakeholders to determine business needs, scoping and delivering solutions through data products
• Design, build, and maintain data pipelines and dashboards to automate “keep the lights on” work out of manually-managed processes
• Build a data foundation by incorporating business logic into raw data tables, laying the groundwork to enable value-add insights
• Create a dynamic reporting environment based on stakeholder needs
• Identify data discrepancies and set best practices for data logic to create a clean and well-documented environment
• Collaborate with broader data organization as steward to the definition and process management of core Gusto metrics

Here’s what we're looking for:

• Education or work experience in Engineering or Computer Science, or a related technical field 
• 7+ years of experience in an analytics engineering, business intelligence, or technical data analytics role
• Experience with SQL and ETL optimization techniques, especially within cloud-based data warehouses like Redshift, Snowflake, etc.
• Command-line experience and familiarity with version control collaboration tools (git)
• Experience with data pipeline management technologies with dependency checking, such as Airflow, as well as schema design and data modeling tools (dbt)
• Experience with data visualization technologies, e.g., Tableau, Looker, Sigma, Mode, Hex
• Experience with Python and data ingestion tools
• Ability to problem-solve open-ended problems and project manage dependencies and timelines to optimal outcomes
• Ability to demonstrate tools, business intuition, and attention to detail for data validation and QA 

Our cash compensation amount for this role is targeted at $138,000-156,000 in Denver & most remote locations, and $168,000-189,000 in New York & San Francisco Bay Area. Stock equity is additional. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

Mission Summary:

As a Staff Engineer within the Platform Engineering team, you will be a hands-on technical leader driving the evolution of Motional's global cloud and hybrid infrastructure. Operating as a senior individual contributor, you'll tackle our hardest platform problems directly — designing systems, creating code, and setting technical direction for initiatives that span multiple teams. Your work will help transform our R&D environment into a hardened, cost-efficient, and scalable commercial backbone, and ensure our internal platforms deliver the developer velocity required for rapid AV deployment.

What you'll be doing:

• Design and build major components of our cloud architecture — including networking, storage, compute abstraction layers. You'll own the technical design end-to-end and create code where it matters most
• Drive technical evolution of our Kubernetes-based developer platform. Identify the highest-leverage improvements to scalability, cost attribution, access control, and developer ergonomics — then design and implement them to reduce configuration complexity and accelerate engineering velocity
• Raise the reliability bar across Platform Engineering. Define and implement standards for SLIs, SLOs, observability, and failover, and partner with peer teams to roll them out across platform-layer services
• Drive FinOps practices — cost visibility, attribution, accountability as well as optimization recommendations
• Design and ship AI-native developer experiences by integrating LLM-powered tooling into CI, build systems, monitoring platforms, and local development workflows to remove friction and boost engineering throughput
  
  

What we're looking for:

• Bachelor's or Master's in Computer Science, Engineering, or a related field (or equivalent practical experience)
• 9 years in Software or Infrastructure Engineering, with significant experience in a senior IC capacity
• Deep, expert-level knowledge of Kubernetes internals and ecosystem (Operators (Crossplane, ArgoWorkflow/Airflow, KubeRay), Kubecost/OpenCost, Service Mesh, GitOps and other CNCF projects)
• Proven track record of designing or migrating complex workloads between on-prem data centers and major cloud providers (AWS, GCP, other)
• Experience with Infrastructure-as-Code (Terraform/CloudFormation, Terraform Cloud/Spacelift/Atlantis) and advanced observability tooling (OpenTelemetry, Prometheus/VictoriaMetrics, Grafana, Datadog)
• Expert in architecting AI-driven operations, leveraging LLMs and agentic workflows to automate incident response, predictive scaling, and intelligent system observability
• Demonstrated ability to influence technical roadmaps across an entire engineering organization and mentor senior technical staff
  
  

Bonus points (not required):

• Proven expertise in CI/CD orchestration, build systems (Bazel, RBE), frameworks
• Prior experience with large-scale machine learning training pipelines
• Experience leading technical projects in a globally distributed team
• Open-source contributions to Kubernetes, observability, or infrastructure tooling ecosystems

Mission Summary:

As a Staff Engineer within the Platform Engineering team, you will be a hands-on technical leader driving the evolution of Motional's global cloud and hybrid infrastructure. Operating as a senior individual contributor, you'll tackle our hardest platform problems directly — designing systems, creating code, and setting technical direction for initiatives that span multiple teams. Your work will help transform our R&D environment into a hardened, cost-efficient, and scalable commercial backbone, and ensure our internal platforms deliver the developer velocity required for rapid AV deployment.

What you'll be doing:

• Design and build major components of our cloud architecture — including networking, storage, compute abstraction layers. You'll own the technical design end-to-end and create code where it matters most
• Drive technical evolution of our Kubernetes-based developer platform. Identify the highest-leverage improvements to scalability, cost attribution, access control, and developer ergonomics — then design and implement them to reduce configuration complexity and accelerate engineering velocity
• Raise the reliability bar across Platform Engineering. Define and implement standards for SLIs, SLOs, observability, and failover, and partner with peer teams to roll them out across platform-layer services
• Drive FinOps practices — cost visibility, attribution, accountability as well as optimization recommendations
• Design and ship AI-native developer experiences by integrating LLM-powered tooling into CI, build systems, monitoring platforms, and local development workflows to remove friction and boost engineering throughput
  
  

What we're looking for:

• Bachelor's or Master's in Computer Science, Engineering, or a related field (or equivalent practical experience)
• 9 years in Software or Infrastructure Engineering, with significant experience in a senior IC capacity
• Deep, expert-level knowledge of Kubernetes internals and ecosystem (Operators (Crossplane, ArgoWorkflow/Airflow, KubeRay), Kubecost/OpenCost, Service Mesh, GitOps and other CNCF projects)
• Proven track record of designing or migrating complex workloads between on-prem data centers and major cloud providers (AWS, GCP, other)
• Experience with Infrastructure-as-Code (Terraform/CloudFormation, Terraform Cloud/Spacelift/Atlantis) and advanced observability tooling (OpenTelemetry, Prometheus/VictoriaMetrics, Grafana, Datadog)
• Expert in architecting AI-driven operations, leveraging LLMs and agentic workflows to automate incident response, predictive scaling, and intelligent system observability
• Demonstrated ability to influence technical roadmaps across an entire engineering organization and mentor senior technical staff
  
  

Bonus points (not required):

• Proven expertise in CI/CD orchestration, build systems (Bazel, RBE), frameworks
• Prior experience with large-scale machine learning training pipelines
• Experience leading technical projects in a globally distributed team
• Open-source contributions to Kubernetes, observability, or infrastructure tooling ecosystems

Mission Summary:

As a Staff Engineer within the Platform Engineering team, you will be a hands-on technical leader driving the evolution of Motional's global cloud and hybrid infrastructure. Operating as a senior individual contributor, you'll tackle our hardest platform problems directly — designing systems, creating code, and setting technical direction for initiatives that span multiple teams. Your work will help transform our R&D environment into a hardened, cost-efficient, and scalable commercial backbone, and ensure our internal platforms deliver the developer velocity required for rapid AV deployment.

What you'll be doing:

• Design and build major components of our cloud architecture — including networking, storage, compute abstraction layers. You'll own the technical design end-to-end and create code where it matters most
• Drive technical evolution of our Kubernetes-based developer platform. Identify the highest-leverage improvements to scalability, cost attribution, access control, and developer ergonomics — then design and implement them to reduce configuration complexity and accelerate engineering velocity
• Raise the reliability bar across Platform Engineering. Define and implement standards for SLIs, SLOs, observability, and failover, and partner with peer teams to roll them out across platform-layer services
• Drive FinOps practices — cost visibility, attribution, accountability as well as optimization recommendations
• Design and ship AI-native developer experiences by integrating LLM-powered tooling into CI, build systems, monitoring platforms, and local development workflows to remove friction and boost engineering throughput
  
  

What we're looking for:

• Bachelor's or Master's in Computer Science, Engineering, or a related field (or equivalent practical experience)
• 9 years in Software or Infrastructure Engineering, with significant experience in a senior IC capacity
• Deep, expert-level knowledge of Kubernetes internals and ecosystem (Operators (Crossplane, ArgoWorkflow/Airflow, KubeRay), Kubecost/OpenCost, Service Mesh, GitOps and other CNCF projects)
• Proven track record of designing or migrating complex workloads between on-prem data centers and major cloud providers (AWS, GCP, other)
• Experience with Infrastructure-as-Code (Terraform/CloudFormation, Terraform Cloud/Spacelift/Atlantis) and advanced observability tooling (OpenTelemetry, Prometheus/VictoriaMetrics, Grafana, Datadog)
• Expert in architecting AI-driven operations, leveraging LLMs and agentic workflows to automate incident response, predictive scaling, and intelligent system observability
• Demonstrated ability to influence technical roadmaps across an entire engineering organization and mentor senior technical staff
  
  

Bonus points (not required):

• Proven expertise in CI/CD orchestration, build systems (Bazel, RBE), frameworks
• Prior experience with large-scale machine learning training pipelines
• Experience leading technical projects in a globally distributed team
• Open-source contributions to Kubernetes, observability, or infrastructure tooling ecosystems

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

We're looking to hire for our Data side of our AI team at Speechify. This role is responsible for all aspects of data collection to support our model training operations. We are able to build high-quality datasets at petabyte-scale and low cost through a tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us.

What You’ll Do

• Be scrappy to find new sources of audio data and bring it into our ingestion pipeline
• Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform.
• Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models.
• Collaborate with others on the AI Team and Speechify Leadership to craft the AI Team’s dataset roadmap to power Speechify’s next-generation consumer and enterprise products.

An Ideal Candidate Should Have

• BS/MS/PhD in Computer Science or a related field.
• 5+ years of industry experience in software development.
• Proficiency with bash/Python scripting in Linux environments
• Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (we use GCP)
• Experience with web crawlers, large-scale data processing workflows is a plus
• Ability to handle multiple tasks and adapt to changing priorities.
• Strong communication skills, both written and verbal.

What we offer

• A fast-growing environment where you can help shape the company and product.
• An entrepreneurial-minded team that supports risk, intuition, and hustle.
• A hands-off management approach so you can focus and do your best work.
• An opportunity to make a big impact in a transformative industry.
• Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.
• Opportunity to work on a life-changing product that millions of people use.
• Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.
• Work in one of the fastest-growing sectors of tech, the intersection of artificial intelligence and audio.

Compensation: The United States base salary range for this full-time position is $140,000-$200,000 + bonus + equity depending on experience

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

The responsibilities of our Platform team include building and maintaining all backend services, including, but not limited to, payments, analytics, subscriptions, new products, text to speech, and external APIs.

This is a key role and ideal for someone who thinks strategically, enjoys fast-paced environments, is passionate about making product decisions, and has experience building great user experiences that delight users.

We are a flat organization that allows anyone to become a leader by showing excellent technical skills and delivering results consistently and fast. Work ethic, solid communication skills, and obsession with winning are paramount. 

Our interview process involves several technical interviews and we aim to complete them within 1 week. 

What You’ll Do

• Design, develop, and maintain robust APIs including public TTS API, internal APIs like Payment, Subscription, Auth and Consumption Tracking, ensuring they meet business and scalability requirements
• Oversee the full backend API landscape, enhancing and optimizing for performance and maintainability
• Collaborate on B2B solutions, focusing on customization and integration needs for enterprise clients
• Work closely with cross-functional teams to align backend architecture with overall product strategy and user experience

An Ideal Candidate Should Have

• Proven experience in backend development: TS/Node (required)
• Direct experience with GCP and knowledge of AWS, Azure, or other cloud providers
• Efficiency in ideation and implementation, prioritizing tasks based on urgency and impact
• Preferred: Experience with Docker and containerized deployments
• Preferred: Proficiency in deploying high availability applications on Kubernetes

What We Offer

• A dynamic environment where your contributions shape the company and its products
• A team that values innovation, intuition, and drive
• Autonomy, fostering focus and creativity
• The opportunity to have a significant impact in a revolutionary industry
• Competitive compensation, a welcoming atmosphere, and a commitment to an exceptional asynchronous work culture
• The privilege of working on a product that changes lives, particularly for those with learning differences like dyslexia, ADD, and more
• An active role at the intersection of artificial intelligence and audio – a rapidly evolving tech domain

The United States Based Salary range for this role is: 140,000-200,000 USD/Year + Bonus + Stock depending on experience

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

BASE SALARY: $150,000 to $190,000 per year, paid semi-monthly

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

TOTAL COMPENSATION

Base salary is set according to market rates for the nearest major metro and varies based on Launch Potato’s Levels Framework. Your compensation package includes a base salary, profit-sharing bonus, and competitive benefits. Launch Potato is a performance-driven company, which means once you are hired, future increases will be based on company and personal performance, not annual cost of living adjustments.

BASE SALARY: $150,000 to $190,000 per year, paid semi-monthly

MUST HAVE:

• 5+ years of experience in data engineering within fast-paced, cloud-native environments
• Deep expertise in Python, SQL, Docker, and AWS (S3, Glue, Kinesis, Athena/Presto)
• Experience building and managing scalable ETL pipelines and data lake infrastructure
• Familiarity with distributed systems, Spark, and data quality best practices
• Strong cross-functional collaboration skills to support BI, analytics, and engineering teams

EXPERIENCE: 5+ years of data engineering experience in an AWS-based environment where data powers decision-making across product, marketing, and operations.

YOUR ROLE

Lead scalable data engineering efforts that empower cross-functional teams with reliable, timely, and actionable data, ensuring Launch Potato’s analytics and business intelligence infrastructure fuels strategic growth.

OUTCOMES

• Build and optimize scalable, efficient ETL and data lake processes that proactively catch issues before they impact the business
• Own the ingestion, modeling, and transformation of structured and unstructured data to support reporting and analysis across all business units
• Partner closely with BI and Analytics to deliver clean, query-ready datasets that improve user acquisition, engagement, and revenue growth
• Maintain and enhance database monitoring, anomaly detection, and quality assurance workflows
• Serve as the internal point of contact for reporting infrastructure—delivering ad hoc data analyses and driving consistent data integrity
• Drive adoption and advancement of Looker dashboards by ensuring robust and scalable backend data support
• Contribute to the future of Launch Potato’s data team by mentoring peers and shaping a high-performance, quality-first engineering culture

COMPETENCIES

• Data Engineering Mastery: Demonstrates technical excellence in building data pipelines, troubleshooting distributed systems, and scaling infrastructure using AWS and open-source tools
• Cross-Functional Collaboration: Communicates clearly across technical and non-technical teams, translating business needs into robust data solutions
• Proactive Ownership: Operates with a strong sense of accountability; identifies and solves data issues independently and efficiently
• Quality-Driven Execution: Holds a high bar for data accuracy, auditability, and documentation throughout all systems and workflows
• Strategic Thinking: Anticipates how data infrastructure impacts wider company OKRs and proactively suggests improvements and innovations
• Growth Mindset: Seeks out opportunities to elevate team capabilities, mentor others, and stay ahead of evolving best practices in data engineering

TOTAL COMPENSATION

Base salary is set according to market rates for the nearest major metro and varies based on Launch Potato’s Levels Framework. Your compensation package includes a base salary, profit-sharing bonus, and competitive benefits. Launch Potato is a performance-driven company, which means once you are hired, future increases will be based on company and personal performance, not annual cost of living adjustments.

As an AWS Cloud Data Engineer, you will be responsible for designing, developing, and maintaining robust data infrastructure solutions to support the organization’s data-driven initiatives. We seek self-driven and motivated individuals who take ownership of their projects. You will collaborate closely with cross-functional teams including project managers, business analysts, and software engineers to ensure the availability, reliability, and scalability of our system.

This role is onsite and can be based at any of the following Shift4 locations: Tampa, FL / Atlanta, GA / Las Vegas, NV / Center Valley, PA

Responsibilities

Technology:

• Work hands on within the cloud data platform to deliver new features, fix issues and ensure best practices.
• Contribute to the technical design and architecture development for parts of the solution. Ensure that best practices are defined and adhered to
• Diagnose and resolve issues with deployed systems (as part of level 3 support).
• Become technically solid for the cloud data platform.
• Evaluate and resolve technical debt, engage in platform modernization and build reliable features.
• Recommend and implement best practices and standards for the cloud data platforms.

People and Leadership

• Work closely with multiple engineering teams, product owners and stakeholders to understand needs and meet data requirements.
• Interface across multiple engineering teams and engineering groups working on various parts of the platform.
• Mentor and develop junior team members.

Process

• Ensure efficient operation of Scrum within the team.
• Analyze and update tools and processes when required.
• Measure key team metrics.

Qualifications

• Bachelors or Masters degree in Computer Science, Information Systems, or a related field. Experience in lieu of a degree may be considered. 
• 3+ years of experience in cloud data engineering. 
• 2+ years working with AWS services including Redshift, AWS Glue, Lambda, DMS, Kinesis, etc.
• 1+ years working with ETL tools (MS SSIS or similar).
• Significant hands-on experience working with databases, schemas, complex queries, data modeling, stored procedures, etc. (MS SQL Server, Postgres and Redshift preferred).
• Excellent communication skills in English, with the ability to collaborate effectively with cross-functional teams and stakeholders.

Additional experience that is a plus to have:

• AWS Certified Data Engineer – Associate
• AWS Certified Cloud Practitioner
• AWS Certified AI Practitioner

Shift4 is expanding globally and seeking a key Senior AWS Cloud Data Engineer to join our team of world-class in-house engineers that will contribute to the technology, architecture and engineering delivery across an AWS Cloud Data Services team.

As a Senior AWS Cloud Data Engineer, you will be responsible for designing, developing, and maintaining robust data infrastructure solutions to support the organization’s data-driven initiatives. We seek self-driven and motivated individuals who take ownership of their projects. You will collaborate closely with cross-functional teams including project managers, business analysts, and software engineers to ensure the availability, reliability, and scalability of our system.

This role is onsite and can be based at any of the following Shift4 locations: Tampa, FL / Atlanta, GA / Las Vegas, NV / Center Valley, PA

Responsibilities

Technology:

• Work hands on within the cloud data platform to deliver new features, fix issues and ensure best practices.
• Contribute to the technical design and architecture development for parts of the solution. Ensure that best practices are defined and adhered to
• Diagnose and resolve issues with deployed systems (as part of level 3 support).
• Become a technical expert for the cloud data platform.
• Evaluate and resolve technical debt, engage in platform modernization and build reliable features.
• Recommend and implement best practices and standards for the cloud data platforms.

People and Leadership

• Work closely with multiple engineering teams, product owners and stakeholders to understand needs and meet data requirements.
• Interface across multiple engineering teams and engineering groups working on various parts of the platform.
• Mentor and develop junior team members.

Process

• Ensure efficient operation of Scrum within the team.
• Analyze and update tools and processes when required.
• Measure key team metrics.

Qualifications

• Bachelors or Masters degree in Computer Science, Information Systems, or a related field. Experience in lieu of a degree may be considered. 
• 5+ years of experience in cloud data engineering. 
• 4+ years working with AWS services including Redshift, AWS Glue, Lambda, DMS, Kinesis, etc.
• 2+ years working with ETL tools (MS SSIS or similar).
• Significant hands-on experience working with databases, schemas, complex queries, data modeling, stored procedures, etc. (MS SQL Server, Postgres and Redshift preferred).
• Excellent communication skills in English, with the ability to collaborate effectively with cross-functional teams and stakeholders.

Additional experience that is a plus to have:

• AWS Certified Data Engineer – Associate
• AWS Certified Cloud Practitioner
• AWS Certified AI Practitioner

#LI-BN1

About Axon 911 

Axon 911 brings together Prepared and Carbyne under Axon. Together, we are creating the only platform that combines modern 911 infrastructure with an AI intelligence layer—helping public safety agencies move faster, make better decisions, and deliver better outcomes in the moments that matter most.

911 is the backbone of public safety, yet the professionals behind it have long been held back by outdated technology. Axon 911 is here to change that. Joining this team means more than taking a job—it means helping shape the future of emergency response and building a safer, more connected world.

Your Impact

As a Senior Sales Engineer, Public Safety (Mountain or Pacific Region), you are both a technical expert and a storyteller. You’ll work closely with Account Executives (AEs), Regional Sales Managers (RSMs), and customers to translate complex technical requirements into compelling solutions. You will lead discovery, configure and demonstrate our platform, manage technical validations, and ensure a smooth handoff to post-sales implementation.

This role is ideal for someone who understands the intersection of technology, public safety operations, and customer success, and who thrives in a mission-driven, fast-paced environment.

What You’ll Do

Pre-Sales Solutioning

• Partner with AEs and RSMs to qualify opportunities, understand customer challenges, and design tailored technical solutions.
• Conduct in-depth discovery with 911 centers, emergency management agencies, and public safety IT teams.
• Deliver engaging product demonstrations, technical workshops, and proof-of-concept sessions tailored to the agency’s environment.
• Lead and respond to RFPs, RFIs, and security questionnaires with accuracy and professionalism.
• Translate complex technical concepts into clear, benefit-focused explanations for non-technical audiences.

Technical Leadership

• Serve as the subject-matter expert for Prepared’s platform architecture, integrations, APIs, and data workflows.
• Provide configuration and system design guidance based on customer requirements, existing CAD/NG911 systems, and IT infrastructure.
• Advise agencies on best practices for network security, system interoperability, and deployment planning.
• Stay up-to-date with public safety software trends, standards (NG911, CAD, RMS, PSAP operations), and competitor offerings.

Sales Enablement & Collaboration

• Work alongside Sales, Product, and Engineering to continuously improve our demo environments, messaging, and field readiness.
• Collect and relay customer feedback to influence product roadmap and technical documentation.
• Support proposal teams with technical content, diagrams, and specifications.
• Assist marketing and partner teams in developing technical collateral, webinars, and events.

Customer Advocacy

• Build trust with agency decision-makers, IT administrators, and operations leaders by demonstrating deep understanding of public safety workflows.
• Ensure technical confidence throughout the sales cycle to accelerate buying decisions.
• Represent Prepared at tradeshows, conferences, and industry events as a technical ambassador.

What You Bring

• 8+ years of progressive experience in public safety, emergency communications, or PSAP operations, with senior-level leadership experience strongly preferred (Director, Assistant Director, Executive Director, or equivalent).
• Demonstrated experience selling, implementing, or enabling public safety software (e.g., NG911 call handling, CAD, RMS, ESInet, radio systems, mass notification, or emergency communications platforms).
• Proven ability to operate as a field-facing technical advisor to Sales—owning discovery, solution design, demonstrations, technical validation, and RFP/RFI responses end-to-end.
• Deep understanding of PSAP workflows, operational constraints, funding models, procurement cycles, and compliance environments, including experience presenting to boards, executives, and elected officials.
• Strong technical fluency across cloud-based platforms, integrations/APIs, network infrastructure, data workflows, and system interoperability within public safety environments.

Additional Requirements

• Track record of building credibility with PSAP directors, IT leadership, emergency management leaders, and dispatch supervisors through consultative, trust-based engagement.
• Experience partnering cross-functionally with Product and Engineering to influence roadmap priorities based on real-world PSAP needs.
• Comfortable operating in high-growth, ambiguous environments with minimal playbooks—able to create structure, demo narratives, and field enablement materials where needed.
• Exceptional executive communication and storytelling skills—able to translate technical capability into operational ROI and mission impact.
• Willingness to travel up to 75% and represent Prepared as a technical ambassador at industry conferences and customer events.

Public Safety Technology & Systems Expertise

Candidates who are well-positioned for success in this role typically bring hands-on experience working with the core technology systems that power emergency communications centers.

This may include experience with:

• 911 call handling systems (CHE) such as VESTA, Viper, or Solacom
 • Computer-Aided Dispatch (CAD) platforms used to manage emergency response workflows
 • Radio console systems supporting multi-agency communications
 • Logging recorders used for call review, compliance, and operational analysis
 • Network and traffic analysis tools, such as Wireshark, used to troubleshoot system performance and integrations

Successful candidates often have direct experience supporting, configuring, troubleshooting, or operating these systems within PSAPs, ECCs, or other mission-critical public safety environments.

Work Location

This is a fully remote role open to candidates based in the United States. Candidates located in the Mountain or Pacific regions are strongly encouraged to apply. Due to the nature of the position, up to 75% travel is required, including customer meetings, training sessions, and industry events.

Benefits that Benefit You

• Competitive salary and 401k with employer match
• Discretionary paid time off
• Paid parental leave for all
• Medical, dental, and Vision plans
• Fitness Programs
• Emotional & Mental Wellness support
• Learning & Development programs
• And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work.

Pay Transparency

Axon offers a comprehensive total compensation package, which includes base salary, a generous annual bonus, and company equity.

The starting base salary for this role ranges from $110,000 to $160,000 annually, excluding commission and bonuses, and varies based on geographic market. Actual base pay will depend on several factors, including level, function, training, transferable skills, work experience, business needs, and location.

Our benefits are designed to support you physically, financially, and emotionally—through life’s major milestones and in your everyday moments. To learn more about our benefits, please visit www.axon.com/careers/benefits.

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 Autonomous Vehicle (AV) Test Engineering team at Motional is responsible for validating the safety, functionality, and performance of our self-driving technology and commercial operations platform through rigorous, system-level testing. Motional is seeking a highly skilled and motivated Senior Automation Test Engineer to join our AV Test Engineering team. In this role, you will lead the design, development, and execution of backend and frontend automation frameworks for our fleet operations platform — the operational backbone of our commercial robotaxi service. You will also lead and mentor a fellow automation engineer, driving best practices and continuous improvement across the team.

What you'll work on:

• Own the architecture, development, and maintenance of scalable backend and frontend test automation frameworks for a fleet operations platform, with a primary focus on backend API and service-level validation.
• Design and execute comprehensive automated test suites covering backend services, APIs, and data pipelines, as well as frontend UI workflows within the operations platform.
• Lead integration testing efforts for third-party APIs and internal services, ensuring reliable end-to-end data flow across fleet management, dispatching, and monitoring systems.
• Develop automation solutions primarily in Python and Go for backend testing, and JavaScript for frontend validation, while proactively adopting new tools and frameworks as the platform evolves.
• Lead, mentor, and collaborate with one automation test engineer, providing technical guidance, code reviews, and support for professional development.
• Partner closely with software engineers and product teams to define test strategies, identify coverage gaps, and establish quality gates within CI/CD pipelines.
• Conduct root-cause analysis on test failures and system defects, driving resolution across backend services and frontend interfaces.
• Contribute to documentation, test plans, and operational frameworks that bring clarity and transparency to the automation testing process for all stakeholders.
  
  

What we're looking for:

• 5+ years in software QA or test automation, with a strong emphasis on backend and API testing.
• Bachelor's degree or higher in Engineering, Computer Science, or a related technical field.
• Technical Expertise:
• Hands-on proficiency in Python and Go for backend test automation, and JavaScript for frontend automation.
• Demonstrated experience designing and building automation frameworks from the ground up for complex, distributed systems.
• Experience with REST/gRPC API testing, service integration validation, and data pipeline verification.
• Experience with CI/CD pipelines and integrating automated quality gates for production-grade software releases.
• Proven ability to lead technical efforts, operate autonomously, and drive cross-functional collaboration.
• Ability and willingness to quickly learn new tools, frameworks, and technologies as the platform and stack evolve.
  
  

Bonus points:

• Experience with autonomous vehicle fleet monitoring, dispatching, or fleet management systems.
• Experience with Uber API or similar ride-hail/transportation platform integration testing.
• Familiarity with cloud telemetry systems or AV data pipelines.
• Experience in a cross-site or global engineering organization.
• Master's degree in a relevant field.

 This role is based in our Las Vegas office and requires in-office 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:

We are seeking an experienced and visionary Principle Level Tech Lead Manager to build and lead our new Machine Learning (ML) Acceleration team. This pivotal role will drive the strategy, development, and execution of initiatives aimed at significantly accelerating ML model training. The ultimate goal is to drastically reduce the development cycle for new ML models and enable rapid hot-patching for issues within our deployed autonomous vehicle services.

You will be a hands-on leader, blending deep technical expertise in ML systems and performance optimization with strong leadership and people management skills. You will recruit, mentor, and grow a high-performing team of engineers, fostering a culture of innovation, collaboration, and continuous improvement.

What you'll be doing:

• Team Leadership & Management:
• Build, lead, and manage a high-performing team of ML and infra engineers focused on acceleration.
• Provide technical guidance, mentorship, and career development opportunities to team members.
• Foster a collaborative and inclusive team environment.
• Define team goals, priorities, and roadmap in alignment with company objectives.
  
  
• Technical Strategy & Execution:
• Define the technical vision and strategy for ML acceleration across the organization.
• Identify and evaluate cutting-edge technologies and methodologies for speeding up ML training, including but not limited to data pipeline optimization, large scale distributed training, data loader optimization, hardware acceleration, and model optimization techniques.
• Design, develop, and implement scalable and efficient ML acceleration solutions.
  
  
• Cross-functional Collaboration:
• Collaborate closely with ML research, ML Training platform, and product teams to understand their needs and integrate acceleration solutions seamlessly.
• Communicate complex technical concepts and strategies to both technical and non-technical stakeholders.
• Act as a technical expert and advocate for ML acceleration initiatives across the company.
  
  
• Impact & Measurement:
• Regularly measure and report on the impact of acceleration efforts.
• Continuously seek opportunities for further optimization and innovation.
  
  

What we're looking for:

• Experience:
• Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience
• 8+ years of experience in software engineering, with at least 5+ years focused on Machine Learning systems and model performance optimization.
• 3+ years of experience in a technical lead or management role, with a proven track record of building and leading high-performing teams.
• Extensive experience with large-scale ML model training and deployment, ideally in a production environment.
• Strong understanding of distributed systems and cloud computing platforms (e.g., AWS, GCP, Azure).
  
  
• Technical Skills:
• Deep expertise in ML frameworks such as PyTorch or JAX.
• Proficiency in performance profiling and optimization techniques for Deep Neural Networks.
• Strong programming skills in Python; C++ experience is a plus.
• Knowledge of MLOps principles and practices.
  
  
• Leadership Skills:
• Exceptional leadership, communication, and interpersonal skills.
• Ability to attract, hire, and retain top engineering talent.
• Proven ability to drive complex technical projects from conception to completion.
• Strong problem-solving skills and a proactive, results-oriented mindset.
• Ability to thrive in a fast-paced, dynamic environment.

Mission Summary:

We are seeking an experienced and visionary Principle Level Tech Lead Manager to build and lead our new Machine Learning (ML) Acceleration team. This pivotal role will drive the strategy, development, and execution of initiatives aimed at significantly accelerating ML model training. The ultimate goal is to drastically reduce the development cycle for new ML models and enable rapid hot-patching for issues within our deployed autonomous vehicle services.

You will be a hands-on leader, blending deep technical expertise in ML systems and performance optimization with strong leadership and people management skills. You will recruit, mentor, and grow a high-performing team of engineers, fostering a culture of innovation, collaboration, and continuous improvement.

What you'll be doing:

• Team Leadership & Management:
• Build, lead, and manage a high-performing team of ML and infra engineers focused on acceleration.
• Provide technical guidance, mentorship, and career development opportunities to team members.
• Foster a collaborative and inclusive team environment.
• Define team goals, priorities, and roadmap in alignment with company objectives.
  
  
• Technical Strategy & Execution:
• Define the technical vision and strategy for ML acceleration across the organization.
• Identify and evaluate cutting-edge technologies and methodologies for speeding up ML training, including but not limited to data pipeline optimization, large scale distributed training, data loader optimization, hardware acceleration, and model optimization techniques.
• Design, develop, and implement scalable and efficient ML acceleration solutions.
  
  
• Cross-functional Collaboration:
• Collaborate closely with ML research, ML Training platform, and product teams to understand their needs and integrate acceleration solutions seamlessly.
• Communicate complex technical concepts and strategies to both technical and non-technical stakeholders.
• Act as a technical expert and advocate for ML acceleration initiatives across the company.
  
  
• Impact & Measurement:
• Regularly measure and report on the impact of acceleration efforts.
• Continuously seek opportunities for further optimization and innovation.
  
  

What we're looking for:

• Experience:
• Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience
• 8+ years of experience in software engineering, with at least 5+ years focused on Machine Learning systems, and model performance optimization.
• 3+ years of experience in a technical lead or management role, with a proven track record of building and leading high-performing teams.
• Extensive experience with large-scale ML model training and deployment, ideally in a production environment.
• Strong understanding of distributed systems and cloud computing platforms (e.g., AWS, GCP, Azure).
  
  
• Technical Skills:
• Deep expertise in ML frameworks such as PyTorch or JAX.
• Proficiency in performance profiling and optimization techniques for Deep Neural Networks.
• Strong programming skills in Python; C++ experience is a plus.
• Knowledge of MLOps principles and practices.
  
  
• Leadership Skills:
• Exceptional leadership, communication, and interpersonal skills.
• Ability to attract, hire, and retain top engineering talent.
• Proven ability to drive complex technical projects from conception to completion.
• Strong problem-solving skills and a proactive, results-oriented mindset.
• Ability to thrive in a fast-paced, dynamic environment.

Mission Summary:

We are seeking an experienced and visionary Principle Level Tech Lead Manager to build and lead our new Machine Learning (ML) Acceleration team. This pivotal role will drive the strategy, development, and execution of initiatives aimed at significantly accelerating ML model training. The ultimate goal is to drastically reduce the development cycle for new ML models and enable rapid hot-patching for issues within our deployed autonomous vehicle services.

You will be a hands-on leader, blending deep technical expertise in ML systems and performance optimization with strong leadership and people management skills. You will recruit, mentor, and grow a high-performing team of engineers, fostering a culture of innovation, collaboration, and continuous improvement.

What you'll be doing:

• Team Leadership & Management:
• Build, lead, and manage a high-performing team of ML and infra engineers focused on acceleration.
• Provide technical guidance, mentorship, and career development opportunities to team members.
• Foster a collaborative and inclusive team environment.
• Define team goals, priorities, and roadmap in alignment with company objectives.
  
  
• Technical Strategy & Execution:
• Define the technical vision and strategy for ML acceleration across the organization.
• Identify and evaluate cutting-edge technologies and methodologies for speeding up ML training, including but not limited to data pipeline optimization, large scale distributed training, data loader optimization, hardware acceleration, and model optimization techniques.
• Design, develop, and implement scalable and efficient ML acceleration solutions.
  
  
• Cross-functional Collaboration:
• Collaborate closely with ML research, ML Training platform, and product teams to understand their needs and integrate acceleration solutions seamlessly.
• Communicate complex technical concepts and strategies to both technical and non-technical stakeholders.
• Act as a technical expert and advocate for ML acceleration initiatives across the company.
  
  
• Impact & Measurement:
• Regularly measure and report on the impact of acceleration efforts.
• Continuously seek opportunities for further optimization and innovation.
  
  

What we're looking for:

• Experience:
• Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience
• 8+ years of experience in software engineering, with at least 5+ years focused on Machine Learning systems and model performance optimization.
• 3+ years of experience in a technical lead or management role, with a proven track record of building and leading high-performing teams.
• Extensive experience with large-scale ML model training and deployment, ideally in a production environment.
• Strong understanding of distributed systems and cloud computing platforms (e.g., AWS, GCP, Azure).
  
  
• Technical Skills:
• Deep expertise in ML frameworks such as PyTorch or JAX.
• Proficiency in performance profiling and optimization techniques for Deep Neural Networks.
• Strong programming skills in Python; C++ experience is a plus.
• Knowledge of MLOps principles and practices.
  
  
• Leadership Skills:
• Exceptional leadership, communication, and interpersonal skills.
• Ability to attract, hire, and retain top engineering talent.
• Proven ability to drive complex technical projects from conception to completion.
• Strong problem-solving skills and a proactive, results-oriented mindset.
• Ability to thrive in a fast-paced, dynamic environment.

Mission Summary:

As a Principal Engineer within the Platform Engineering group, you will serve as the primary architect for Motional’s global cloud and hybrid infrastructure. Your mission is to evolve our current R&D environment into a hardened, cost-efficient, and scalable commercial backbone. You will lead the technical strategy for our hybrid cloud migration and ensure our internal frameworks provide  the velocity required for rapid AV deployment.

What you’ll be doing:

• Architect and drive the execution of our hybrid cloud strategy. You will design the networking, security, and compute abstraction layers that allow seamless workload mobility between on-premises high-performance computing (HPC) and AWS.
• Serve as the primary architect for our Kubernetes-based developer framework. You will identify and implement core improvements to the framework to enhance scalability, cost tracking and access control, reduce configuration complexity, and increase developer velocity.
• Lead organization-wide initiatives to harden service reliability. You will define the standards for observability, failover strategies, and production-grade stability across all platform-layer services.
• Prototype and deploy GenAI-focused tooling and agents to automate Platform Engineering tasks. This includes leveraging LLMs for automated incident response, predictive infrastructure scaling, and intelligent log analysis.
• Act as the final technical authority for infrastructure decisions, ensuring all new platform services align with long-term scalability and security goals.

What we’re looking for:

• Bachelor's or Master's in Computer Science, Engineering, or a related field (or equivalent practical experience)
• 12+ years in Software or Infrastructure Engineering, with significant experience in a Principal or Architect capacity
• Deep, expert-level knowledge of Kubernetes internals and ecosystem (EKS, Operators (KubeRay, ArgoWorkflow, Airflow), Service Mesh, GitOps)
• Proven track record of designing and migrating complex workloads between on-prem data centers and AWS
• Experience with Infrastructure-as-Code (Terraform/CloudFormation, Terraform Cloud/Spacelift/Atlantis) and advanced observability tooling (OpenTelemetry, Prometheus, Grafana, Datadog)
• Expert in architecting AI-driven operations, leveraging LLMs and agentic workflows to automate incident response, predictive scaling, and intelligent system observability
• Demonstrated ability to influence technical roadmaps across an entire engineering organization and mentor senior technical staff.

Bonus Points (not required):

• Expert-level experience managing and architecting solutions using Equinix datacenter products and services (e.g., Equinix Fabric, Network Edge, Metal) to enable high-speed hybrid cloud connectivity (AWS Direct Connect)
• Prior experience in the Autonomous Vehicle, Robotics, or large-scale IoT/Fleet Management industries.
• Experience leading technical projects in a globally distributed team
• Proven expertise in CI/CD orchestration, build systems (Bazel), frameworks

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:

The Autonomous Vehicle (AV) Test Engineering team at Motional is responsible for validating the safety, functionality, and performance of our self-driving technology through rigorous, system-level testing. As an AV Test Engineer, you will take a lead role in the strategy, planning, and execution of comprehensive test campaigns that span perception, planning, and control systems across virtual, closed-course, and public road environments.

Motional is seeking a highly skilled and motivated Senior/Mid-Level AV Test Engineer to join our AV Test Engineering team. You will play a lead role in validating the safety, functionality, and performance of our self-driving technology through rigorous, system-level testing across virtual, closed-course, and public road environments, with a direct focus on commercial readiness of our robotaxi service.

This role requires a proven technical leader who can guide test development, drive continuous improvements to our infrastructure, and ensure high standards for release readiness and safety assurance as we move towards mass deployment.

What you'll work on:

• Own the planning, design, and execution of comprehensive validation campaigns across Perception, Planning, and Control systems using simulation, SIL, HIL, and on-vehicle environments, specifically targeting scenarios critical for robotaxi service reliability and rider experience.
• Drive test execution and documentation to meet the highest standards, ensuring system compliance with safety-critical standards (ISO26262, ISO21448 (SOTIF)), with an emphasis on Operational Design Domain (ODD) limits and safe fallback behavior.
• Develop, maintain, and enhance robust, scalable test infrastructure and automation frameworks using Python, Shell, and relevant platforms to support high-volume, fleet-wide software rollouts.
• Serve as a technical lead for scenario-based testing (using tools like Applied Intuition) and AV capability campaigns, focusing on testing for end-to-end mission performance and service uptime.
• Service Readiness Validation:
  • Design and execute testing for non-driving features critical to the commercial service, including rider interactions, remote assistance handoffs, fleet operations protocols, and over-the-air (OTA) update verification.
  • Define and track Service Quality Indicators (SQI) and KPIs related to rider experience and operational efficiency during validation.
• Conduct detailed log analysis, support root-cause investigations across AV software and hardware, and utilize CAN-based tools for subsystem verification, particularly diagnosing issues impacting fleet efficiency and customer satisfaction.
• Lead QA review cycles, define release readiness gates for commercial software, represent Test Engineering in cross-functional forums, and mentor junior engineers.

What we're looking for:

• 5+ years in software QA or system testing, specifically within AV, ADAS, robotics, or safety-critical systems.
• Bachelor’s degree or higher in Engineering, Robotics, ECE, Computer Science, or a related technical field.
• Technical Expertise:
• Demonstrated expertise in test strategy, automation, and end-to-end testing for complex mechatronic/autonomous systems.
• Experience planning and executing tests in a simulated environment, both HIL and SIL
• Experience with CI/CD pipelines and integrating quality gates for production-grade software releases.
• Proven ability to lead technical efforts, mentor, operate with minimal oversight, and drive cross-functional alignment with teams like Fleet Operations and Product.

Bonus points:

• Master’s degree in a relevant field.
• Deep familiarity with CAN-based tools (CANalyzer/CANoe) and logging/debugging techniques.
• Working knowledge of industry safety standards (ISO26262, SOTIF).
• Familiarity with AV safety case development or safety validation workflows.
• Experience with robotaxi service features (e.g., in-cabin HMI testing, rider support systems).
• Experience with ROS, cloud telemetry systems, or AV data pipelines.
• Experience in a cross-site or global engineering organization.

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.

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.

While performing the duties of this job, the team member is regularly exposed to outside weather conditions, road conditions, and pedestrian traffic.  The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and airborne particles.  The noise level in the environment is low to moderate.

Mission Summary:

The Autonomous Vehicle (AV) Test Engineering team at Motional is responsible for validating the safety, functionality, and performance of our self-driving technology through rigorous, system-level testing. As a Senior AV Test Engineer, you will take a lead role in the strategy, planning, and execution of comprehensive test campaigns that span perception, planning, and control systems across virtual, closed-course, and public road environments.

In this role, you will guide test development efforts across multiple AV subsystems, mentor junior engineers, and drive improvements to our tooling, test infrastructure, and methodologies. You will lead cross-functional initiatives that directly impact release readiness and safety assurance, translating high-level engineering requirements into scalable test plans and measurable quality outcomes. Your work will contribute to iterative development, fault injection analysis, and validation of safety-critical systems that meet the highest standards for reliability and compliance.

Essential Duties:

Technical Leadership & Validation:

• Lead the planning, design, and execution of validation campaigns across simulation, SIL, HIL, and on-vehicle environments, with a focus on perception, planning, and control systems.
• Serve as the technical lead for scenario-based testing, utilizing platforms like Applied Intuition or equivalents for synthetic and re-simulation use cases.
• Lead AV capability campaigns, employing AB Dynamics equipment for system-level validation and performance benchmarking.
• Own the creation and execution of test plans for complex mechatronic and software systems, including drive-by-wire (DBW), braking, steering, and system integrations.

Test Infrastructure & Analysis:

• Develop and maintain robust test infrastructure using Python, Shell, and automation frameworks, ensuring modular, reusable, and scalable test architecture.
• Conduct detailed analysis of logs and system behavior, supporting root-cause investigations across AV software and hardware components.
  
  

Quality Assurance & Compliance:

• Participate in and lead QA review cycles, helping to define entry/exit criteria, regression coverage, and release readiness gates.
• Ensure traceability and compliance by documenting procedures, results, and outcomes using Jira, GitLab, and Confluence.
• Contribute to compliance with safety-critical standards such as ISO26262, ISO21448 (SOTIF), and ISO9001.
  
  

Collaboration & Mentorship:

• Represent the Test Engineering function in cross-functional planning meetings, collaborating closely with perception, planning, controls, and safety teams.
• Mentor and support junior Test Engineers, providing technical guidance and fostering a culture of continuous learning and improvement.
  
  

Strategic Adaptation & Support:

• Continuously adapt and optimize test strategies in response to evolving product requirements, architectural shifts, and real-world findings.
• Support after-hours testing or incident triage as needed by fleet or field operations.
• Travel domestically on occasion to support on-site testing or operational deployments.
• Perform additional duties as assigned.

Required Qualifications:

• Bachelor's degree or higher in Engineering, Robotics, ECE, Computer Science, or a related technical field.
• 5+ years of experience in software QA or system testing, including AV, ADAS, robotics, or safety-critical systems.
• Demonstrated expertise in test strategy, test case development, test execution, and automation for complex mechatronic or autonomous systems.
• Experience leading end-to-end testing across software stacks and physical systems, including SIL, HIL, and real-world deployments.
• Strong analytical skills with proficiency in debugging, log parsing, and root cause analysis.
• Excellent verbal and written communication skills, with the ability to drive cross-functional alignment and effectively report technical findings.
• Proven ability to lead technical efforts, mentor junior engineers, and operate with minimal oversight.
• High level of initiative, ownership, and accountability in a fast-paced, startup-style engineering environment.
• Flexible schedule and willingness to support late meetings, night shifts, or urgent test activities as required.

Preferred:

• Master’s degree in a relevant field.
• Deep familiarity with CAN-based tools (CANalyzer, CANoe) for fault injection, bus analysis, and subsystem verification.
• Working knowledge of industry standards for safety-critical systems such as ISO26262, ISO21448 (SOTIF), and ISO9001.
• Familiarity with AV safety case development or safety validation workflows.
• Experience with robotic middleware (e.g., ROS), cloud telemetry systems, or AV data pipelines.
• Experience in a cross-site or global engineering organization.
  
  

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.

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.

While performing the duties of this job, the team member is regularly exposed to outside weather conditions, road conditions, and pedestrian traffic.  The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and airborne particles.  The 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 regarding race, sex, color, national origin, age, disability, veteran status, genetic data, religion, gender identity, sexual orientation, or another 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.

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

The AI Data Foundry is the vital link between our company's expansive data and the engineering teams that rely on it. We architect and operate the core services and infrastructure necessary to transform petabytes of raw data each month into actionable insights for our Machine Learning and Autonomy engineers. This role is a key contributor across our core initiatives:

• Data Processing: We are building state-of-the-art infrastructure to meet the demands of our rapidly scaling fleet and sophisticated ML engineering requirements. You will be responsible for ensuring that our core data pipelines are robustly engineered—meaning they are performant, user-friendly, and highly fault-tolerant.
• Data Discovery: we are building a platform that combines cataloging data for search needs across our metadata stores, vector datastores, and various data warehouses to super charge our ML pipelines. You would be coming in and working with ML and autonomy stakeholders to build out this new discovery platform. 
• Data Lineage: we are getting started with building our data lineage system that will track the usage of all data at Motional. You would work with our stakeholders to ensure our system is widely adopted and address customer pain points.

What You'll Be Doing

• Play a key role in designing and building the next generation of data infrastructure.
• Build scalable backend services for data discovery and data lineage systems.
• Write high quality, maintainable code to process petabytes of data 
• Lead and champion high-level system design and quality code reviews/technical contributions.
• Design, build, and maintain scalable data processing and access with cloud ETL technology.

What We're Looking For

• 3+ years of professional experience as a data engineer or data pipeline engineer
• BS or MS in Computer Science or related field
• Strong development experience with Python and SQL.
• Expertise with AWS services and solutions (EKS, Lambda, ETL) 
• Experience with distributed system design and development
• Comfortable working in a fast-paced, continuous delivery environment

Bonus Points (not required): 

• Experience with Infrastructure Monitoring
• Experience working in cross-functional development teams 

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.

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

Mission Summary:

Join us on the ground floor as we launch our commercial Autonomous Vehicle (AV) ride service. We are looking for a mission-driven Senior Software Engineer to join our Command Center team. You will be the vital link between our real-world AV operations and our core development team, ensuring our vehicles run smoothly and our technology rapidly evolves.

What will you be doing:

AV operations integration & support

• Act as the primary engineering presence at the Las Vegas AV operation center, providing real-time technical support and troubleshooting to ensure daily mission success.
• Resolve production incidents to reduce downtime and strengthen feedback loops between on-road operations and global engineering teams.
• Become the go-to technical expert, surfacing operational insights that influence our product roadmap and support commercial launch readiness.

Command Center feature development

• Design and develop software tools that enhance AV fleet operations, including cloud platform, over-the-air deployment, and fleet management systems.
• Build and maintain foundational technologies including ride-hail partner integration and the global scaling of the autonomous vehicle service.
• Collaborate cross-functionally to deliver scalable, efficient solutions aligned with both engineering and operational requirements.

What we're looking for:

• 5+ years of professional experience as a software engineer, with a proven track record of designing and building distributed systems.
• Strong Product Mindset: You focus on real-world impact. You can identify bottlenecks within a busy operational workflow and design software solutions that bring order and efficiency.
• Experience supporting production systems with a customer-centric mindset and strong communication skills.
• Experience working independently and collaborating effectively with a globally distributed team across different time zones.
• Proficiency in Golang / Python for web service and scripting.
• Experience building cloud services using SQL and NoSQL databases.
• Comfortable working in a fast-paced, continuous delivery environment.
• A Bachelor's or Master's in Computer Science, Engineering, or a related field (or equivalent practical experience).

Bonus Points (not required):

• Experience with Amazon Web Services (AWS), Docker, and Terraform.
• Experience with OLAP databases (e.g., ClickHouse) or building observability tools for monitoring and tracing.
• Previous experience in the Autonomous Vehicle (AV), Robotics, or IoT industries.

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.

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

Mission Summary:

Join us as a key technical leader in Las Vegas as we launch our commercial Autonomous Vehicle (AV) ride service. We are seeking a Staff Software Engineer with a strong product mindset to bridge the gap between our Operations partners and our global Engineering team. You will lead the development of critical operational tools—like fleet management and orchestration systems—while shaping the roadmap to ensure our technology meets real-world needs.

What You'll Be Doing:

Hands-on Development & Leadership

• Build High-Impact Ops Tools: Lead the coding and delivery of frontend and backend services that the Operations team uses daily to monitor and manage the fleet. You will balance long-term scalability with the need for immediate operational solutions.
• Act as the primary engineering presence at the Las Vegas AV operation center, providing real-time technical support and troubleshooting to ensure daily mission success.
• You will interview and onboard future hires, mentor junior engineers, and define the workflows (handovers, async communication, documentation standards) that enable seamless collaboration between Las Vegas and Singapore.

Product Engineering & Stakeholder Alignment

• Own the "Ops-to-Tech" Bridge: Partner deep with Operations, Product, and TPMs to translate complex, real-world fleet challenges into clear, actionable technical requirements for the global engineering team.
• Shape the Tooling Roadmap: Drive the vision for our fleet management and orchestration systems. You won't just build tickets; you will identify the right problems to solve to increase fleet efficiency and reduce manual toil.
• Feedback Loop Architect: Design processes and features that turn qualitative operational feedback into quantitative data, helping the global team prioritize platform improvements.

What We're Looking For:

• 8+ years of professional experience as a software engineer, with a proven track record of designing and building distributed systems.
• Strong "Product" Mindset: You are obsessed with value. You can look at a chaotic operational floor and architect a software solution that brings order and efficiency.
• Experience supporting production systems with a customer-centric mindset and strong communication skills.
• Ability to manage stakeholders (Ops, Product) and communicate effectively with a remote engineering team to get things done without owning the entire stack.
• Proficiency in Golang / Python for web service and scripting.
• Experience building cloud services using SQL and NoSQL databases.
• A Bachelor's or Master's in Computer Science, Engineering, or a related field (or equivalent practical experience).

Bonus Points (not required): 

• Experience with Amazon Web Services (AWS), Docker, and Terraform.
• Experience with OLAP databases (e.g., ClickHouse) or building observability tools for monitoring and tracing.
• Previous experience in the Autonomous Vehicle (AV), Robotics, or IoT industries.

About the Role:

The Senior Engineer will provide expertise and consulting services for IT infrastructure projects. This position will provide deep technical expertise in networking and systems administration, as well as the ability to influence and guide both internal teams and client stakeholders through complex system upgrades and architectural changes.

*** This is a 100% Onsite requirement with heavy travel***

What You’ll Do:

• Serve as lead for on-site and remote technical management at customer locations.
• Provide mentorship to the on-site professional services engineering team.
• Deliver expert on-site support for networking and systems administration in alignment with the client’s IT upgrade initiatives and system conversions.
• Provide strategic consultation and expert technical guidance in IT infrastructure planning, engineering, and architecture.
• Evaluate and advise on the impact of IT strategies on infrastructure capabilities.
• Assess and advise on the impact of IT strategies, offering recommendations on system design, including analysis of risks, costs, and benefits.
• Collaborate with internal stakeholders and third-party vendors to troubleshoot and resolve complex system issues.
• Lead and support the technical implementation of infrastructure solutions to meet client IT enhancement goals.
• Lead technology engineering efforts by providing direction and insight to improve efficiency, ensure quality, and support the successful delivery of services and customer deployments.
• Serve as a subject matter expert and trusted advisor to influence project outcomes and drive team performance.

REQUIRED SKILLS AND EXPERIENCE:

• Bachelor’s degree from an accredited university required or equivalent years of experience.
• A minimum of 6 years of experience in hands-on experience in IT infrastructure, networking, and systems administration.
• Strong understanding of networking technologies, system architecture, and cloud infrastructure.
• Strong understanding of low-voltage cabling and data center configuration best practices.
• Excellent problem-solving skills and the ability to manage multiple technical projects simultaneously.
• Outstanding communication and collaboration abilities with a strong client-service orientation.
• Ability to travel domestically up to 85% - 90% of the time

PHYSICAL DEMANDS:

 This role blends active movement with desk-based responsibilities. Candidates should be comfortable with:

• Standing and walking for long stretches across different areas of the facility.
• Lifting items—sometimes heavy, up to 65 to 200 pounds—including navigating stairs and placing objects overhead.
• Occasionally working from ladders when tasks require elevation.
• Performing physical motions such as bending, crouching, and reaching on a regular basis.
• Sitting for extended periods while handling administrative or computer-related tasks.
• Reading printed documents and screens with clarity, including close-up work and adjusting focus as needed.
• Communicating effectively in person and by phone, with clear hearing and speech.

WORK ENVIRONMENT:

• The job takes place in environments where animals are present, which may involve exposure to pet dander, medical tools, and related substances.
• Travel by car and air (up to 75%) is required.
• A valid Driver's License is required. 
• Employees will often be surrounded by coworkers and clients, with frequent conversations happening nearby.
• Noise levels and indoor temperatures may fluctuate depending on the setting.

Why this role is exciting

As (Senior) Fleet Support Engineer, you will be instrumental in maintaining, managing and optimizing our platform and network infrastructure for Vay’s commercial driverless fleet in Las Vegas. This role requires a unique combination of superb debugging skills, technical expertise, network configuration and troubleshooting. You'll be driving continuous improvement in our system, ensuring robust monitoring and alerts and providing L1 support for our commercial, driverless fleet. Your role is pivotal in maintaining the efficiency and reliability of our vehicle and remote driving station fleet which leads to high quality service that our users love.

What you’ll be driving

• L1 support and on-call for incidents and customer support requests involving vehicles, remote driving stations, equipment, network and cloud infrastructure and fleet configuration.
• Vehicle and remote driving station network infrastructure maintenance
• Supporting bring-up of new vehicle and remote driving stations

What are we looking for

• Extensive Linux experience
• Strong debugging skills for large, complex systems
• Experience in Python and bash scripting
• Experience with on-premise network maintenance and troubleshooting
• Experience with CI/CD tools (namely GitHub, CircleCI, Jenkins)
• Understanding and experience in Docker

Nice to have

• Experience in C and/or C++
• Understanding of CAN protocol 
• Familiar with network security concepts
• Familiar with mobile network and telecommunication technologies (4G/5G)

Why choose Vay

💪A global team of smart, motivated people from 30+ countries who love tackling hard problems and turning bold ideas into reality.

🌍 Huge scope for impact in a fast paced environment

💰 ESOP stock options: A stake in Vay’s future - not just a salary.

🌴 Unlimited Paid Vacation Days

🎫 401(k) programme

🏥 Health, Dental & Vision Insurance 

🚗 All Vay team members receive 30% off their Vay rides

🏋️‍♂️ Wellness Hub free gym access & wellness app subscriptions

🛍️ Exclusive external discounts

✈️ Relocation financial assistance when relocating to Las Vegas 

🎊 Regular team events throughout the year