MongoDB’s Storage Layer Services (SLS) team is re-architecting the MongoDB cloud storage layer and sits at the heart of our next-generation cloud storage architecture. This relatively new team is building performant, multi-tenant distributed storage services that both enhance today’s Atlas storage stack and enable more customer workloads to run more efficiently.

You will partner with the teams building these storage services to define SLOs, shape capacity plans, and ensure the reliability, durability, and operational safety of the storage layer that underpins Atlas. You’ll join a small, senior team of SREs as founding members of this organization, playing a crucial role in executing on a multi-year roadmap for MongoDB’s cloud storage architecture.

This role can be based out of our Boston, New York City, Raleigh, Miami, Pittsburgh or remotely in the United States while physically based in an Eastern or Central time zone location. 

The ideal candidate should

• Have 6+ years of experience working on software development and operating distributed systems
• Proficiency in Python, Go, or a similar language
• Have operated or supported stateful storage or database systems at scale, and are comfortable with durability, consistency, and recovery trade-offs.
• Possess a customer-focused mindset
• Value efficiency in processes and operations
• Prefer automation over manual processes. We are a small team of software engineers with a strong bias towards software solutions to avoid toil
• Experience using and extending containerization technologies, particularly Kubernetes, to enhance application agility, optimize resource utilization, and accelerate time-to-market
• Expertise in cloud infrastructure platforms, including AWS, Google Cloud Platform (GCP), or Azure
• Understanding of Linux operating system internals and networking concepts (e.g., TCP/IP, DNS, TLS, routing)

Responsibilities 

• Work on our multi-tenant distributed storage systems, balancing long-term strategic infrastructure goals with immediate engineering needs
• Build for reliability, making services and infrastructure available, resilient, fault-tolerant, and self-healing
• Identify and configure key metrics to detect incidents and quantify service health, availability, and performance
• Participate in a 24/7 on-call rotation to resolve issues involving the storage infrastructure
• Become an expert in infrastructure performance, helping us optimize from the application level all the way to the kernel

Strong candidates may also have experience with:

• Leading major architectural shifts, such as moving from legacy storage stacks to new multi-tenant storage architectures, including planning and executing large-scale data and workload migrations with tight availability and durability requirements
• Managing and scaling infrastructure across multi-cloud environments (AWS, GCP, or Azure)
• Designing secure, multi-tenant runtime environments at scale

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform, the most widely available, globally distributed database on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and over 60,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Req ID: 1273396252

Description:

The Assurance, Risk, and Compliance (“ARC”) Initiatives team at MongoDB owns the strategy, governance, and delivery of our most critical cross-functional risk and compliance initiatives. We design and execute programs that support compliance audits, risk assessments, employee awareness and enablement, and the implementation of common control frameworks, along with consistent operating cadences that align key stakeholders, accelerate decision making, and drive the execution of initiatives that reinforce MongoDB’s assurance, risk management, and compliance objectives. We define and track key metrics and deliver clear and timely, executive reporting to provide transparency, measure progress, and ensure lasting operational resilience and governance.

We serve as the central coordination point for ARC-wide initiatives, connecting Product, Engineering, Security, and Legal teams around clear priorities, milestones, and outcomes. Our focus is on building scalable governance structures, defining decision-making frameworks, and establishing repeatable ways of working so that complex efforts can be executed consistently across the team.

The Policy Program Manager is a mid-to-senior level individual contributor role responsible for leading the development and operationalization of policies and procedures aligned to established control frameworks. You will drive end-to-end ownership of policy lifecycle management, from drafting and review through implementation and ongoing maintenance, while coordinating inputs across teams to ensure accuracy, consistency, and adoption. Additionally, you will lead documentation standardization efforts, facilitate stakeholder reviews, and perform gap analyses to continuously strengthen and mature our ARC policy framework.

Responsibilities:

• Lead the end-to-end execution of company-wide compliance programs, including the annual security policy and procedure review cycle
• Design and implement scalable frameworks for policy lifecycle management (creation, review, approval, publication, and retirement)
• Establish standards, templates, and governance processes to ensure consistency and clarity across all compliance documentation
• Maintain a centralized, audit-ready repository for policies, procedures, and supporting artifacts
• Act as the primary point of contact for cross-functional teams (HR, Legal, Engineering, Product)
• Drive alignment, gather inputs, and ensure timely completion of policy updates and compliance deliverables
• Ensure policies and procedures align with regulatory, security, and internal control requirements
• Support internal and external audits by maintaining complete, accurate, and accessible documentation
• Translate audit findings and regulatory changes into actionable policy program updates
• Maintain the integrity of project-specific Jira boards and Confluence pages. Ensure all project artifacts are organized, up-to-date, and ready for leadership review or external audit
• Develop and maintain dashboards to report on program health, completion rates, and obstacles. Present status updates and metrics to leadership
• Evaluate existing program workflows and implement improvements to increase efficiency, reduce manual effort, and improve the stakeholder experience

Requirements:

• 5-8 years of program management experience, ideally within an Information Security or high-growth technology environment
• Experience creating and managing policy and procedure programs or governance frameworks
• Deep understanding of security and compliance frameworks (e.g., SOC 2, ISO 27001, PCI DSS, HIPAA, NIST CSF)
• Strong proficiency in managing full-lifecycle projects, including scoping, planning, risk mitigation, and change control
• Advanced experience with Jira and Confluence, including the ability to build custom dashboards and manage complex documentation repositories
• Maintain and support a GRC/policy management platform to ensure consistent policy administration and system usability
• Excellent interpersonal skills with the ability to hold cross-functional stakeholders accountable to deadlines in a professional and effective manner
• Exceptional attention to detail and the ability to manage multiple overlapping priorities without losing sight of milestones
• A proactive, self-directed approach to work. You enjoy taking ownership of a program and building the structure necessary for its success

Responsibilities & Expectations

• You are expected to be the owner of your assigned programs. While you will work closely with technical SMEs, you are responsible for the logistical success of the workstream. Your success is measured by the timely completion of program goals, the clarity of your reporting, and your ability to anticipate and resolve project bottlenecks
• You don't just track tasks; you own the success of the program

Scope & Complexity

• The scope is horizontal and impacts multiple departments across MongoDB
• Managing complex programs that require coordination with various business units, ensuring that project delays in one area do not derail the overall compliance roadmap

Authority & Impact

• You have the authority to manage the timelines and execution steps of your assigned programs
• Your impact is reflected in the strength of policy program management and organizational readiness you drive; by overseeing and coordinating these workstreams, you ensure the Compliance team consistently meets foundational policy requirements and aligns with external audit expectations

Expertise

• You will develop deep expertise in compliance and audit operations
• You will become the go-to resource for designing, scaling, and executing policy and compliance programs within a cloud-first organization. This role is responsible for independently and collaboratively developing and managing policies and procedures, with a strong understanding of compliance frameworks and the ability to interpret and operationalize control requirements

Leadership

• Leadership in this role is demonstrated through influence and mentorship. While you may not have direct reports, you will guide cross-functional teams in developing and standardizing policies/supporting documentation, as well as provide mentorship on policy governance, standardized documentation practices, and compliance alignment

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform, the most widely available, globally distributed database on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and over 60,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

REQ ID: 1273402887

The Team

This role can sit in our NYC HQ on a hybrid basis, or it can be fully remote while working from a location based in either Eastern or Central time zones. We are looking for an experienced Senior Engineer for our SRE, Atlas team to support, maintain and grow the Atlas platform. As a senior SRE, you will be expected to be able to design & build complex systems, operate with autonomy and act as owner for everything you do. 

The SRE Atlas team works alongside the various Atlas software engineering teams to provide expertise about running systems at scale, build new tooling and automation and perform essential maintenance of the Atlas fleet. 

This is an SRE team, which means you can expect a highly hands-on approach, tackling the technical challenges of implementing large scale solutions that have the ability to impact our customer’s most crucial workloads. 

Role Overview

We are seeking a talented Site Reliability Engineer (SRE) with a strong infrastructure background. This role requires engineers to have a customer-first mindset to ensure that everything we do results in a stronger product and a better experience for all Atlas customers. 

The ideal candidate should

• Have 5+ years of experience running critical systems at scale
• Value efficiency in processes and operations, and display a preference for automation over manual processes (“allergic to ops work”)
• Be familiar with a major cloud provider (AWS, Azure, or GCP) and possess the ability to build and operate systems in a multi-cloud environment
• A strong understanding of how to run a large scale Linux environment, including low level fundamentals 
• Firm grasp of at least one modern programming language, beyond basic scripting (Go, Ruby, Python)
• Solid understanding of web and network protocols and standards (HTTP, TLS, DNS, etc)

Special Requirements:

• Be a US Citizen

Expectations

• Participate in the development of a reliable and resilient multi-cloud platform that hosts business critical applications for a wide & varied range of customer applications
• Collaborate with service-owning teams to provide internal support, solve technical challenges and adapt or build tooling to solve novel use cases in a generic fashion
• Participate in a 24/7 on-call rotation to swiftly resolve issues related to any disruption of our customer facing Atlas fleet, ensuring minimal disruption and high availability

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Req ID: 426187

What we are looking for

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all.

We're searching for a Staff Client Platform Engineer to join our Enterprise Site Reliability (SRE) team to lead the management of our enterprise Windows, Mac, and Ubuntu clients. The team is responsible for designing, implementing, and maintaining scalable and secure client device infrastructure. They also automate device deployment, configuration, and management processes.

This role will contribute to delivering the benefits of self-driving by leading the development of tailored client device solutions that address Aurora-wide and team-specific requirements for software and hardware development and manufacturing.

In this role you will

• Guide the approach and execution of the Client Platform Engineering Team
• Plan, design, and implement scalable solutions to manage Aurora's physical and virtual client platforms (Macs, Windows, Ubuntu) to ensure they receive security patches, configuration, and software package updates
• Partner with IT Support, InfoSec, and Developer Experience on strategy and implementation of client platform management solutions
• Handle escalations from IT Support, with an emphasis on mentoring and empowering IT Support to address similar problems
• Participate in the Enterprise SRE 24/7 on-call rotation

Required qualifications

• Experience of at least 8 years in Client Platform engineering and at least 3 years in leading engineering solutions (design to implementation) at scale.
• Expertise with client device lifecycle management, including experience across multiple client operating systems and various hardware platforms.
• Experience with MacOS, Windows, and Linux system administration.
• Experience deploying configuration management tools such as Intune, Kandji, Puppet, Ansible, or Chef.
• Experience with automation and tool development, preferably using Powershell, Go, or Python.
• Strong change management skills, including rollout planning and communication, and collaborating with stakeholders.
• Understanding of client endpoint security concepts and experience applying security hardening to client devices, such as CIS Benchmarks.
• Outstanding written and verbal communication skills that drive executional impact at scale. 
• Experience with automating testing for imaging, provisioning, and configuration management.

Desirable qualifications

• Experience working within cloud environments such as AWS, GCP, or Azure.
• Experience in environments deploying containerized workflows, using tools such as Docker or Kubernetes.
• Familiarity with SRE concepts such as SLIs, SLOs, SLAs, incident response, and best practices and partnering with teams on them.
• Experience with Infrastructure as Code (IaC) tools such as Terraform, Pulumi, or CloudFormation

The base salary range for this position is  $163,000 - $236,500 per Year. Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

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

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

Our mission at Duolingo is to develop the best education in the world and make it universally available. It’s a big mission, and that’s where you come in!

At Duolingo, you’ll join a team that cares about finding innovative solutions to complex technical problems, running countless experiments (300+ at a time!) with our massive user base to make data-driven decisions, and educating our users and employees alike. You’ll have limitless learning opportunities, mentorship and collaboration with world-class minds, and a variety of projects with large scopes — while doing work that’s both fun and meaningful. 

Join our life-changing mission to develop education for our half a billion (and growing!) learners around the world.

About the role...

As a Platform Engineer on the Compute team, you’ll improve how engineers build and run services, helping ensure our compute platform is reliable at scale for our learners and fellow Duo engineers.

The Compute team builds and operates the core compute platform that powers our applications. We build paved roads (self-service platform primitives, templates, and tooling) and we operate them so product engineers can focus on shipping features with confidence.

This role is based in our Pittsburgh office and requires in-office presence Monday through Thursday.

🧠  You will...

• Build and operate core compute primitives that power production workloads based on Kubernetes, across different regions and cloud providers. 
• Improve the delivery pipeline from commit to production by evolving our GitOps and deployment patterns, making rollouts safer and faster.
• Raise the operational bar: define SLOs, build dashboards/alerts, write runbooks, and participate in on-call/incident response to keep the platform dependable.
• Enable effective self-service by turning platform capabilities into reusable abstractions.

✅  You have...

• Strong problem-solving skills and experience delivering and shipping pragmatic solutions in production environments.
• Experience with distributed systems fundamentals (networking, service-to-service communication, failure modes, caching/storage concepts).
• Experience working on production systems (through industry roles, internships, or substantial open-source work).
• Experience with one or more CI/CD tools (Jenkins, Argo CD, GitHub Actions) and infrastructure management tools (Terraform, CloudFormation)
• Clear written and verbal communication skills—comfortable writing docs/runbooks and collaborating across teams.
• Functional knowledge of Linux system administration and automation
  
  
  

⭐  Exceptional candidates will have...

• A Bachelor’s degree in Computer Science, related technical field, or equivalent practical experience
• Experience managing a production infrastructure on AWS, Google Cloud, Alibaba Cloud, or Azure.
• Exposure to multi-cluster or multi-region architectures and the operational patterns that make them reliable.
• Experience with service mesh / zero-trust networking patterns (e.g., Istio mTLS, traffic management, authorization policies).

Our mission at Duolingo is to develop the best education in the world and make it universally available. It’s a big mission, and that’s where you come in!

At Duolingo, you’ll join a team that cares about finding innovative solutions to complex technical problems, running countless experiments (300+ at a time!) with our massive user base to make data-driven decisions, and educating our users and employees alike. You’ll have limitless learning opportunities, mentorship and collaboration with world-class minds, and a variety of projects with large scopes — while doing work that’s both fun and meaningful. 

Join our life-changing mission to develop education for our half a billion (and growing!) learners around the world.

About the role...

As a Platform Engineer on the Compute team, you’ll improve how engineers build and run services, helping ensure our compute platform is reliable at scale for our learners and fellow Duo engineers.

The Compute team builds and operates the core compute platform that powers our applications. We build paved roads (self-service platform primitives, templates, and tooling) and we operate them so product engineers can focus on shipping features with confidence.

This role is based in our Pittsburgh office and requires in-office presence Monday through Thursday.

🧠  You will...

• Build and operate core compute primitives that power production workloads based on Kubernetes, across different regions and cloud providers. 
• Improve the delivery pipeline from commit to production by evolving our GitOps and deployment patterns, making rollouts safer and faster.
• Raise the operational bar: define SLOs, build dashboards/alerts, write runbooks, and participate in on-call/incident response to keep the platform dependable.
• Enable effective self-service by turning platform capabilities into reusable abstractions.

✅  You have...

• Strong problem-solving skills and experience delivering and shipping pragmatic solutions in production environments.
• Experience with distributed systems fundamentals (networking, service-to-service communication, failure modes, caching/storage concepts).
• Experience working on production systems (through industry roles, internships, or substantial open-source work).
• Experience with one or more CI/CD tools (Jenkins, Argo CD, GitHub Actions) and infrastructure management tools (Terraform, CloudFormation)
• Clear written and verbal communication skills—comfortable writing docs/runbooks and collaborating across teams.
• Functional knowledge of Linux system administration and automation
  
  
  

⭐  Exceptional candidates will have...

• A Bachelor’s degree in Computer Science, related technical field, or equivalent practical experience
• Experience managing a production infrastructure on AWS, Google Cloud, Alibaba Cloud, or Azure.
• Exposure to multi-cluster or multi-region architectures and the operational patterns that make them reliable.
• Experience with service mesh / zero-trust networking patterns (e.g., Istio mTLS, traffic management, authorization policies).

Mission

Speechify is the easiest way to listen to the world’s information. Articles on the web, documents in the cloud, books on your phone. We absorb it all and let you listen to it at your desk, on the go, at your own speed, and with tools that make learning easier, deeper, and faster.

What streaming services have done for audio entertainment, we’re doing for audio information. And whatever we’re doing seems to be working. We’re #1 in our category, and experiencing exponential growth.

Overview

We're looking for a Senior Software Engineer to join our Core Experiences Team. This team builds and maintains the foundational services and SDKs that power Speechify’s product experience across platforms. It's a critical role for someone who enjoys working at the intersection of product and infrastructure, thinks strategically, and is passionate about designing clear, reliable APIs and simple systems that directly enhance the user experience.

What You’ll Do

• Collaborate with Speechify’s Product Teams to scope projects, find ways to reduce scope to get faster feedback from customers, navigate the integration/UX tradeoffs relevant to different product teams, and deliver solutions via our cross-platform SDK
• Optimize existing functionality to ship things like faster loading and more intelligent parsing by designing more efficient abstractions and improving our algorithms
• Ship cloud functions, lightweight backend services, and jobs using Kotlin

An Ideal Candidate Should Have

• Systems thinking. You know that optimizing a system requires end-to-end design, and you believe simplicity is valuable.
• Speed. You work quickly to generate ideas and options and know how to decide which things can ship now and what things need time
• Focus. We’re a high-growth startup with a busy, remote team. You know how and when to engage or be heads down
• Collaboration. You know how to inspire, play, and negotiate with opinionated designers, marketers, and PMs
• Preferred Tech Stack:
  • Kotlin Multiplatform (Java experience is OK but role is Kotlin Multiplatform) 
  • Prior experience with GCP is a plus

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.

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.

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.

The ML Data Service team is seeking a highly experienced and motivated Staff Tech Lead Manager (TLM) to lead the development and operation of our core machine learning data infrastructure. This critical role requires a blend of deep technical expertise in machine learning systems, large-scale data processing, and proven leadership ability to manage both individual contributors and technical direction.

The ML Data Service team is responsible for providing reliable, high-quality, and easily accessible data for all ML use cases. As owners of the "Data Engineering" phase of the ML lifecycle, they manage the most critical input to any ML system: the data itself. Our infrastructure supports hundreds of data pipelines and petabytes of data, directly enabling the success of our flagship products.

What You'll Do

Technical Leadership and Strategy

• Define and drive the technical roadmap and long-term strategy for the ML Data Service platform, ensuring it meets the evolving needs of ML engineers across the company.
• Serve as the top technical expert for the team, architecting complex, highly scalable, and fault-tolerant systems for data ingestion, transformation, and serving.
• Lead the technical vision for the provision of diverse training data sources, including ingestion from real-world drive logs, resimulation outputs, autolabelling pipelines, and human labelling efforts.
• Drive the implementation of robust mechanisms for monitoring data quality, tracking data lineage, and ensuring overall data governance and compliance.
• Provide hands-on technical guidance, design reviews, and mentorship to engineers, ensuring the adoption of best practices, high code quality, and operational excellence.

Management and Team Growth

• Manage a team of software engineers, including performance reviews, career development, coaching, and mentoring.
• Act as a technical leader-manager hybrid, balancing 50% management duties with 50% technical leadership, architecture, and hands-on coding/design.
• Drive hiring and recruitment efforts to attract, onboard, and retain top engineering talent, fostering a diverse and inclusive team culture.
• Champion engineering excellence, operational rigor, and a strong sense of ownership within the team.

Collaboration and Execution

• Collaborate closely with ML model teams and Infrastructure teams to understand data needs and deliver solutions that accelerate ML development cycles.
• Lead the execution of major projects, ensuring on-time delivery and alignment with business objectives.
• Communicate complex technical concepts and strategic direction effectively to both technical and non-technical stakeholders, including executive leadership.

What We're Looking For

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 8+ years of experience in software engineering, with a strong focus on large-scale data systems, distributed systems, or ML infrastructure.
• 3+ years of experience managing engineering projects with a track record of delivering efficient tools and infra. Manger experience  of building and scaling high-performing teams is a strong plus (including mentoring, performance management, and career development).
• Deep expertise in data processing technologies (e.g., Spark, Flink, Beam, distributed databases) and experience with cloud platforms (e.g., AWS, GCP, Azure).
• Demonstrated experience designing, implementing, and operating production-grade ML data pipelines or feature stores.

This role is hybrid from our Pittsburgh office and requires two in-office days per week, ideally Tuesday and Thursday.

The ML Data Service team is seeking a highly experienced and motivated Staff Tech Lead Manager (TLM) to lead the development and operation of our core machine learning data infrastructure. This critical role requires a blend of deep technical expertise in machine learning systems, large-scale data processing, and proven leadership ability to manage both individual contributors and technical direction.

The ML Data Service team is responsible for providing reliable, high-quality, and easily accessible data for all ML use cases. As owners of the "Data Engineering" phase of the ML lifecycle, they manage the most critical input to any ML system: the data itself. Our infrastructure supports hundreds of data pipelines and petabytes of data, directly enabling the success of our flagship products.

What You'll Do

Technical Leadership and Strategy

• Define and drive the technical roadmap and long-term strategy for the ML Data Service platform, ensuring it meets the evolving needs of ML engineers across the company.
• Serve as the top technical expert for the team, architecting complex, highly scalable, and fault-tolerant systems for data ingestion, transformation, and serving.
• Lead the technical vision for the provision of diverse training data sources, including ingestion from real-world drive logs, resimulation outputs, autolabelling pipelines, and human labelling efforts.
• Drive the implementation of robust mechanisms for monitoring data quality, tracking data lineage, and ensuring overall data governance and compliance.
• Provide hands-on technical guidance, design reviews, and mentorship to engineers, ensuring the adoption of best practices, high code quality, and operational excellence.

Management and Team Growth

• Manage a team of software engineers, including performance reviews, career development, coaching, and mentoring.
• Act as a technical leader-manager hybrid, balancing 50% management duties with 50% technical leadership, architecture, and hands-on coding/design.
• Drive hiring and recruitment efforts to attract, onboard, and retain top engineering talent, fostering a diverse and inclusive team culture.
• Champion engineering excellence, operational rigor, and a strong sense of ownership within the team.

Collaboration and Execution

• Collaborate closely with ML model teams and Infrastructure teams to understand data needs and deliver solutions that accelerate ML development cycles.
• Lead the execution of major projects, ensuring on-time delivery and alignment with business objectives.
• Communicate complex technical concepts and strategic direction effectively to both technical and non-technical stakeholders, including executive leadership.

What We're Looking For

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 8+ years of experience in software engineering, with a strong focus on large-scale data systems, distributed systems, or ML infrastructure.
• 3+ years of experience managing engineering projects with a track record of delivering efficient tools and infra. Manger experience  of building and scaling high-performing teams is a strong plus (including mentoring, performance management, and career development).
• Deep expertise in data processing technologies (e.g., Spark, Flink, Beam, distributed databases) and experience with cloud platforms (e.g., AWS, GCP, Azure).
• Demonstrated experience designing, implementing, and operating production-grade ML data pipelines or feature stores.

This role is hybrid from our Boston and Pittsburgh offices and requires two in-office days per week, ideally Tuesday and Thursday.

The ML Data Service team is seeking a highly experienced and motivated Staff Tech Lead Manager (TLM) to lead the development and operation of our core machine learning data infrastructure. This critical role requires a blend of deep technical expertise in machine learning systems, large-scale data processing, and proven leadership ability to manage both individual contributors and technical direction.

The ML Data Service team is responsible for providing reliable, high-quality, and easily accessible data for all ML use cases. As owners of the "Data Engineering" phase of the ML lifecycle, they manage the most critical input to any ML system: the data itself. Our infrastructure supports hundreds of data pipelines and petabytes of data, directly enabling the success of our flagship products.

What You'll Do

Technical Leadership and Strategy

• Define and drive the technical roadmap and long-term strategy for the ML Data Service platform, ensuring it meets the evolving needs of ML engineers across the company.
• Serve as the top technical expert for the team, architecting complex, highly scalable, and fault-tolerant systems for data ingestion, transformation, and serving.
• Lead the technical vision for the provision of diverse training data sources, including ingestion from real-world drive logs, resimulation outputs, autolabelling pipelines, and human labelling efforts.
• Drive the implementation of robust mechanisms for monitoring data quality, tracking data lineage, and ensuring overall data governance and compliance.
• Provide hands-on technical guidance, design reviews, and mentorship to engineers, ensuring the adoption of best practices, high code quality, and operational excellence.

Management and Team Growth

• Manage a team of software engineers, including performance reviews, career development, coaching, and mentoring.
• Act as a technical leader-manager hybrid, balancing 50% management duties with 50% technical leadership, architecture, and hands-on coding/design.
• Drive hiring and recruitment efforts to attract, onboard, and retain top engineering talent, fostering a diverse and inclusive team culture.
• Champion engineering excellence, operational rigor, and a strong sense of ownership within the team.

Collaboration and Execution

• Collaborate closely with ML model teams and Infrastructure teams to understand data needs and deliver solutions that accelerate ML development cycles.
• Lead the execution of major projects, ensuring on-time delivery and alignment with business objectives.
• Communicate complex technical concepts and strategic direction effectively to both technical and non-technical stakeholders, including executive leadership.

What We're Looking For

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 8+ years of experience in software engineering, with a strong focus on large-scale data systems, distributed systems, or ML infrastructure.
• 3+ years of experience managing engineering projects with a track record of delivering efficient tools and infra. Manger experience  of building and scaling high-performing teams is a strong plus (including mentoring, performance management, and career development).
• Deep expertise in data processing technologies (e.g., Spark, Flink, Beam, distributed databases) and experience with cloud platforms (e.g., AWS, GCP, Azure).
• Demonstrated experience designing, implementing, and operating production-grade ML data pipelines or feature stores.

This role is hybrid from our Boston office and requires two in-office days per week, ideally Tuesday and Thursday.

Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

The Data Services Operations team plays a crucial role in delivering data and analysis that supports development of autonomous systems and features essential for a great ADAS driving experience. Within Data Services Operations, the GIS Services organization at Latitude is the operational backbone and spatial intelligence engine driving our system and its complex relationship with the world and our customers. We go beyond traditional High Definition (HD) map production to build, scale, and operationalize a GIS ecosystem capable of supporting a highly accurate and up-to-date ADAS driving network.

Within this organization, the GIS Platform Team is tasked with building, scaling, and maintaining the robust technological infrastructure that empowers all Latitude stakeholders to easily access, visualize, and exploit spatial data. We are looking for a highly skilled GIS Solutions Analyst (Front-End Support) to lead web application development, design intuitive cartographic templates, and build a seamless "one-stop shop" portal critical to reliable spatial data integration, analysis, and self-service capabilities across the Latitude AI enterprise.

What you’ll do: 

• Infrastructure & Database Management: Develop, optimize, and maintain enterprise spatial databases (specifically Postgres/PostGIS), including schema design, indexing strategies, and performance tuning for high-volume mapping data.
• Performant Geoprocessing: Design, build, and deploy custom Python geoprocessing tools and services that support high delivery velocity, complex vehicle mission routing, and self-service web applications across Latitude.
• Esri Enterprise Administration: Extend the functionality of Esri Enterprise GIS systems by implementing custom data feeds, managing server environments, and ensuring high availability.
• System Optimization: Monitor system performance, troubleshoot storage or network bottlenecks, and proactively implement infrastructure optimizations to support the at-scale global operations.
• Integration & Automation: Implement and maintain CI/CD pipelines and source control practices for geospatial tools, services, and infrastructure deployments.
• Cross-Functional Collaboration: Work closely with the Front-End Solutions Analyst, Operations stakeholders, Spatial Data & Analytics Teams, and Map Engineering to align backend geospatial architecture with business, operational, and delivery needs.
• Best Practices: Establish, document, and promote industry best practices for geospatial data engineering, system design, and backend deployment.

What you'll need to succeed:

• Associate or Bachelor’s Degree preferred.
• Proven experience building, deploying, and tuning relational and spatial databases, with deep proficiency in PostgreSQL and PostGIS.
• Exceptional skills in Python and SQL, specifically for backend geospatial data manipulation, automation, and API development (e.g., ArcPy, GeoPandas, SQLAlchemy).
• Hands-on experience deploying, maintaining, and scaling Esri Enterprise Architecture (Portal, Server, Data Store, Image Server).
• Proficiency in GIS software such as ArcGIS, QGIS, or similar.
• Familiarity with CI/CD workflows, version control (Git), and modern software development lifecycle practices.
• Strong analytical and problem-solving skills with a laser focus on system performance, backend reliability, and infrastructure optimization.
• Excellent communication and teamwork abilities

Nice to have:

• Experience with cloud infrastructure platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes) for GIS deployments
• Experience designing and scaling raster services, including modern formats (e.g., Cloud Optimized GeoTIFFs [COG], SpatioTemporal Asset Catalogs [STAC]), and enterprise image service delivery (e.g., Esri Image Server) to support high-volume Imagery Based Production (IBP).
• Experience taking nascent, ground-up GIS backend systems and evolving them into mature, highly performant enterprise architectures.
• Experience with Cloud Data Warehouse platforms such as Big Query or Snowflake.
• Familiarity with high-frequency spatial event data management and streaming architectures. Experience utilizing Elastic-stack technologies (Elasticsearch, OpenSearch) or message brokers (e.g., Apache Kafka) to synchronize real-time vehicle fleet telemetry and rapid map updates at scale.
• Familiarity with open-source GIS server technologies (e.g., GeoServer).
• Previous experience working in an autonomous vehicle (AV), ADAS, or high-definition (HD) mapping environment.

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

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:

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:

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:

We are seeking a highly skilled and motivated Principal Engineer, Technical Lead to lead our large-scale AI model and software evaluation framework – Ground Truth Regression. The ideal candidate will have a strong background in data engineering, machine learning principals and leadership, with experience in developing and deploying advanced data analysis and large scale orchestration frameworks.

At Motional, large scale orchestration for data analysis plays a critical role in delivering our ML-centered autonomous driving vehicle. Our robo-taxi ML Models and software are developed by hundreds of developers and deployed multiple times a day – The Ground Truth Regression team provides the large scale perception analysis framework for validating all changes to perception which can impact the autonomous vehicle behavior. 

The GTRegression team validates the end impact of ML and software changes to the autonomous vehicle while those changes are in development, providing the tools for Root Cause Analysis, and safety consideration. We monitor for model errors, anomalies, rare objects & long-tail driving scenarios across thousands of driving hours. The team develops the full stack – AWS Kubernetes orchestration framework, ReSimulation, model metrics, regression reports, and deep dive analysis UI’s. The team works together with all other perception and ML teams to develop the metrics and analyze results.

What You'll Do: 

• Lead a team of engineers with a diverse skill set to deliver critical software supporting the development of the autonomous vehicle ML models and software.
• Drive innovation by researching and developing new large scale data warehousing and analysis.
• Own large-scale data analysis workflows that surface unexpected impacts of planned and unplanned changes to the ML models and software.
• Build high-quality datasets to improve ML products through training & edge case validation.
• Provide statistical depth on model performance & generalization through rigorous error and change analysis.
• Provide technical leadership and mentorship to the team, fostering a culture of collaboration and continuous improvement.
• Manage project timelines, resources, and deliverables to ensure successful project execution.

What We're Looking For:

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• Excellent leadership, communication, and problem-solving skills.
• Proven record leading a small diverse dedicated team supporting a large user base.
• Experience in machine learning, data mining, and statistical analysis.
• Proven experience in developing and deploying large scale cloud frameworks.
• Strong programming skills in Python.
• Experience with large-scale data processing and distributed computing technologies.
  
  

Bonus Points:

• Ph.D. in Computer Science or a related field.
• Experience with cloud platforms such as AWS, Google Cloud, or Azure.
• Experience with machine learning in the autonomous driving domain.
• Publications or contributions to the AI/ML community.

Mission:

We are seeking a highly skilled and motivated Senior Data Analysis Engineer for our large-scale AI model and software evaluation framework – Ground Truth Regression. The ideal candidate will have a strong background in data engineering, machine learning principals and statistical analysis. 

At Motional, large scale orchestration for data analysis plays a critical role in delivering our ML-centered autonomous driving vehicle. Our robo-taxi ML Models and software are developed by hundreds of developers and deployed multiple times a day – The Ground Truth Regression team provides the large scale perception analysis framework for validating all changes to perception which can impact the autonomous vehicle behavior. 

The GTRegression team validates the end impact of ML and software changes to the autonomous vehicle while those changes are in development, providing the tools for Root Cause Analysis, and safety consideration. We monitor for model errors, anomalies, rare objects & long-tail driving scenarios across thousands of driving hours. The team develops the full stack – AWS Kubernetes orchestration framework, ReSimulation, model metrics, regression reports, and deep dive analysis UI’s. The team works together with all other perception and ML teams to develop the metrics and analyze results.

What You'll Do:

• Work with ML Engineers and Autonomy Software Developers to develop new data analysis metrics and KPI’s for the validation of the autonomous vehicle performance.
• Drive innovation by researching and developing new large scale data analysis systems.
• Own large-scale data analysis workflows that surface unexpected impacts of planned and unplanned changes to the ML models and software.
• Build high-quality datasets to improve ML products through training & edge case validation.
• Provide statistical depth on model performance & generalization through rigorous error and change analysis.

What We're Looking For:

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• Strong programming skills in Python, SciPy, and related data analysis frameworks.
• Experience in machine learning, data mining, and statistical analysis.
• Experience with large-scale data processing and distributed computing technologies.
• Strong communication and software development skills: goal setting, design documentation, test frameworks, collaborative cross team development.
  
  

Bonus Points:

• Ph.D. in Computer Science or a related field.
• Experience with cloud platforms such as AWS, Google Cloud, or Azure.
• Experience with machine learning in the autonomous driving domain.
• Publications or contributions to the AI/ML community.

Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.  

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

Latitude Cloud Platform engineers create reusable architecture via infrastructure as code for Latitude teams to leverage as common shared components and educate Latitude teams on how to architect their solutions for scale, security, and reviewed changes through automation. This includes ownership of the workload ecosystem on Kubernetes running on public and hybrid cloud environments.

The Cloud Platform team interacts with engineering teams including ingest/data processing, mapping, labeling, triage, machine learning (detection, prediction, tracking), motion planning/control, offline simulation, and release/deployment teams to unify development practices and scalable efficiency of cloud/cloud native technologies.

What you’ll do: 

• Architect and scale a multi-tenant, hybrid-cloud Kubernetes platform to ensure seamless workload portability across public and internal environments
• Develop custom Kubernetes operators and self-service abstractions to simplify complex infrastructure management for autonomous vehicle engineering teams
• Optimize high-performance distributed workloads by architecting specialized compute environments for ML and simulation on heterogeneous hardware
• Standardize end-to-end GitOps workflows and CI/CD pipelines to automate security, networking, and observability across the infrastructure lifecycle
• Provide technical leadership and architectural guidance to ensure engineering teams build resilient, cost-effective services aligned with cloud-native best practices
• Manage the lifecycle of critical platform components like service mesh and networking while proactively resolving systemic bottlenecks in hybrid cloud environments

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD)
• Hands on development in Python, Go, or Java to create production level services that incorporate CI/CD
• Experience in using infrastructure as code to automate the creation of cloud resources. E.g. Terraform, CloudFormation, or others
• Strong experience with architecting/deploying scalable services and workloads in the cloud (AWS, GCP) and/or cloud native environments
• Strong experience with deployment management/scheduling/high availability/failure modes for distributed applications and compute workloads running on CPUs and GPUs
• Understand engineering design limitations and provide guidance for teams to scale their deployments in the cloud so that they can achieve desired performance within budget
• Experience creating reusable deployment patterns for teams to adopt, that incorporate networking, security, monitoring, logging, alerting, continuous integration and deployments
• Understanding of API specification languages (e.g. Open API/gRPC) and the ability to create reusable code via code generation, templates, and other rapid development techniques for teams to consume
• Leverage and modify open source tools to meet unique requirements for internal teams, including but not limited to Kubernetes, Prometheus, FluentD, Istio, Envoy, CoreDNS, etcd, Flux, among others

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $179,200 - $268,800 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.  

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

As a Site Reliability Engineer on the team, you will be responsible for helping to build and run these mission critical systems.  Through the implementation of monitoring and automation, you will constantly ensure the health, reliability, scalability, and performance of the platforms.

The Site Reliability team interacts with engineering teams including ingest/data processing, mapping, labeling, triage, machine learning (detection, prediction, tracking), motion planning/control, offline simulation, and release/deployment teams to provide uniform service observability and incident response.

What you’ll do: 

• Build monitoring to ensure our platform is healthy and its reliability measurable
• Build alerting and a set of runbooks to enable faster detection and remediation of platform issues
• Debug complex issues that may combine multiple components of the stack and ensure proper fixes are implemented to prevent these issues from happening again
• Participate in an on-call rotation and culture of continuous improvement through blameless postmortems
• Design and implement components of the platform to enable features that make the work of our customers possible, simpler and more efficient
• Build Kubernetes controllers to automate operations

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD)
• Fundamental understanding of Linux operating system internals, TCP/IP networking, and storage subsystems
• Hands on development in Go or Python to create robust software that can run reliably in production
• Strong experience scaling and securing services in the cloud (AWS, GCP) or cloud native environments
• Experience using infrastructure-as-code principles to automate the creation of infrastructure resources (e.g. Terraform, CloudFormation)
• Experience authoring and maintaining Kubernetes Controllers in Go
• Experience running Kubernetes and related core components in a large-scale, production environment
• Experience with metrics (e.g. Prometheus), logging (e.g. Elasticsearch, Loki) and tracing (e.g. Jaeger, Tempo) systems
• Understanding of engineering design limitations and ability to provide guidance to teams to scale their services to achieve desired performance within budget
• A focus on increasing service reliability through defining and adhering to SLOs
• Strong communication skills and the ability to work effectively in a diverse and distributed team

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $179,200 - $268,800 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

About Us

Are you ready to build the future of supply chain? At Gather AI, we’re not just creating software; we’re pioneering a new era of warehouse intelligence. We’ve developed a groundbreaking, vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, completely digitizing workflows that have historically been manual and error-prone. This means facilities operate smarter, safer, and more efficiently, ultimately redefining “on-time, in full” delivery.

If you’re looking for an opportunity to contribute to truly transformative technology and make a significant impact in a vital industry, Gather AI is the place for you. We’re leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time.

About the Team

You’ll lead the Machine Learning and FPT teams, working closely with the Director of Cloud Engineering and Director of Autonomy. Cross-departmentally, you’ll collaborate with Product and Business leadership to translate ML capabilities into product value. This is a high-visibility role with a direct line to executive leadership and significant influence over product direction.

About the Role

We are looking for a Director of Machine Learning to define our ML strategy, lead our computer vision organization, and drive the next phase of ML maturity at Gather AI. You will assess existing ML and CV capabilities, identify gaps and opportunities, and establish a clear technical vision for how machine learning will power our warehouse intelligence platform over the next 12–18 months.

The ideal candidate brings deep computer vision expertise, a track record of shipping production ML systems, and the leadership experience to build and scale a world-class ML team.

What You’ll Do

• Define and own the ML strategy and technical roadmap for Gather AI, aligned with product and business objectives
• Lead and grow the Machine Learning and FPT teams, establishing a culture of rigor, experimentation, and production-quality delivery
• Drive improvements to core computer vision models (object detection, segmentation, OCR) used across our drone and MHE Vision products
• Build out MLOps infrastructure — model training pipelines, deployment, monitoring, and CI/CD for ML workloads
• Collaborate with the Director of Cloud Engineering and Director of Autonomy to ensure ML systems integrate seamlessly into the broader platform
• Partner with Product and Operations to translate customer needs into ML-driven product capabilities

What You’ll Need

• 10+ years building and scaling production ML or computer vision systems
• 5+ years managing and growing ML engineering teams
• Deep expertise in computer vision: object detection, image segmentation, OCR, and CNN architectures
• Strong Python and PyTorch (or TensorFlow) proficiency, plus a track record of shipping ML models to production at scale
• MS or PhD in Computer Science, Machine Learning, or a related field (strong industry track record considered in lieu of advanced degree)

Nice to Have

• Experience with drone, robotics, or autonomous systems perception
• Edge ML deployment experience (ONNX, TensorRT, mobile/embedded inference)
• Familiarity with warehouse, logistics, or supply chain domain
• Experience with AWS or GCP ML services (SageMaker, Vertex AI)

SOC Manager 

New York City, NY

Created in 2000, Ivalua is a leading global provider of cloud-based procurement solutions.

COMPANY OVERVIEW

At Ivalua we are a global community of exceptional professionals, who believe that digital transformation revolutionizes supply chain sustainability and resiliency to unlock the power of supplier collaboration. 

We achieve this through our leading cloud-based spend management platform that empowers hundreds of the world's most admired brands to effectively manage all categories of spend and all suppliers to increase profitability, improve ESG (environmental, social, and corporate governance) performance, lower risk, and improve productivity. Driven by our passions and fueled by our shared ambitions, we empower and challenge each other to create meaningful experiences for our colleagues, customers, partners, and communities. 

Learn more at www.ivalua.com. Follow us on LinkedIn and Twitter.

THE OPPORTUNITY

CONTEXT: 

Our IT department, international in scope (EMEA, AMER, APAC) and in full growth, is made up of over sixty IT & Cybersecurity professionals in charge of the deployment and operations of the Ivalua Cloud, which hosts the environments for our clients around the world.  It is also responsible for internal IT infrastructures, IT applications and data, IT support for our users as well as the Security monitoring & IT security handling.
In this context of growth, we are looking for a skilled SOC Manager based in Pittsburgh to expand our team capability and embrace the era of AI.

ROLE: 

The Manager, IT SOC is responsible for leading and developing a global Security Operations Center team, ensuring 24/7 security monitoring, effective incident response, and proactive vulnerability management across the organization.
This role provides technical leadership, operational governance, and strategic direction to protect the company’s infrastructure, cloud environments, applications, and data from cyber threats.
You will report to the Global IT Director and will manage a distributed team of SOC analysts based in the United States, France, and India, ensuring consistent processes, tooling, and service levels across regions.

WHAT YOU WILL DO WITH US 

1.  SOC Operations & Security Monitoring
• Lead and manage the global SOC team (6 analysts across multiple time zones, relying also on our 24/7 global IT Service center in India).
• Ensure continuous monitoring of security events using SIEM, EDR/XDR, NDR, and cloud security tools.
• Define, maintain, and optimize SOC processes, playbooks, and runbooks.
• Ensure detection use cases are continuously improved to reduce false positives and increase detection coverage.
• Manage SOC KPIs and SLAs (MTTD, MTTR, alert volume, incident closure rates).
2.  Incident Response & Threat Management
• Oversee security incident handling from triage to containment, eradication, and recovery.
• Act as escalation point for major security incidents and coordinate with IT, Infosec, Business,  Legal, and Communications teams.
• Lead post-incident reviews (lessons learned, root cause analysis) and implement remediation plans.
• Coordinate with external partners (MDR providers, forensics firms, law enforcement if required).
3. Vulnerability Management
• Collaborate closely with Infosec on the vulnerability management lifecycle: scanning, prioritization, remediation tracking, and reporting.
• Work with infrastructure, cloud, and application teams to ensure timely patching and risk mitigation.
• Define vulnerability SLAs based on risk and business criticality.
• Help Infosec to provide risk-based reporting to technology and business stakeholders.
4. Governance, Risk, and Compliance Support
• Contribute to security policies, standards, and operating procedures.
• Support audits, regulatory requirements, and frameworks (e.g., ISO 27001, NIST, SOC2, PCI DSS, GDPR, HIPAA, FEDRAMP, IRAP).
• Maintain documentation and evidence for security operations controls.
5. Tooling & Technology Strategy
• Own SOC tooling strategy (SIEM, SOAR,, vulnerability scanners, cloud security tools, etc.) and contribute to the other IT security solutions (EDR/XDR, Network & Cloud Security, Identity protection, etc.). Evaluate and implement new security technologies and integrations.
• Drive automation and orchestration to improve SOC efficiency and reduce manual workload.
• Contribute actively to the security logging quality (new technologies, review existing log sources and help to get them optimized and cleaned-up). 
6. Team Leadership & Global Coordination
• Manage and mentor SOC analysts across regions and time zones.
• Define shift models, on-call rotations, and coverage strategy.
• Conduct performance reviews, training plans, and career development.
• Foster collaboration between US, France, and India teams to ensure consistent operations and engage actively with the overall IT & Infosec community 
7. Reporting & Stakeholder Communication
• Produce executive-level security operations reports and dashboards.
• Communicate risks, incidents, and trends to senior leadership (CISO, IT leadership, risk committees).
• Provide guidance to engineering and business teams on security best practices.

YOUR PROFILE

If you have the below experience and strengths this role could be for you:

Mastery:
SIEM platforms (Splunk, Microsoft Sentinel, QRadar, Elastic, etc.)
EDR/XDR solutions (Microsoft Defender, CrowdStrike, SentinelOne, etc.)
Cloud security (Azure, AWS, GCP security monitoring and logging)

Proficient:
Vulnerability management tools (Qualys, Tenable, Rapid7, etc.).
Knowledge of NIST, MITRE ATT&CK, ISO 27001, SOC2, CIS benchmarks, and ITIL/IT operations processes
Excellent understanding of networking, operating systems, and application security fundamentals

Basic knowledge:
Familiarity with SOAR, threat intelligence platforms, and security automation
Knowledge of web application & database

Required experience:

Bachelor’s degree in relevant field preferred with a minimum of 10 years of relevant professional experience, OR Master’s degree in relevant field with a minimum of 8 years relevant professional experience, OR Equivalent combination of education and experience

Relevant certifications such as GIAC, OSCP, HTB are preferred. 7–12+ years in cybersecurity, with 3–5+ years in SOC or security operations leadership.
Proven experience managing distributed/global security teams.
Strong background in incident response, security monitoring, and vulnerability management.
U.S. Citizen / Permanent Resident. No sponsorship required

“Nice to have” experience:
Knowledge of cloud concepts and platforms, especially Azure.
Experience in an international company & team.
Experience in monitoring regulated environments (Fedramp, IRAP)

Soft skills:
Strong leadership and people management skills
Structured, process-driven, and comfortable with crisis management, problem solving aptitude
Team player, good communication skills and confortable working in multicultural, global teams and across time zones.
Strong reporting & good documentation writing skill.

WHAT HAPPENS NEXT

If your application fits this specific position’s needs, our skilled Talent team will reach out to schedule an initial screening call. Get one step closer to achieving your goals – apply today! 

Our Talent team will guide you through every step of the interview process - from preparation to completion. They're here to support you! 

Our recruitment process is designed to assess your competencies through a series of personalized interviews with internal stakeholders relevant to the role. 

Interviews will be conducted virtually via video or on-site with face-to-face meetings.

LIFE AT IVALUA

• Hybrid working model (3 days in the office per week),
• We're a team dedicated to pushing the boundaries of product innovation and technology,
• Sustainable Growth, Privately Held,
• A stable and cash-flow positive Company since 10 years,
• Snacks and weekly lunches in the office,
• Feel empowered to pursue your goals with improved team collaboration and increased creativity/productivity,
• Unlock and unleash your full professional potential with our exceptional training and career development program,
• Join a dynamic and international team of top-notch professionals who are experts in their respective fields. Collaborate with like-minded individuals who are deeply passionate and highly motivated about their work. Experience a truly diverse and inclusive work environment where your unique contributions are highly valued,
• Regular social events, competitive outings, team running events, and musical activities,
• Comparably recognized Ivalua for the following (https://www.comparably.com/companies/ivalua) :

Powered by People - Powered by You!

United by our values we embrace diversity and equity in the broadest possible sense to create an inclusive workplace. To help our customers make supply chains more efficient, sustainable and resilient, we rely on a global team with a variety of backgrounds, skills and views. We believe in equal opportunity and in diversity as a driver of innovation that cultivates a spirit of inclusiveness, creates a productive and fun place to work, and provides fulfilling career opportunities for all Ivaluans. https://www.linkedin.com/company/ivalua/about/

Experience life at Ivalua - check out our captivating video! Gain insight into our unique company culture and get a glimpse of what it's like to work with us.

One of Ivalua’s core values is to Care & Grow People. We take matters like pay equity very seriously and strive to reward our employees appropriately and fairly for their talents. The salary range for this position is based upon careful and continual market compensation research. In addition to location, salary may also vary based upon job-related knowledge, skills, and experience.

Title: Manager, IT - SOC

Base range minimum: $108,750

Base range maximum: $181,250

*Additional compensation / rewards: In addition to the base salary information above, Ivalua offers an uncapped commission plan as part of the competitive compensation package. Other compensation factors may also be considered. Ivalua also offers exceptional benefits including medical, dental, vision, retirement (with company match), and much more.

 #LI-SG1

#LI-HYBRID

SOC Manager 

Pittsburgh, PA

Created in 2000, Ivalua is a leading global provider of cloud-based procurement solutions.

COMPANY OVERVIEW

At Ivalua we are a global community of exceptional professionals, who believe that digital transformation revolutionizes supply chain sustainability and resiliency to unlock the power of supplier collaboration. 

We achieve this through our leading cloud-based spend management platform that empowers hundreds of the world's most admired brands to effectively manage all categories of spend and all suppliers to increase profitability, improve ESG (environmental, social, and corporate governance) performance, lower risk, and improve productivity. Driven by our passions and fueled by our shared ambitions, we empower and challenge each other to create meaningful experiences for our colleagues, customers, partners, and communities. 

Learn more at www.ivalua.com. Follow us on LinkedIn and Twitter.

THE OPPORTUNITY

CONTEXT: 

Our IT department, international in scope (EMEA, AMER, APAC) and in full growth, is made up of over sixty IT & Cybersecurity professionals in charge of the deployment and operations of the Ivalua Cloud, which hosts the environments for our clients around the world.  It is also responsible for internal IT infrastructures, IT applications and data, IT support for our users as well as the Security monitoring & IT security handling.
In this context of growth, we are looking for a skilled SOC Manager based in Pittsburgh to expand our team capability and embrace the era of AI.

ROLE: 

The Manager, IT SOC is responsible for leading and developing a global Security Operations Center team, ensuring 24/7 security monitoring, effective incident response, and proactive vulnerability management across the organization.
This role provides technical leadership, operational governance, and strategic direction to protect the company’s infrastructure, cloud environments, applications, and data from cyber threats.
You will report to the Global IT Director and will manage a distributed team of SOC analysts based in the United States, France, and India, ensuring consistent processes, tooling, and service levels across regions.

WHAT YOU WILL DO WITH US 

1.  SOC Operations & Security Monitoring
• Lead and manage the global SOC team (6 analysts across multiple time zones, relying also on our 24/7 global IT Service center in India).
• Ensure continuous monitoring of security events using SIEM, EDR/XDR, NDR, and cloud security tools.
• Define, maintain, and optimize SOC processes, playbooks, and runbooks.
• Ensure detection use cases are continuously improved to reduce false positives and increase detection coverage.
• Manage SOC KPIs and SLAs (MTTD, MTTR, alert volume, incident closure rates).
2.  Incident Response & Threat Management
• Oversee security incident handling from triage to containment, eradication, and recovery.
• Act as escalation point for major security incidents and coordinate with IT, Infosec, Business,  Legal, and Communications teams.
• Lead post-incident reviews (lessons learned, root cause analysis) and implement remediation plans.
• Coordinate with external partners (MDR providers, forensics firms, law enforcement if required).
3. Vulnerability Management
• Collaborate closely with Infosec on the vulnerability management lifecycle: scanning, prioritization, remediation tracking, and reporting.
• Work with infrastructure, cloud, and application teams to ensure timely patching and risk mitigation.
• Define vulnerability SLAs based on risk and business criticality.
• Help Infosec to provide risk-based reporting to technology and business stakeholders.
4. Governance, Risk, and Compliance Support
• Contribute to security policies, standards, and operating procedures.
• Support audits, regulatory requirements, and frameworks (e.g., ISO 27001, NIST, SOC2, PCI DSS, GDPR, HIPAA, FEDRAMP, IRAP).
• Maintain documentation and evidence for security operations controls.
5. Tooling & Technology Strategy
• Own SOC tooling strategy (SIEM, SOAR,, vulnerability scanners, cloud security tools, etc.) and contribute to the other IT security solutions (EDR/XDR, Network & Cloud Security, Identity protection, etc.). Evaluate and implement new security technologies and integrations.
• Drive automation and orchestration to improve SOC efficiency and reduce manual workload.
• Contribute actively to the security logging quality (new technologies, review existing log sources and help to get them optimized and cleaned-up). 
6. Team Leadership & Global Coordination
• Manage and mentor SOC analysts across regions and time zones.
• Define shift models, on-call rotations, and coverage strategy.
• Conduct performance reviews, training plans, and career development.
• Foster collaboration between US, France, and India teams to ensure consistent operations and engage actively with the overall IT & Infosec community 
7. Reporting & Stakeholder Communication
• Produce executive-level security operations reports and dashboards.
• Communicate risks, incidents, and trends to senior leadership (CISO, IT leadership, risk committees).
• Provide guidance to engineering and business teams on security best practices.

YOUR PROFILE

If you have the below experience and strengths this role could be for you:

Mastery:
SIEM platforms (Splunk, Microsoft Sentinel, QRadar, Elastic, etc.)
EDR/XDR solutions (Microsoft Defender, CrowdStrike, SentinelOne, etc.)
Cloud security (Azure, AWS, GCP security monitoring and logging)

Proficient:
Vulnerability management tools (Qualys, Tenable, Rapid7, etc.).
Knowledge of NIST, MITRE ATT&CK, ISO 27001, SOC2, CIS benchmarks, and ITIL/IT operations processes
Excellent understanding of networking, operating systems, and application security fundamentals

Basic knowledge:
Familiarity with SOAR, threat intelligence platforms, and security automation
Knowledge of web application & database

Required experience:

Bachelor’s degree in relevant field preferred with a minimum of 10 years of relevant professional experience, OR Master’s degree in relevant field with a minimum of 8 years relevant professional experience, OR Equivalent combination of education and experience

Relevant certifications such as GIAC, OSCP, HTB are preferred. 7–12+ years in cybersecurity, with 3–5+ years in SOC or security operations leadership.
Proven experience managing distributed/global security teams.
Strong background in incident response, security monitoring, and vulnerability management.
U.S. Citizen / Permanent Resident. No sponsorship required

“Nice to have” experience:
Knowledge of cloud concepts and platforms, especially Azure.
Experience in an international company & team.
Experience in monitoring regulated environments (Fedramp, IRAP)

Soft skills:
Strong leadership and people management skills
Structured, process-driven, and comfortable with crisis management, problem solving aptitude
Team player, good communication skills and confortable working in multicultural, global teams and across time zones.
Strong reporting & good documentation writing skill.

WHAT HAPPENS NEXT

If your application fits this specific position’s needs, our skilled Talent team will reach out to schedule an initial screening call. Get one step closer to achieving your goals – apply today! 

Our Talent team will guide you through every step of the interview process - from preparation to completion. They're here to support you! 

Our recruitment process is designed to assess your competencies through a series of personalized interviews with internal stakeholders relevant to the role. 

Interviews will be conducted virtually via video or on-site with face-to-face meetings.

LIFE AT IVALUA

• Hybrid working model (3 days in the office per week),
• We're a team dedicated to pushing the boundaries of product innovation and technology,
• Sustainable Growth, Privately Held,
• A stable and cash-flow positive Company since 10 years,
• Snacks and weekly lunches in the office,
• Feel empowered to pursue your goals with improved team collaboration and increased creativity/productivity,
• Unlock and unleash your full professional potential with our exceptional training and career development program,
• Join a dynamic and international team of top-notch professionals who are experts in their respective fields. Collaborate with like-minded individuals who are deeply passionate and highly motivated about their work. Experience a truly diverse and inclusive work environment where your unique contributions are highly valued,
• Regular social events, competitive outings, team running events, and musical activities,
• Comparably recognized Ivalua for the following (https://www.comparably.com/companies/ivalua) :

Powered by People - Powered by You!

United by our values we embrace diversity and equity in the broadest possible sense to create an inclusive workplace. To help our customers make supply chains more efficient, sustainable and resilient, we rely on a global team with a variety of backgrounds, skills and views. We believe in equal opportunity and in diversity as a driver of innovation that cultivates a spirit of inclusiveness, creates a productive and fun place to work, and provides fulfilling career opportunities for all Ivaluans. https://www.linkedin.com/company/ivalua/about/

Experience life at Ivalua - check out our captivating video! Gain insight into our unique company culture and get a glimpse of what it's like to work with us.

One of Ivalua’s core values is to Care & Grow People. We take matters like pay equity very seriously and strive to reward our employees appropriately and fairly for their talents. The salary range for this position is based upon careful and continual market compensation research. In addition to location, salary may also vary based upon job-related knowledge, skills, and experience.

Title: Manager, IT - SOC

Base range minimum: $108,750

Base range maximum: $181,250

*Additional compensation / rewards: In addition to the base salary information above, Ivalua offers an uncapped commission plan as part of the competitive compensation package. Other compensation factors may also be considered. Ivalua also offers exceptional benefits including medical, dental, vision, retirement (with company match), and much more.

 #LI-SG1

#LI-HYBRID

Aurora hires talented people with diverse backgrounds who are excited about building the future of transportation that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient & accessible for all. We are searching for an exceptional Staff-level Backend Software Engineer to join the Aurora Services Engineering team and take on a critical role in building Aurora's suite of fleet management tools.

The Aurora Services Engineering team creates full-stack solutions including backend services, web apps, mobile apps, and real-time onboard code that enable commercial operation of autonomous vehicle fleets at scale. Our mission is to build the software that drives the commercial side of our platform such as assigning work to autonomous vehicles, providing remote support, managing a fleet of vehicles, and receiving orders from customers. As Aurora prepares to massively scale its fleet and integrate with partners on an API level, the tools we build are critical to the efficient daily operation of our business.

As a Staff Backend Software Engineer you will join a team which builds solutions for autonomous vehicle terminal operations: launching and landing vehicles at locations owned by Aurora and its largest customers. You will add new features to existing products and greenfield completely new ones. Your contributions will have a significant impact on the way terminal operations function at Aurora.

In this role, you will

• Design complex systems from the ground up, working closely with software, hardware, and infrastructure engineering teams along with other stakeholder teams within Aurora.
• Embrace AI tools to add new features which delight our users, along with improving frontend, backend, and onboard engineering efficiency.
• Build backend services running in Aurora’s AWS cloud used to monitor and manage the location and activity of our entire autonomous fleet.
• Establish technology and infrastructure to scale our products with high availability and reliability.
• Collaborate with stakeholders including Security, Product, Design, Safety, and Cloud Platform to achieve company milestones.
• Send suggestions and receive updates from vehicles in real time in order to ensure the safe operation of Aurora’s autonomous fleet.
• Contribute to and evolve our team culture around mentorship, feedback, collaboration, and engineering excellence.

You will be a good fit if you have

• Phenomenal communication skills. We build software with people and for people. You know how to write an effective technical spec, provide feedback to others, translate technical concepts into lay terms, and incorporate feedback into your efforts. You value and practice openness, empathy, kindness, and collaboration.
• A preference for action. You will use good judgment to balance speed and quality. You will deliver products that are built in a responsible and sustainable way. You will use a self-starter mentality to thrive in a growing environment where all hands are on deck, and consider no obstacle too big or too small. You will notice where there is a need and will hustle to fill it.
• The drive to make teams stronger. You're excited to work hard and fast to the finish line on new opportunities with a collaborative and integrated team. You will be proactive in engaging conflict with openness, patience and kindness in an environment where it is safe to lean on each other and learn from failures.
• Motivation to own the product lifecycle end to end. You’re happy to engage with our product and design teams and our internal customers to understand their needs and find ways to meet them. You ensure that product development stays on course all the way through release and post-release support.
• Strong backend service engineering skills. We use modern technologies to build our products including Golang, Python, C++, gRPC, Kubernetes, and AWS. We’re happy to help you learn and adapt to our stack.
• Experience working with databases and caches such as Postgres and Redis.
• Bachelor’s or Master’s Degree in Computer Science or a related field.
• 6+ years of industry experience with a  focus on high-availability cloud services.

Desirable experience

• Experience taking a SaaS development project into production at scale.
• Experience building gRPC services using Golang.
• Experience with IoT devices and Over-the-Air communication.
• Experience with Kubernetes, including service configuration, monitoring and deployment.
• Experience with cloud environments such as AWS, Google Cloud, or Azure.
• Experience with fleet management solutions for robots, vehicles, or aerial drones.
• Experience with external customer facing software including production rollout with real customers.

The base range for this position is $171,000 - $273,000.  Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

 #LI-WS1 #Senior 

What we are looking for

We’re searching for a Senior Cloud Security Engineer. You will be part of the Cloud Security engineering team dedicated to building resilient, automated security systems at scale. 

Cloud security collaborates with infrastructure and application teams closely. The areas we cover are infrastructure security, workload security, and CI/CD hardening.

Our team is dedicated to building resilient, automated systems at scale. We take a hybrid approach to our toolkit: we utilize the best of open-source (OPA, Trivy, Spire) and COTS products, while still writing custom code to automate workflows and harden our global digital integrity. You’ll help us strike the perfect balance between leveraging existing solutions and building custom ones from the ground up.

In this role you will

• Secure Aurora’s cloud environment in the areas of but not limited to:
• Manage IAM roles and policies
• Enforce security controls
• Construct security boundaries for resources and services
• Provide security guidance involving Cloud and Kubernetes
• Create automation to solve security problems at the root
• Design, build, and configure security infrastructure clouds such as like AWS, Azure, or GCP
• Manage the security posture of workloads deployed on Kubernetes environments

Required qualifications

• 5+ years of progressive experience in security engineering
• Understanding of fundamental security concepts such as Authentication, Authorization, Zero-Trust, and their application to cloud native infrastructure and applications. 
• Hands-on experience in securing cloud and Kubernetes environments. Experience with Kubernetes admission controllers, vulnerability management, supply-chain security, network security, and use of mTLS and PKI to secure infrastructure.
• Ability to design and implement security controls for Kubernetes, including strong knowledge of authorization models, admission controllers, and security best practices.
• Understanding of modern Identity and Access Management (IAM) standards and technologies such as OAuth2/OIDC, SAML.
• Proficiency in at least one modern programming/scripting language (e.g., Python or Go) for building security automation.
• Experience writing and using Terraform.

Desirable qualifications

• Deep fundamental understanding of enterprise-level network security, operating system (Linux), Kubernetes, CI/CD, and application security principles.
• Familiarity with compliance frameworks (e.g., SOX, SOC 2, ISO 27001).
• Familiarity with machine identity frameworks like SPIFFE/SPIRE, mTLS or equivalent.

The base salary range for this position is $146,000 - $211,000 per year. Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. We’re searching for a Software Engineer II, Test Drive.

Role/Team overview:

Test Drive team as a Software Engineer and play a pivotal role in the development and validation of autonomous driving technology. Our team is at the forefront of building the critical tools, robust data pipelines, and scalable infrastructure. This role will be measured by how productive our entire organization is. You straddle the line between front-end and back-end development with advanced knowledge in multiple frameworks and languages.

In this role, you will be instrumental in designing and implementing a robust, integrated, and user-friendly platform that serves as the backbone of Aurora’s offline testing workflows. This challenging and rewarding work is absolutely essential for generating the high-quality, diverse data needed to thoroughly validate and continuously optimize the Aurora Driver's planning behavior. Your contributions will directly impact our ability to scale the Aurora Driver safely and efficiently, bringing the future of autonomous transportation closer to reality. 

We are looking for passionate and skilled software engineers who are eager to tackle complex problems and contribute to a mission-critical component of Aurora's success. Success in this role requires a value for design, a commitment to fast learning, and strong teamwork. You will be expected to quickly adapt to new technologies, understand the full web stack, and take ownership of shipping impactful results.

In this role, you will

• Design, develop a platform for validating off-board autonomy software.
• Develop tools for increasing the development speed of building and evaluating autonomy software.
• Build highly scalable, robust, and fault-tolerant services that support our unique rate-of-growth requirements
• Develop tools for introspection, visualization, and performance analysis of autonomy systems.
• Improve the performance of autonomy systems through architectural and algorithmic optimizations
• Collaborate with stakeholders including Autonomy Engineers, Test Engineers, Product, Cloud Platform and Safety to ensure timely delivery of validation data set.

Required Qualifications

• Experience with cloud automation, data and test automation
• Experience with modern programming languages such as Python, Golang, or Typescript.
• Experience with cloud offerings such as AWS or GCP.
• Experience with cloud storages such as S3, Postgres and Redis.

Desirable Experience

• Experience in Distributed Systems and Concurrency.
• Experience in Scaling Data Pipelines through Observability and Traceability.
• Experience in Self Driving / Autonomy Driving.

The base salary range for this position is $126,000-$181,500 per year.  Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits. 

 #LI-KW1

#Associate 

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. We’re searching for a Software Engineer to join Aurora’s Behavior Planning ML Platform team.  Our team is responsible for building both the offline pipelines to train and evaluate models and the infrastructure to efficiently run these models onboard the vehicle. On the offboard side, we build and support  the large scale distributed pipelines that model developers rely on to source data at scale, train, and evaluate machine learning models. On the onboard side, we build and maintain the on-vehicle infrastructure required to deploy these models and run inference in a soft real-time system.

In this role, you will

• Develop large scale pipelines for data extraction, model training and model evaluation
• Build and optimize onboard ML infrastructure used to deploy models and run inference onboard the vehicle
• Collaborate closely with motion planning, systems engineering, and other autonomy groups to define and develop critical ML workflow requirements.

Required Qualifications

• BS or higher degree in Computer Science/Engineering or related fields. > 6 months of experience
• Strong programming skills in C++ or Python, ideally both
• Experience with machine learning frameworks (PyTorch or TensorFlow)
• Solid foundation in computer science fundamentals - especially operating system concepts including concurrency, memory management and process scheduling.

Desirable Qualifications (this section is optional)

• Experience with GPU programming and Nvidia profiling tools - CUDA, NSight Systems, Nsight Compute
• Experience working in cloud compute (AWS, Azure, GCP) ideally with batch processing or other large-scale workflow management platforms. 
• Experience profiling and optimizing software on Linux

The base salary range for this position is $126,000 - $181,000 per year.  Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

#LI-JL261

#Mid-Senior 

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. 

We are looking for a Software Engineer to partner with our Mapping team to deliver stable, fast, scalable solutions for the Aurora Atlas – our mapping storage and versioning system. The Atlas powers many key functions, from map update processes, test creation systems, offboard simulations, visualizations, and onboard perception and decision making. This role is ideal for those who are energized by challenging problems at the intersection of scalable backend systems, data versioning and cross team collaborations.

In this role you will:

• Design, develop, and maintain the scalable backend infrastructure and data processing pipeline for storing and serving map data as we onboard the Aurora Driver to more commercial routes.
• Establish and maintain robust testing and performance optimization practices to ensure the stability and scalability of the Atlas system.
• Partner closely with internal and external customers to influence existing and future designs and features.

Required Qualifications:

• 4+ years experience building server side and data processing systems.
• Expert proficiency in C++ with a commitment to writing clean, testable, and production-ready code.
• Deep understanding of distributed systems principles, with a proven ability to deliver scalable, reliable backend systems.
• Strong understanding of cloud-native technologies (e.g., AWS, GCP, Kubernetes).
• Excellent communication and collaboration skills.
• Proven ability to rapidly learn new technologies and adapt to evolving requirements.

Desirable Qualifications:

• M.S. or Ph.D in Computer Science or a similar technical field, or equivalent practical experience.
• Domain experience with geospatial data, mapping systems, or high-throughput data pipelines.
• Working proficiency in Python and Golang.

The base salary range for this position is $146,000 - $234,000 . Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

 #LI-Mid-Senior

Position Overview

We are looking for a Software Engineer to work at the forefront of developing and optimizing the software infrastructure and tools necessary for training cutting-edge AI models. You will focus on building robust, scalable, and efficient training pipelines and frameworks that support the entire machine learning lifecycle, from data preparation to model deployment. You will collaborate with researchers and machine learning engineers to ensure seamless integration and operation of training systems, pushing the boundaries of what AI can achieve in real-world robotics applications. You will explore new ways to efficiently make use of many types of data in our training pipeline.

Responsibilities

• Develop and maintain robust, scalable, and distributed training pipelines (data preprocessing, training orchestration, and model evaluation) and frameworks for large-scale AI models.
• Optimize training processes for performance and resource utilization, ensuring scalability and reliability.
• Collaborate with researchers and machine learning engineers to integrate state-of-the-art algorithms and techniques into training pipelines.
• Monitor and analyze training, identifying bottlenecks and proposing solutions to improve efficiency and performance.
• Ensure the robustness and reliability of the training infrastructure, including automated testing and continuous integration.

Preferred Qualifications

• BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
• Minimum of 3 years of industry experience.
• Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
• Strong background in distributed computing, parallel processing techniques, handling large-scale datasets and data preprocessing.
• Deep understanding of state-of-the-art machine learning techniques and models.
• Experience with cloud-based training environments (AWS, Google Cloud, Azure).
• Experience in developing and maintaining software tooling and infrastructure for machine learning.
• Deep understanding and practical experience with software engineering principles, including algorithms, data structures, and system design.
• Experience with continuous integration and automated testing frameworks.

About The Role

Join the Autonomy team as a Senior Software Engineer where you will architect and contribute to the core robot software platform by driving the development of critical software modules and their interfaces. You will establish a data-driven approach to system performance by building scalable telemetry and metrics infrastructure, alongside rigorous regression testing plans, to track KPIs and monitor long-term reliability. This high-impact role is essential for enabling the next phase of commercial scaling by ensuring the robot can reliably perceive, plan, and execute complex tasks within dynamic environments.

About The Work

• Drive the implementation of selected middleware solutions to optimize communication and scalability across the core software platform.
• Define, document, review, and enforce process boundaries and API contracts, driving organization-wide alignment.
• Collaborate closely across the robot software and architecture teams to solve complex, cross-functional problems and ensure robust performance on physical robot hardware.
• Own and maintain the large-scale regression pipelines to automatically measure critical autonomous behavior metrics and track key performance indicators (KPIs) across motion planning, navigation, and localization.

About You

• Demonstrated expertise in designing and implementing multi-process robot architectures and distributed systems. Proficiency with different robotics middleware solutions (e.g., ROS, DDS, custom messaging) and experience with inter-process/inter-machine communication.
• Strong experience developing and maintaining telemetry/metrics pipelines (e.g., using OpenTelemetry/Otel). Proficiency in querying and analyzing large datasets using SQL-like big data tools (e.g., Amazon Athena, Spark SQL) and time-series databases (e.g., Prometheus, InfluxDB).
• Demonstrated expertise in simulation at scale, including techniques like domain randomization and procedural content generation. Hands-on experience transitioning models/behaviors from simulation (e.g., Gazebo, MuJoCo, Isaac Sim) to real-world physical robot hardware.
• Proficiency in programming languages commonly used in robotics/testing (Python, C++).
• Experience with CI/CD pipelines (e.g., Git, Jenkins, GitHub Actions) and containerization technologies (e.g., Docker, Kubernetes) for scaling simulation and deployment environments.
• Deep understanding of robotics fundamentals, including kinematics, dynamics, controls, and perception.
• MS or Ph.D. in Robotics, Computer Science, or a related field, or equivalent industry experience.

Bonus Qualifications

• Familiarity with cloud storage solutions and data lakes (e.g., AWS S3, Google Cloud Storage).
• Hands-on experience creating impactful data visualizations and dashboards using tools like Datadog, Grafana, or Apache Superset.
• Experience training or deploying Reinforcement Learning (RL) agents for complex autonomous behaviors.
• Publications in top-tier robotics or related conferences (RSS, ICRA, IROS).

This a hybrid position based out of one of our Salem, Pittsburgh, or Fremont offices.

The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future.

About the Role:  

Veeam, following its acquisition of Securiti AI - the leader in AI-powered data security posture management (DSPM) - is seeking a Senior Sales Engineer to drive technical leadership in our sales team, focusing on the Securiti AI portfolio. 

You will guide customers from needs assessment to solution design, delivering hands-on demos and proof-of-concepts to showcase value. Success in this role requires strong technical skills and the ability to build trust with clients.

You’re already a technical leader trusted at executive levels when the conversation shifts from “we need to secure our data” to “we need to enable safe, compliant AI at scale.” 

You’re already an expert on data/AI security and a proven enterprise sales engineer. Now it’s time to join the home of Data and AI Trust. 

You’ve already seen our new release of Agent Commander, but you haven’t seen what’s coming next. After the acquisition of Securiti AI, Veeam is even further into the forefront of data resilience, protection, trust, and the acceleration of safe AI at scale.

Are you ready for an exciting new challenge at enterprise scale?

What You’ll Do: 

• Act as the primary technical contact for Securiti AI solutions during the sales cycleServe as the primary technical data protection expert for Securiti AI and Veeam solutions throughout the pre-sales cycle.
  
• Lead discovery to translate risk, architecture, and business goals into a practical solution approach.
  
• Design and deliver tailored demos and hands-on proof-of-concepts that prove value in the customer’s environment.
  
• Drive technical conversations on AI Trust, Data Discovery, DSPM, Data Access & Governance, and Compliance (including GDPR, HIPAA, PCI-DSS).
  
• Provide solution guidance across AWS, Azure, and GCP, including cloud security best practices and identity/access concepts.
  
• Partner cross-functionally with sales, product, engineering, and customer success to ensure clean technical handoff and customer confidence post-sale.
  
• Hone your professional development through hands-on experimentation, team collaboration, robust onboarding, and more.
  
• Work ~80% remote, with client-facing travel usually 1-2 short trips per month.

What You’ll Bring (required): 

• Extensive enterprise sales experience in data protection, cloud security, networks, and AI.
  
• Proven ability to quickly develop trust and credibility with both technical and business stakeholders.
  
• Strong technical leadership foundation in enterprise data protection, cloud security, networks, and AI.
  
• Hands-on experience with AWS, Azure, or GCP (multi-cloud exposure strongly valued).
  
• Deep working knowledge of data privacy/security and compliance programs, especially GDPR, HIPAA, and PCI-DSS, plus data governance and access controls.
  
• Ability to build and run compelling demos and POCs while earning trust as a customer-facing technical lead.
  
• Practical technical fluency with areas such as Linux, Kubernetes/containerized environments, and modern cloud/data architectures.
  
• Strong expertise with DSPM, DLP, data discovery approaches (e.g., patterns/keywords/dictionaries/regex/exact matching) and with common cloud/data systems (e.g., object storage and enterprise databases/warehouses).

Preferred (strong differentiators): 

• Experience applying or discussing GenAI security in real enterprise contexts, including RAG (Retrieval-Augmented Generation) concepts and vector databases / indexing approaches.
  
• Exposure to CASB / SASE / DLP technologies and how customers operationalize them.
  
• Relevant certifications (CISSP, CISM, AWS/Azure/GCP).
  

#LI-JC3

About us

TeleTracking began with a simple but powerful belief that no one should wait for the care they need. More than a slogan, it’s a promise to continually improve healthcare.

TeleTracking builds groundbreaking technology incorporating deep clinical expertise. Our solutions are used in the nation’s largest healthcare systems and around the world to positively impact patients, families and communities.

What’s your contribution to the TeleTracking story?

When you choose to bring your passion and skills to help achieve our purpose, you’ll be part of a team that understands that there’s a human life behind every data point.   Your skills, curiosity, and compassion—will help fuel our innovation and achieve the TeleTracking promise of revolutionizing modern healthcare. 

About the role

The Director of Data Engineering is responsible for defining and executing the long-term technical strategy of the enterprise data platform while ensuring reliable, secure, and scalable day-to-day operations. This role combines deep technical leadership, architecture ownership, client engagement, cross-functional collaboration, and team management.

What you will do

Architecture & Delivery Oversight

• Oversee the design, development, and delivery of data pipelines, platform enhancements, and large-scale data solutions.
• Review engineering designs, remove technical blockers, and lead architectural decision-making.
• Ensure all technical solutions support scalability, performance, reliability, and cost-efficient operations.

Strategy & Platform Architecture

• Define the long-term data platform vision, including data lake/warehouse strategy, governance frameworks, data modeling, and technology tooling.
• Drive strategic alignment between platform architecture and organizational goals.
• Establish and enforce architectural standards ensuring consistency and future platform growth.

Technical Leadership

• Own the overall technical strategy while managing critical operational priorities.
• Define and approve technical and behavioral acceptance criteria.
• Participate in client VOC discussions to gather requirements.
• Lead architecture and system design reviews.
• Guide engineering best practices.
• Drive cloud cost-optimization efforts.
• Partner with business leaders to define ROI and platform investment impact.
• Develop and manage budget for the department, including employee, contractor and cloud spending.

Stakeholder & Cross-Functional Collaboration

• Collaborate with product, analytics, ML, engineering, and executive leadership.
• Translate business objectives into scalable technical solutions.
• Influence roadmap prioritization based on business and technical needs.
• Participates in focused technical discussions with key clients.

Vendor Management

• Act as a technical and business liaison with vendors.

Operations, Governance & Optimization

• Ensure platform reliability, data quality, observability, and compliance.
• Lead governance activities including audits and access reviews.
• Serve as the ISO audit point of contact.

People Leadership & Team Management

• Hire, mentor, and develop data engineering talent.
• Establish performance expectations and foster a culture of quality and accountability.

What we look for

• 7 + years of experience in data architecture, cloud-based data infrastructure, distributed systems, and building reliable data pipelines that support analytics and AI/ML workloads.
• Strong expertise in data architecture, cloud data platforms, and building scalable data pipelines using technologies such as AWS/Azure/GCP, Snowflake, Databricks, or Spark.
• Experience building and operating large-scale data pipelines.
• Proven engineering leadership and cross-functional collaboration skills.
• Experience aligning data strategy with business outcomes.
• Experience in regulated industries such as healthcare or education. (preferred)
• Background in cloud cost optimization and platform modernization. (preferred)

Education

• Bachelor's in computer science, computer information or any related discipline with equivalent combination of work and experience. (required)
• Master's in computer science, computer information or any related discipline (preferred)

Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future.