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 Security Platform Engineer to join our Enterprise Security Engineering team, reporting to the Technical Lead Manager of Security Engineering.

Aurora is scaling its autonomous trucking operations, and we need someone who makes our security tools actually work, not just deployed, but deeply configured, continuously tuned, and fully leveraged. This role is for the practitioner who has spent their career living inside security platforms: the person who knows their EDR better than the vendor's own support team, who can write a SIEM query from memory, and who instinctively knows when an alert is misfiring and exactly why.

This is not a software engineering role. It's a role for an elite security operator — someone with the instincts of a seasoned SOC analyst and the technical depth to own the platforms that power detection, response, and protection at enterprise scale. If you find deep satisfaction in mastering a tool, closing a coverage gap, or hunting down a threat that nobody else noticed, this role was written for you.

In this role you will

• Own the operational health, configuration, and continuous improvement of Aurora's enterprise security platform stack — including EDR/XDR, MDM, SIEM, DLP, IAM/IGA, DNS security, Email security, and PKI — ensuring each tool is tuned, policy-complete, and delivering reliable signal.
• Develop and refine detection rules, correlation logic, and alert policies, reducing noise while ensuring Aurora maintains high-fidelity coverage against real threats.
• Conduct proactive threat hunting across Aurora's security telemetry — forming hypotheses, querying logs, and investigating anomalies before they surface as incidents.
• Serve as the deepest internal expert on Aurora's enterprise security tooling, acting as the escalation point for complex platform issues, misconfigurations, and detection failures.
• Participate in the team's on-call rotation, leading deep-dive investigations into security alerts and incidents and driving triage, containment, and root cause analysis.
• Continuously audit and validate that existing security controls are configured to actually do what they're supposed to do — not just deployed and forgotten.
• Maintain operational runbooks, detection documentation, and platform configuration records, ensuring the team can operate consistently and scale institutional knowledge.

Required qualifications

• 12+ years of hands-on experience in enterprise security operations, security platform administration, or a senior SOC engineering role — with a career built on deep operational ownership of security tooling rather than software development.
• Expert-level proficiency administering and operating at least two enterprise security platforms (e.g., CrowdStrike, SentinelOne, Splunk, Panther, Sentinel, Jamf, Kandji/Iru, Puppet, WorkspaceONE, Intune, Zscaler, Okta, Proofpoint, Wiz, osquery), with strong working knowledge across several others.
• Demonstrated ability to tune and optimize security platforms beyond out-of-the-box configurations — writing custom detection logic, adjusting policy sets, and validating control effectiveness.
• Strong log analysis and threat hunting skills: you know how to build a hypothesis, write the query, follow the thread, and know when to escalate.
• Experience conducting thorough incident investigations — triage, containment, root cause analysis, and post-incident review — and communicating findings clearly to technical and non-technical stakeholders.
• Ability to assess security control effectiveness: not just "is this tool deployed" but "is it configured correctly, covering the right scope, and generating actionable signal."
• Comfort working under pressure in ambiguous, fast-moving situations with competing priorities.

Desirable qualifications

• Scripting ability for automation, log parsing, or workflow improvement (Python, Bash, or similar) — you don't need to be a software engineer, but you can write a script when it saves you an hour.
• Deep familiarity with MITRE ATT&CK as an operational tool for detection gap analysis and threat hunting hypothesis development.
• Experience with AWS security telemetry (CloudTrail, GuardDuty, Security Hub) and integrating cloud signals into a corporate SIEM.
• Familiarity with Zero Trust and identity-centric security models as they apply to policy enforcement in IAM and endpoint platforms.
• Platform-specific certifications such as CrowdStrike Certified Falcon Administrator, Splunk Core Certified Power User, or equivalent — or practitioner certifications like GCIH, GCIA, GCFE, or GCFA.

The base salary range for this position is $171,000 - $247,000 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.

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 Security Engineer to join our Enterprise Security Engineering team, reporting to the Technical Lead Manager of Security Engineering.

Aurora is scaling its autonomous trucking operations, and the security foundations protecting our employees, devices, internal systems, and data need to scale with us. We're looking for a deeply technical enterprise security engineer who is as comfortable in a code editor as in a security console — you build the systems that make Aurora's security operations possible. This is a role for someone who can architect robust enterprise security solutions, write the code to implement them, and partner across Engineering and IT to make sure security is embedded from the start, not bolted on at the end.

This is not a security operations-only role. It sits squarely in enterprise security engineering, where the work is designing, building, and owning the platforms, integrations, and automation that power Aurora's internal security posture at scale.

In this role you will

• Own the architecture and implementation of Aurora's enterprise security controls — designing the systems and integrations that protect Aurora's endpoints, identities, internal infrastructure, and SaaS environment.
• Design and build Aurora's security telemetry and detection infrastructure, including log pipelines, SIEM integrations, and alerting frameworks — in partnership with the Security Operations Engineer who owns ongoing tuning and rule development.
• Define and enforce enterprise security standards, conducting architecture and design reviews to ensure alignment with Aurora's security posture and risk tolerance.
• Partner with IT, Infrastructure, and Engineering teams to embed security requirements early — shifting left on corporate IT initiatives before they become technical debt.
• Build automation and tooling that extends the capabilities of Aurora's security platforms, reduces manual operational burden, and scales the team's impact.
• Serve as the escalation point for enterprise security incidents requiring engineering-level investigation or remediation, and participate in the team's on-call rotation.
• Translate security strategy into concrete, executable engineering projects with clear milestones and measurable outcomes.

Required qualifications

• 12+ years of hands-on experience in enterprise security engineering or corporate information security — specifically securing employee-facing systems, endpoints, identities, and internal infrastructure (not product or application security).
• Proficiency in at least one programming language, used in a security context — writing production-quality automation, integrations, or internal tooling (the team primarily uses Go; Python is also common).
• Experience architecting and integrating enterprise security platforms — designing API integrations, automating workflows, and building tooling that extends platform capabilities across domains such as EDR/XDR, MDM, IAM/IGA, DLP, SaaS security, cloud security, or PKI.
• Experience designing and building security telemetry pipelines and detection infrastructure — log ingestion, normalization, SIEM integration, and alerting architecture.
• Experience leading cross-functional security engineering projects — defining scope, driving execution, and aligning stakeholders across Engineering and IT.
• Track record of conducting security architecture reviews and translating findings into actionable, risk-prioritized remediation plans.
• Experience evaluating security posture and identifying systemic gaps, with a bias toward building durable solutions rather than one-off fixes.

Desirable qualifications

• Experience with Zero Trust architecture and identity-centric security models (BeyondCorp-style or similar).
• Familiarity with NIST CSF, MITRE ATT&CK, and CIS Benchmarks as engineering inputs — used to inform what to build and how to validate it, not just as compliance checkboxes.
• Hands-on AWS security experience (SCPs, GuardDuty, Security Hub, IAM, etc.) and familiarity with integrating cloud security signals into a corporate security platform.
• Experience with applied cryptography and PKI in a production enterprise environment — certificate lifecycle management, CA design, or secrets management.
• Familiarity with securing AI/ML platforms or applications built on LLMs, RAG pipelines, or MCP-based architectures.
• Security certifications such as CISSP, GCED, GREM, or similar (valued but not required).

The base salary range for this position is $171,000 - $247,000 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.

#Mid-Senior 

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

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

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

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.

Position Overview

Woolpert is hiring a Senior Software Engineer to join our dynamic Atlas Labs team supporting our Geospatial sector. This position reports to the Director of Product and AI. Atlas Labs oversees technology development for Woolpert’s Geospatial sector, including various types of AI model development, R&D, software infrastructure, and user-facing products.

We are unable to provide visa sponsorship for this position.  Applicants must already possess work authorization in the country the job is located.

What You Will Do:

• Contribute to the planning, research, design, architecture, development, and testing of Atlas Labs software features. You’ll write code daily, definitely in Python and possibly in C++ or JavaScript.
• Work as part of a cross-functional Scrum team with domain experts in AI/ML, Geospatial Data, Software Engineering, and GIS.
• Collaborate with internal and external users to ensure the correctness, quality, and availability of Atlas Labs software products.

What You Will Bring:

• Meaningful employment experience working on commercial software products
• Experience writing production code in Python, preferably dealing with large datasets
• Demonstrated experience or academic output in a relevant domain:
• Geospatial Data Processing
• Computer Vision
• AI & Machine Learning
• LiDAR
• Robotics/Self-Driving/Autonomy
• General familiarity with relevant technologies:
• Linux, Docker, and GitHub
• AI/ML frameworks (Tensorflow, Pytorch)
• Cloud platforms (Azure, AWS, Google)

Nice to Have:

• Familiarity with GIS applications like ESRI, QGIS, Google Earth
• Familiarity with orchestration frameworks like Kubernetes, AirFlow, MLFlow
• Programming experience in C++ or JavaScript
• Experience with Agile processes like Scrum

Benefits You Will Love

Certified as a Great Place to Work, Woolpert is one of the fastest-growing architecture, engineering, and geospatial companies in the world. With over 75 offices and countless projects around the globe, you’ll work on meaningful assignments that improve quality of life around the world. In addition to offering competitive pay, we provide employees with a robust set of unique benefits, including:

• Freedom to Work program: Set your own schedule and location (as appropriate).
• Principal program: Earn the opportunity to become an owner of the firm.
• Flexible paid time off/vacation: Take time off when it makes sense for you and your team.
• Career development: Explore a wide range of learning and growth opportunities within and across industries.
• Health, life, vision, and dental insurance: Cover all your medical bases.
• Paid sick time, retirement plan, fitness reimbursement, pet insurance, identity protection, technology stipend, employee assistance program, and more!

#LI-Hybrid

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

Company Description

Govini transforms Defense Acquisition from an outdated manual process to a software-driven strategic advantage for the United States. Our flagship product, Ark, supports Supply Chain, Science and Technology, Production, Sustainment, Logistics, and Modernization teams with AI-enabled Applications and best-in-class data to more rapidly imagine, develop, and field the capabilities we need. Today, the national security community and every branch of the military rely on Govini to enable faster and more informed Acquisition decisions.

Job Description

We are seeking an experienced Lead AI Engineer to lead our Agentic AI team as we scale our agentic offerings across all levels of the US government. Over the past year, we have seen the rapid adoption of our agent, Ace. We expect Ace to be handling much more complex tasks and workflows end-to-end and/or in cooperation with a human user as time goes on. The team is striving to make Ace an even more effective agent, focusing on planning, reliable execution over longer time horizon tasks, scaled tool use, Ace Skills, memory, and inter-agent coordination.

In order to do this job well, we are looking for someone who can demonstrate a project built on LLMs that showcases your skill at getting them to do complex tasks.

• Experience leading agentic system development from ideation through production, including technical design, architecture decisions, and day-to-day leadership of Data Scientists and Machine Learning Engineers
• Experience integrating and working with LLMs, with a strong understanding of their capabilities and limitations
• Experience integrating and working with agent frameworks like Claude Agent SDK or OpenAI Agent SDK
• Experience building observability, evaluation, and feedback loops for agent behavior (telemetry, prompt evaluation, regression testing, and reliability metrics).
• Experience working in highly ambiguous environments, and operating with urgency
• Lead Agile ceremonies and technical planning for the Agentic AI team

Strong Candidates have:

• Experience designing and deploying complex agentic systems using LLMs
• Hands-on work with multi-agent coordination, routing, and tool orchestration
• Passion for building autonomous and semi-autonomous systems that solve real customer problems

This role is a full-time position located out of our office in Pittsburgh, PA. 

This role may require up to 10% travel

Scope of Responsibilities 

• Designs and builds multi-agent systems with tool use, memory, routing, and planning
• Develops Agent Skills and tools as modular, composable services that interact with backend systems, models, and data processing
• Assist with automated evaluation of agents, skills, and prompts across the entire product lifecycle
• Work with our Product and Implementation organizations to find solutions to our most vexing challenges applying agents to our customer problems

Qualifications

• U.S. Citizenship is required

Required Skills:

• Bachelor's, Master’s, or Doctorate in Computer Science, Computer Engineering, Data Science, or a related field
• Minimum 3 years of experience building and deploying ML or LLM-powered systems in production environments
• Minimum 2  years of experience leading or mentoring engineering teams in production environments
• Practical experience in building, developing, and productionizing machine learning systems
• Advanced software skills in Python
• Experience with common LLM algorithms and implementations
• Hands-on experience with AWS and cloud infrastructure
• A strong desire to learn and investigate new technologies
• Familiarity with Git source control management
• Ability to work collaboratively with little supervision
• A burning desire to work in a challenging fast-paced tech environment

Desired Skills:

• Current possession of a U.S. security clearance, or the ability to obtain one with our sponsorship
• Experience in or exposure to the nuances of a startup or other entrepreneurial environment
• Experience with Claude Code and GenAI coding best practices.

We firmly believe that past performance is the best indicator of future performance.  If you thrive while building solutions to complex problems, are a self-starter, and are passionate about making an impact in global security, we’re eager to hear from you.

Govini is an Equal Opportunity Employer.  All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans status or any other characteristic protected by law.

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).

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 chose to bring your passion and skills to helping 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

We are seeking a highly skilled and experienced Senior Machine Learning Engineer to join our innovative team at TeleTracking Technologies, focusing on improving patient care. The ideal candidate will have a strong background in developing, deploying, and optimizing machine learning models, as well as expertise in data ingestion and modeling techniques. This role requires a deep understanding of hospital operations, healthcare data, clinical workflows, and regulatory requirements (such as HIPAA or GDPR). The successful candidate will be passionate about leveraging advanced technologies to enhance patient care and operational efficiency. 

What you will do

• Design, develop, and implement machine learning and deep learning models to address hospital-specific challenges such as patient flow optimization, resource allocation, bed management, and predictive analytics for patient outcomes.
• Build and optimize data ingestion and modeling pipelines as needed
• Utilize domain driven techniques and design patterns to build and contribute to technical
• design.
• Collaborate with cross-functional teams including data scientists, software engineers, clinicians, hospital administrators, and experts in TeleTracking Technologies to identify and develop high-impact machine learning solutions.
• Work with large-scale healthcare and hospital datasets including structured data (EHRs, hospital operational data), unstructured data (clinical notes, imaging).
• Ensure data privacy and security, adhering to healthcare regulations such as HIPAA and GDPR, especially when working with sensitive hospital data.
• Mentor junior engineers and data scientists, providing guidance on machine learning techniques, particularly those relevant to hospitals and healthcare systems.
• Monitor, troubleshoot, and enhance the performance of deployed models using MLOps best practices, ensuring they operate effectively in hospital environments.
• Write technical architectural and design documents.

What we look for

• Proven experience in end-to-end design and deployment of machine learning models from ideation to production in healthcare or similar settings.
• Strong programming skills and experience with object or component-oriented development software, one or more of: Python or R, with proficiency in ML frameworks, one or more of: TensorFlow, PyTorch, or Scikit-learn.
• Expertise in NLP, computer vision, or other specialized machine learning techniques applicable to healthcare and hospital environments.
• Deep knowledge of a scripting or statistical programming language (Python preferred). Ability to efficiently work with very large datasets and deal with non-standard machine learning datasets (class-imbalances, sparse matrices, etc.)
• Assess model performance; train multiple models; carry out tuning.  Run A/B tests on models.
• Comfortable writing complex SQL queries and developing python packages.
• Experience with cloud-based management and hosting, one or more of: AWS, Azure, GCS, CloudFormation, Terraform, or Ansible. Interest in developing services as well as the underlying infrastructure
• Experience with database management system software, one or more of: Oracle, MSSQL, MongoDB, MySQL, DynamoDB, or PostgreSQL. 
• Experience with Version Control Software, one or more of: git, Mercurial, CVS, TFS, or Subversion. 
• Strong understanding and experience executing several software development methodologies and life cycles. Ability to understand and translate business requirements into technical specifications.
• Experience with agile development practices.
• Excellent written and oral communication skills. Adept and presenting complex topics, influencing, and executing with timely / actionable follow-through.
• Strong analytical and problem-solving skills with the ability to convert information into practical training deliverables. Uses rigorous logic and methods to solve difficult problems.
• Knowledge of clinical workflows and hospital operations, and how technology can enhance efficiency and patient care.
• Familiarity with healthcare-specific machine learning challenges, such as data imbalance, longitudinal data, and real-time processing in hospital environments.
• Be an active listener, probe requirements for all projects from relevant stakeholders, stay nimble and willing to produce rapid iterations.

Education

• Bachelor's degree in computer science, Data Science, Machine Learning, Artificial Intelligence, or a related field; 7 or more years of experience.
• Master's or PhD in Computer Science, Data Science, Machine Learning, Artificial Intelligence, or a related field; 5 or more years of experience. (preferred)

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

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:

Motional is seeking a Senior Full Stack Engineer expert for its Web Visualization Tooling team.  This role will directly contribute through the creation of critical web tooling and visualization that allows us to improve our feedback loops for machine learning (ML) engineers and improving the performance and adaptability of our autonomous vehicle (AV) system.

Role Responsibilities:

• Own and expand backend implementation and architecture of our visualization tooling suite (e.g., data mining quality assurance, operations and log ingestion, annotation pipelines, telemetry viewers).
• Collaborate closely with ML, frontend, UX, data services, data mining, and data annotation teams to align tooling with real-world workflows
• Support scalable, performance APIs and services for visual development, debugging, and annotation systems.
• Help mature internal standards, observability, and deployment processes for our backend stack
• Maintain and mature the team’s CI/CD infrastructure and process.

Qualifications (required):

• Desire to design and build user-facing visual applications, and a passion for good UX.
• Strong proficiency in backend development with NodeJS and Python.
• Solid understanding and practical experience with AWS CDK in TypeScript.
• Ability to own and expand backend implementation and architecture of visualization tooling suite.
• Proven ability to collaborate effectively with cross-functional teams in diverse and highly technical domains of expertise.
• Experience in supporting scalable, high-performance APIs and services for visual development, debugging, and annotation systems.
• Ability to help mature internal standards, observability, and deployment processes for backend stack.
• Experience in maintaining and maturing CI/CD infrastructure and processes.
• Ability to work autonomously and independently, and to drive development initiatives with little oversight. High aptitude for learning and organization skills.
• Great interpersonal skills and ability to mentor and (on occasion) delegate to other engineers at various levels of relative seniority.
• A well-established technical design and documentation habit

Preferred:

• Experience with full-stack and front-end development using NextJS and React.
• Demonstrated project management expertise / advanced hands-on understanding of project management agility and operational excellence.
• A love for the continuous delivery of value.

Nice to have:

• Knowledge of and experience with Golang
• UI/UX and product design experience.
• 3D Math and Linear Algebra fundamentals.
  
  

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 a capable and highly motivated Engineer for our Developer Platform team to enable rapid and safe software delivery by providing a unified, efficient and reliable platform for all developers at Motional. You will join a talented team of engineers that focuses on improving the engineering experience and developer productivity of teams in Motional by providing them with the necessary tools and processes. You will collaborate closely with teams across the organization to identify pain points and drive initiatives that empower teams to deliver on Motional’s mission.

Your main focus will be on our real-time data pipeline which enables our AVs to communicate with our cloud services such as Command Center, Over-The-Air update systems, and ride hailing partners integration.

This is a remote-first position based anywhere in the U.S. 

What you'll do:

• Design, build, document, test, and maintain network, compute, and storage infrastructure of our cloud platform for the AV fleet.
• Monitor, support, and resolve issues as they arise in production.
• Assist with high-level analysis, system design, and code reviews.
• Communicate with stakeholders and team leads to identify system requirements.

What you'll be working on:

• Observability systems, CI/CD pipelines for integrations with ride hailing partners like Uber and Lyft.
• Cost Optimizations, Performance Optimizations, Security Improvements of Cloud Systems.
• Automation, services and LLM-integrated bots to reduce developer toil.

What you bring:

• 2+ years of professional work experience as a Software Engineer/DevOps in designing and building distributed systems.
• Experience with Golang / Python.
• Experience with AWS (EC2, EKS, ECS, Lambda, VPC, S3, IAM, IOT).
• Knowledge of CI/CD tools (e.g. GitLab CI, Jenkins).
• Experience with Infrastructure as Code (Terraform).
• Comfortable taking projects from ideation through to completion, with strong communication and collaboration across multiple international teams.
• Comfortable working in a fast-paced, continuous delivery environment.

Bonus points for experience with:

• Working with a globally distributed team.
• Experience with serverless architectures, building systems using SQL and NoSQL databases.
• Experience with time-series databases and monitoring tools (Prometheus, VictoriaMetrics, Grafana, Redash).
• Experience with GenAI solutions (Q Developer/Business, Gemini).
• Experience in Site Reliability Engineering.
• Experience with error monitoring software (Sentry, Incident.io).

Mission Summary

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

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

What You'll Be Doing

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

What We're Looking For

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

Bonus Points (not required): 

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

Mission Summary:

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

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

What You'll Do:

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

What We're Looking For:

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

Bonus Points (Nice-to-Haves):

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

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

Mission Summary:

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

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

What You'll Do:

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

What We're Looking For:

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

Bonus Points (Nice-to-Haves):

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

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

Mission Summary:

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

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

What You'll Do:

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

What We're Looking For:

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

Bonus Points (Nice-to-Haves):

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

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

Mission Summary:

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

What you’ll be doing:

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

What we’re looking for:

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

Bonus Points (not required):

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

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

Mission Summary:

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:

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.

We are searching for a Staff Safety Data Scientist on the Safety Analysis team who is a technical leader and go-to expert for risk and safety guidance, leveraging deep expertise in data science to lead critical safety research. Your insights will drive the safety strategy and external safety communications, including the development of industry-leading, benchmark safety studies and frameworks. The role requires a strong background in risk and hazard assessment and exceptional communication and interpersonal skills. You will be responsible for applying advanced statistical analysis and probabilistic modeling to support the safety case, inform hardware and software decisions, and identify critical risk factors. You will collaborate with diverse stakeholders across engineering, operations, and product.

In This Role, You Will:

• Lead the development of novel quantitative data analytics using both proprietary (Aurora-logged, sensor, system, integration testing data) and publicly available data (CRSS, FARS, state-level information).
• Author and present technical analyses and findings to diverse internal and external audiences, including stakeholders, authoritative bodies, and industry forums.
• Design and automate data collection and analysis to support ongoing safety programs.
• Extract insights from historical system safety performance to develop leading indicators for future performance forecasting. Analyze safety data from operational vehicles, crash metrics, and near-miss incidents to inform safety strategies and decision-making.
• Develop statistical models and algorithms to predict potential risks and prevent incidents, improving the safety performance of autonomous systems.
• Model self-driving vehicle behaviors at the system and subsystem levels.
• Develop and maintain reports and expressions of baseline risk coverage and application in operations.
• Design and develop expressions of risk benchmarking from similar industries.
• Create dashboards and reports for communicating risk, ranking, and anomalies.
• Present safety research findings to senior leadership and recommend actionable improvements to safety protocols and operational systems.
• Mentor and lead junior team members, fostering their professional growth.

Required Qualifications

• Bachelor’s degree in Data Science, Statistics, Mathematics, Physics, Engineering, Computer Science, or equivalent applicable technical experience.
• 7+ years of progressive experience solving large-scale complex problems.
• Demonstrated experience in a safety related domain (e.g., transportation, aerospace, robotics, medical devices).
• Strong understanding of safety principles and risk assessment methodologies; with a proven track record of using data science techniques to solve safety challenges and mitigate risks in a dynamic environment.
• Deep command of statistical methods, probabilistic modeling, and performing rapid exploratory data analysis.
• Expertise in data science tools (e.g., Python, SQL, R), statistical modeling, machine learning, predictive analytics, and visualization software (e.g., Tableau, Power BI).
• Adept at querying, analyzing, and visualizing large datasets.
• Excellent communication and presentation skills, with the ability to convey complex information to various audiences.
• Strong leadership skills, with the ability to provide guidance and mentorship.
• Ability to work independently, as part of a cross-functional team, or as a project lead.

Desirable Qualifications

• Advanced degree in Statistics, Mathematics, Physics, Engineering, Computer Science, or equivalent applicable technical experience.
• Experience working in safety and risk, ideally complemented by a portfolio of publications, reports, or conference presentations.
• Familiarity with rapidly scaling operational environments.
• Proficient in working with advanced data transformation tools such as DBT.
• Skilled in building and deploying using Amazon Web Services (AWS) tools.
• Background in the Autonomous Vehicles, Aerospace, or Robotics domains.

The base salary range for this position is $171,000 - $247,000 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.

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.

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 Bench Infrastructure team is responsible for maintaining critical hardware test infrastructure services at Latitude. This infrastructure supports high-velocity code validation for hundreds of developers, on custom hardware for our next-generation automotive autonomy solution. We are seeking a talented Senior Software Engineer to join the team and ensure the test infrastructure is ready to support a significantly larger scale.

What you’ll do: 

• Design and implement software solutions to ensure the usability and supportability of hardware-in-the-loop test execution services
• Deliver streamlined tools which minimize friction for software engineers to build, test, and debug autonomy software
• Identify and resolve stability problems and security vulnerabilities across the entire stack, ensuring the platform remains resilient and secure as the hardware test infrastructure grows
• Leverage performance metrics to pinpoint and remove inefficiencies in test infrastructure logic and complex test runtimes
• Enhance the performance and reliability of test execution, ensuring scheduling logic balances both system throughput and urgent job prioritization
• Maintain performance analysis test logic, ensuring reliable execution and data-driven validation of software performance across diverse hardware configurations
• Act as a technical bridge between Autonomy Software Engineering, IT, and Operations to ensure cross-functional pain points are resolved with scalable technical solutions

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)
• Strong communication, problem solving, task prioritization and teamwork skills 
• Proficiency with Python programming language, navigating a large codebase, and ability to learn other languages or technologies as needed
• Proven track record of designing, developing, and deploying full-stack applications at scale a Kubernetes-orchestrated production environment
• Ability to diagnose and resolve intricate problems in distributed systems and mitigate technical debt
• Experience with Linux systems, networking, distributed filesystems, and databases using SQL and ORMs

Nice to have: 

• Experience with full stack technologies: React, TypeScript, Flask, Postgres, & ORMs 
• Experience with DevOps technologies: AWS, Kubernetes, Docker, Terraform, & Ansible
• Experience with Data Warehousing and Visualization: BigQuery, & Superset
• Experience building validation tools for heterogeneous hardware environments, including Linux-based edge devices, robotics, or ML-driven applications
• Experience with C++ & Bazel

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

Our Autonomy team works at the frontier of real-world robotics — building and deploying systems that navigate, perceive, and act in complex, uncontrolled warehouse environments. The team spans drone autonomy, perception, and MHE Vision, and operates across multiple active product lines with production deployments at customer sites. It's a small, senior group where individual contributions are immediately visible and where the hardest problems are also the most important ones.

About the Role

• Own Architecture: Align backend, frontend, platform, and infrastructure decisions into a coherent, enterprise-grade architecture
• Reflect Excellence: Replace "firefighting" with predictable execution. You will lead the effort to retire scalability and reliability debt, safely upgrade critical infrastructure, and reduce single-threaded dependencies
• Set Direction: Set the standard for engineering technical hygiene. You will drive high-level decisions on testing strategies, validation guardrails, and system design concerns that directly impact delivery speed and maintainability
• Evolve Systems: Modernize and scale existing production systems by applying database-level strategies (schema evolution, replication tradeoffs) and platform primitives (orchestration, runtime constraints) as architectural tools
• Mentor: Elevate the organization by establishing shared practices, aligning terminology, and mentoring senior talent across the engineering team
• Exhibit First-Principles Thinking: Establish a deep understanding of data systems, latency-sensitive services, and failure modes

What You'll Need

• Distributed Systems: Mastery of performance-sensitive REST APIs, caching strategies, and core distributed systems concepts
• Relational Data Systems: Expert-level PostgreSQL (upgrades, query tuning, replication tradeoffs, and schema evolution) and advanced SQL
• Cloud & Containers: Deep experience with Azure and/or AWS and production-grade Kubernetes/Docker
• Backend Development: Strong production experience in Node.js and/or Python
• Reliability & Security: Hands-on experience with Observability (logs, metrics, traces), CI/CD, SRE fundamentals (SLIs/SLOs), and security hygiene (IAM, secrets management)

Nice to Have

• Domain Expertise: Experience in logistics, warehouse systems, or robotics-adjacent platforms is a plus, but not required. We value your ability to apply sound architectural judgment to new problem spaces
• Future Scale: If you have operated at a slightly smaller scale but can reason clearly about "what breaks next" (e.g., multi-regional architectures or advanced data governance), we will help you bridge that gap
• Organizational Maturity: While we value experience driving org-wide standards, we don't expect perfection on day one. We look for the intent to elevate our shared practices as you build trust
• AI-Ready: At Gather, we are at the leading edge of both applied classical ML and next-gen LLM/VLM AI. Come prepared to work with the latest and greatest tooling

About the Company

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 Role

We’re looking for someone who is customer-focused, technically proficient, and proactive in enhancing IT processes. You should excel at clear communication with both technical and non-technical stakeholders, have robust expertise in IT systems (with a strong background in macOS), and thrive in fast-paced environments. You will be the first point of contact for troubleshooting hardware, software, and network issues. Your responsibilities include resolving support requests, coordinating with vendors for equipment procurement, repairs, and maintenance, and actively participating in process and systems improvement initiatives.

What you’ll do

• Collaborate with cross-functional teams to identify opportunities for improvement, support the creation and maintenance of repeatable workflows (such as onboarding and device imaging), and contribute innovative ideas.
• Work closely with cross-functional teams to ensure seamless employee experiences. Clearly articulate issues, potential solutions, and timelines to both technical and non-technical stakeholders.
• Serve as the primary point of contact for troubleshooting hardware, software, and network issues, ensuring prompt and reliable resolution of employee requests.
• Coordinate with vendors for procurement, repairs, and maintenance while managing hardware and software inventories to maintain secure, up-to-date, and standardized systems.
• Support basic cloud operations across environments such as Amazon Web Services and Microsoft Azure, including user access, troubleshooting connectivity issues, and assisting with environment visibility
• Partner with Engineering and Infrastructure teams to troubleshoot access, permissions, and resource-related issues within cloud environments
• Partner with Security and Engineering to ensure IT processes align with compliance requirements (ISO 27001, SOC 2), including maintaining accurate documentation and audit evidence
• Identify opportunities for process improvement and contribute to building repeatable, scalable workflows across onboarding, access management, and device provisioning

Requirements

• Strong technical expertise in macOS (with a working knowledge of Windows as a plus), identity and device management (e.g., Azure AD, Jamf, Intune), and enterprise collaboration tools like Google Workspace, Office 365, Slack, and Atlassian products.
• Excellent written and verbal communication skills, ensuring clarity and professionalism in both internal and external interactions.
• Experience with identity providers such as Okta or Microsoft Entra ID
• Familiarity with Apple Business Manager and automated device enrollment workflows
• Excel at troubleshooting and problem-solving within Mac and macOS environments, ensuring smooth operations for users.
• Have experience orchestrating all-hands events, managing the AV and technical aspects to ensure successful outcomes.
• A proactive approach to problem solving and continuous improvement.
• Exhibit precision and attention to detail in your work, consistently delivering high-quality results.
• Possess a customer-first mindset and the ability to clearly articulate technical details to diverse audiences.
• Are proactive in process improvement and vendor management.
• Exposure to security and compliance frameworks such as ISO 27001 or SOC 2 is a BIG plus.