Scale is a vital part of bringing AI-enabled technologies to the world, from autonomous driving to drones, robots, and large language models. For example, Scale works with the world's top self-driving car and robotics ML teams as well as the largest companies in the generative AI space. 

As our customer base is growing, you will be on the front lines of our field engineering efforts for our federal AI projects, having the opportunity to meaningfully impact millions of dollars in revenue by working closely with our largest public sector customers and ensuring that they become passionate, lifelong Scale customers.

Our Field Engineers ensure customers' experiences with Scale's technology are seamless and optimized to build a successful, long-term partnership. Field Engineers partner closely with Product, Engineering, and Operations to lead existing customers through building production-grade data pipelines. We do this by knowing our customer’s use-cases inside and out, and creating the tooling and documentation needed to scalably support their growth.

Field Engineers in general are experts on Scale's products and codebase, and have general technical knowledge on web development, using APIs, and working with large volumes of data. Field Engineers are strong relationship builders, great project managers, and always fun to work with. 

The ideal person is a software engineer generalist who enjoys working with clients directly, taking ambiguous requirements and issues, and quickly designing and building sustainable solutions in close collaboration with the Product and Engineering teams. This role is at the intersection of customer delivery, product, and engineering, giving you a breadth of experience and fully leveraging both sides of your brain. If this sounds like you, we invite you to apply!

You will:

• Implement end-to-end data integrations, syncing customer’s data to Scale’s platform and back
• Work closely with our customer’s engineering teams to optimize data pipelines, including providing input towards designing API endpoints and input/output schemas
• Design, develop and maintain playbooks, internal tools, Scale’s documentation and SDKs to quickly get customers set up for long-term success
• Partner with Software Engineers and Operations to remove any technical hurdles customers may face / Debug technical issues impacting delivery and own technical escalations coming from the customer
• Be accountable for the customer’s technical experience throughout their time with Scale
• Work with AEs and PMs to identify customer-specific feature requests
• Develop technical domain expertise in areas of Large Language Models, 2D Image Annotation, and working with API integrations
• Evangelize Scale and interact with customers at major events
• Have an active TS/SCI clearance

Ideally you'd have:

• Track record of success as a hybrid customer-facing engineer or similar function, wearing multiple hats along the way
• Prior technical hands-on experience working with clients in a pre or post-sales capacity to realize business goals
• Prior experience developing with Python and JavaScript, or other modern software languages
• Strong engineering background preferably in Computer Science, Mathematics, or other quantitative fields
• Strong project management and interpersonal skills
• Presentation skills with a high degree of technical credibility when speaking with executives and front-line engineers
• High level of comfort communicating effectively across internal and external organizations
• Intellectual curiosity, empathy, and ability to operate with high velocity

Nice to haves:

• Experience in AI
• Experience working in classified environments
• Previous experience as a technical go-to-market resource
• Understanding of DevSecOps principles, including secure software delivery, infrastructure as code, and continuous integration/deployment
• Hands-on knowledge of container orchestration with Kubernetes and experience with Helm charts for application deployment
• Experience automating infrastructure and configuration management using Ansible or similar tools

Scale AI is at the forefront of the AI revolution, helping the U.S. government unlock the potential of AI across national security missions. We’re building enterprise-grade generative AI solutions and delivering them into operational use cases that matter.

We’re hiring an engagement manager (EM) to lead and coordinate delivery of agentic workflows for a national security customer. As an EM on our public sector delivery team, you will own or support a large account plan, manage day-to-day execution for customers, and ensure an incredible customer experience. This role is ideal for someone who blends program leadership, customer relationship building, technical fluency, and contract awareness — and who thrives in fast-moving, ambiguous, and mission-driven environments.

You will:

• Manage customer relationships from the executive to the end user
• Work alongside customers to scope agentic workflow use cases that Scale’s engineering team will build and you will ultimately refine
• Lead a cross-functional project team to deliver on and exceed the customer's AI/ML objectives
• Lead with a “whatever-it-takes” mentality, proactively identifying customer needs and operator pain points to ensure customer success
• Oversee onboarding and successful implementation of customer accounts

Must haves:

• An active TS/SCI clearance
• 5+ years of work experience succeeding in stakeholder management or a customer-facing role delivering enterprise-scale applications / solutions
• A track record of structured, analytics-driven problem solving
• Excellent verbal and written communication skills
• Willingness to be onsite with customers in locations throughout the Oahu area 4 days per week and able to travel at least 25% of the time (as needed)

We have a diverse team with a variety of skill sets, many have:

• 10+ years of professional experience, often in a customer-facing technical program management role in industry or government
• Prior experience at an API technology company and / or managing technical customers using an API
• A technical degree in computer science, engineering, or related field
• Proficiency in Python, SQL or other programming languages
• Domain expertise in a relevant field (e.g. modeling and simulation, joint planning processes, intelligence workflows, etc)

Build, Deploy, and Maintain AI for an Unpredictable World

Striveworks helps organizations harness the power of artificial intelligence to solve real-world national security and business challenges by serving as the command center between data, models, and business outcomes. Founded by data scientists and engineers, Striveworks set out to make the journey from deployment to ongoing optimization simple and effective.

With Striveworks, organizations aren’t just deploying AI—they’re building systems that remain reliable, adaptable, and ready to scale in an unpredictable world. Mission-critical operations require models that perform where they’re deployed, scale as workloads grow, and adapt rapidly as AI capabilities advance. Striveworks meets these demands, increasing reliability and performance while lowering costs—and enabling confident, data-driven decision-making in dynamic environments.

The Role

The Field Program Manager (FPM) is a hands-on leader aligned to a US Army Division HQ who serves as Striveworks’ primary program leadership presence for the Next Generation Command and Control (NGC2) program. This is an “ownership” role, not a coordination role; you are the primary authority for delivery, customer relationships, and growth. The FPM collaborates across a small, cross-functional project team to drive execution against the program roadmap and is the person Striveworks leadership calls when something is at risk. This position is designed for someone who has experience in complex Army environments, who understands how Division-level decisions are actually made, and who is done watching technology fail to land because nobody owned the last mile.

At Striveworks, you are trusted to operate autonomously, step into vacuums, and advocate for the end user with technical specificity. Success is measured by presence and follow-through rather than slide decks. You will serve as the company’s voice in the room, translating customer friction points into actionable technical roadmaps while maintaining a persistent pulse on how capabilities are utilized in the field. We value proactive problem-solvers who can mitigate execution risks independently and ensure that mission-critical systems land effectively within the formation.

Day-to-day responsibilities:

• Own the relationship: Serve as the primary point of contact for all stakeholders, from end users to Division leadership, to build trust and ensure long-term retention
• Drive growth: Identify expansion opportunities within the formation and surface competitive threats or “win signals” to leadership with enough lead time to act
• Define success: Diagnose operational problems before the customer names them, ensuring that Striveworks’ capabilities are providing measurable value
• Bridge the technical gap: Translate field needs into specific, actionable inputs for the engineering team to ensure that product development matches mission reality
• Execute the roadmap: Synchronize technical delivery with contractual milestones, the customer’s operational calendar, and exercise cycles to ensure on-time execution
• Mitigate risk: Identify delivery obstacles early, and autonomously resolve execution issues—escalating them to leadership only with recommended courses of action, not problems

This position offers a fully remote work environment, or you can work hybrid/on site at our office in northwest Austin, TX. You will be expected to travel up to 25% of the time to our customer sites at Schofield Army Barracks in Oߵahu, Hawaiߵi.

The Right Fit

In addition to the specific skills and expertise detailed below, we are looking for individuals who share our values. Sharing a set of values allows us to move at the speed of trust. 

Collectively, we value a high-trust work environment where people respect each other and use candor kindly and constructively. We value work that intersects passion and perseverance, we geek out about the potential of our contributions, and we find joy in working hard on things that matter. Finally, we value taking ownership, having agency, and feeling individual responsibility for collective results.

Here’s what we’re looking for:

• Bachelor’s degree and 4–6+ years of experience with military operations at Division (2-star) level or higher 
• Demonstrated experience planning and directing the execution of complex, multi-stakeholder project activities; proven team leadership in high-accountability environments
• Track record of building and sustaining rapport and trust with senior military and civilian stakeholders across different organizational levels
• Strong written and verbal communication; able to operate credibly across Soldier-level and executive-level audiences in the same day
• Technical fluency to engage software engineers and data scientists as an informed, non-technical counterpart; the ability to translate customer needs to contractual requirements
• Active Secret (or above) US security clearance
• Due to the nature of this role, candidates must have US citizenship

The Wish List

We’re very interested in candidates who possess the above qualifications, and we appreciate and consider the addition of:

• Former Field Grade Officer or Senior NCO, or similar
• Direct experience implementing or integrating battlefield technology within Army formations; you’ve seen a capability succeed or fail at the unit level, and you know why it happened
• Familiarity with DOD IT, network, and communications infrastructure as an operational reality, not just a technical concept
• Working knowledge of agile software delivery practices; able to hold a technical team accountable to a cadence without micromanaging the engineering
• Meaningful exposure to machine learning/AI capabilities in operational or defense contexts—enough to recognize value, identify misuse, and advocate credibly for the customer
• Aptitude with customer success or account management functions within a defense technology vendor

The anticipated base pay range for this position is $145,000–$185,000/year. For candidates located in Hawaiߵi, the anticipated base pay range for this position is $175,000–$220,000/year. Striveworks’ total compensation package includes a competitive base salary, equity grants, and cash bonuses.

The Benefits

• Medical/dental/vision insurance
• Voluntary life, long-term disability, accident, and hospital indemnity insurance
• HSA and FSA (including dependent care FSA) plans 
• 401(k) plan
• Unlimited PTO
• Paid parental leave

Check us out on Built In!

Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks will not tolerate discrimination or harassment of any kind.

If you require assistance or a reasonable accommodation in the application process, please contact Operations at hr@striveworks.us.

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete an employment eligibility verification form upon hire.

Striveworks is a participating employer in the E-Verify program.

Who we are:

Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.

About the Role:

We are seeking a Platform Engineer with an active Top Secret/SCI clearance to play a pivotal role in automating and orchestrating our critical infrastructure. This position is ideal for a technical expert passionate about deploying, managing, and optimizing system infrastructures using the latest technologies in system automation, container orchestration, and open-source applications. You'll be based in San Diego, Ca or Oahu, Hi and work on projects vital to national security and technological advancement.

Key Responsibilities:

• Implement and manage system automation using Ansible and Puppet, ensuring efficient configuration across RHEL and Windows platforms
• Deploy and maintain Kubernetes clusters with RKE2 and Rancher, focusing on scalability, reliability, and security
• Manage a wide array of open-source applications (NiFi, Kafka, Zookeeper, MinIO, Keycloak, Longhorn, Grafana, Prometheus, Loki, Promtail, GitLab), enhancing our capabilities in data processing, storage, and monitoring
• Ensure the highest level of system performance and security across all platforms and technologies
• Collaborate with teams to understand project requirements, providing technical solutions that align with strategic goals
• Maintain comprehensive documentation on system configurations, deployments, and operational practices

Required Qualifications:

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related discipline
• 7+ years of hands-on experience managing enterprise Linux and Windows systems, including:
  • Configuration management with Ansible and Puppet
  • Kubernetes operations (RKE2 and Rancher preferred)
• Strong troubleshooting and problem-solving skills in complex, distributed environments
• Ability to communicate effectively across technical and non-technical stakeholders and work collaboratively within cross-functional teams

Preferred Skills:

• Master’s degree in Computer Science, IT, Engineering, or a related field
• Experience operating and supporting the following technologies in production environments:
  • NiFi, Kafka, Zookeeper, MinIO, Keycloak, Longhorn
  • Grafana, Prometheus, Loki, Promtail
  • GitLab and CI/CD pipelines
• Deep understanding of containerization and cloud-native architectures
• Demonstrated experience with system performance tuning, capacity planning, and reliability engineering

Clearance Requirements:

• Active Top Secret with ability to obtain and maintain SCI

Work Type:

• Onsite at Oahu, Hawaii
• May require up to 10% travel

Salary Range: $100,000 - $170,000

• The determination of compensation is predicated upon a candidate's comprehensive experience, demonstrated skill, and proven abilities

What we will offer you: 

• Highly competitive salary
• Fully covered healthcare, dental, and vision coverage
• 401(k) with company match
• Take as you need PTO + 14 paid holidays
• Generous Referral Bonuses
• And More!

Our Vision Statement: 

We bridge the gap between humans and data through radical transparency and our obsession with the mission. 

Our Customer Obsession: 

We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.

How do we get there? 

Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm. 

Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration. 

Your Rights: California residents have the right to request information about personal data collected and to request deletion, subject to certain exceptions. Note that employment-related information is subject to specific exemptions under CCPA. Contact Us: For questions about this notice or to exercise your privacy rights, contact: operations@teamraft.com or (703)570-4820.

Build, Deploy, and Maintain AI for an Unpredictable World

Striveworks helps organizations harness the power of artificial intelligence to solve real-world national security and business challenges by serving as the command center between data, models, and business outcomes. Founded by data scientists and engineers, Striveworks set out to make the journey from deployment to ongoing optimization simple and effective.

With Striveworks, organizations aren’t just deploying AI—they’re building systems that remain reliable, adaptable, and ready to scale in an unpredictable world. Mission-critical operations require models that perform where they’re deployed, scale as workloads grow, and adapt rapidly as AI capabilities advance. Striveworks meets these demands, increasing reliability and performance while lowering costs—and enabling confident, data-driven decision-making in dynamic environments.

The Role

The Embedded Operations Manager is Striveworks’ permanent, on-the-ground presence at a US Army Division HQ, accountable for the “last mile” of the NGC2 program. Partnered with the Field Program Manager and Technical Lead, you bridge the gap between high-level program intent and daily tactical execution. This role is designed for a mission-driven professional who thrives on proximity to the Soldier and understands that in an operational environment, presence and follow-through are the only currency that matters. You are the critical link that determines whether Striveworks is viewed as a vendor or a trusted partner.

Operating with high autonomy, you manage the ground-level logistics, readiness, and relationships that keep the program moving. An Embedded Operations Manager operates with autonomy, sound judgment, and an ownership mentality—not because someone is watching, but because the mission demands it. This role requires someone who can hold the ground professionally when the rest of the team is remote, who can read a room full of Soldiers and a room full of senior leaders with equal credibility, and who knows instinctively when to solve a problem and when to escalate one. As an operations manager, you take personal ownership of the mission. You are the program’s earliest warning system, ensuring that our software engineers and data scientists are perfectly synced with the unit’s operational reality.

Day-to-day responsibilities:

• Ensure operational readiness: Own the preparation and execution checklists for all exercise cycles and operations, avoiding preventable gaps in systems or facilities access
• Manage on-site logistics: Lead end-to-end ground logistics, including equipment accountability, teammate enablement, and local project team coordination
• Cultivate Soldier-level trust: Build deep, daily relationships across the formation to ensure that Striveworks’ capabilities are integrated into the unit’s actual workflow
• Act as an early warning system: Identify and surface customer friction points, sentiment shifts, and emerging requirements to leadership with enough lead time to act
• Resolve ground-level issues: Handle customer exceptions and satisfaction issues autonomously, escalating scope changes or senior commander demands to the Field Program Manager
• Coordinate field execution: Synchronize on-site team activities with the technical roadmap, ensuring ground-level progress alignment to operational requirements
• Maintain situational awareness: Provide continuous updates on delivery risks and blockers to ensure that program leadership is never surprised by conditions on the ground

This position offers a hybrid/on-site work environment at customer sites at Schofield Army Barracks in Oߵahu, Hawaiߵi. You will be expected to travel up to 15% of the time.

The Right Fit

In addition to the specific skills and expertise detailed below, we are looking for individuals who share our values. Sharing a set of values allows us to move at the speed of trust. 

Collectively, we value a high-trust work environment where people respect each other and use candor kindly and constructively. We value work that intersects passion and perseverance, we geek out about the potential of our contributions, and we find joy in working hard on things that matter. Finally, we value taking ownership, having agency, and feeling individual responsibility for collective results.

Here’s what we’re looking for:

• Bachelor’s degree or equivalent demonstrated experience and 3+ years of experience with military operations at brigade level or higher; someone who understands how formations operate, not just how they’re organized
• Demonstrated ability to operate autonomously in ambiguous, high-stakes environments; sound judgment about when to act and when to escalate
• Track record of building trust with Soldiers and senior leaders through presence and follow-through—not rank or slide decks
• Strong written and verbal communication across organizational levels; able to represent Striveworks credibly in any room at the formation
• Sufficient technical fluency to participate meaningfully in software delivery conversations without leading them
• Active Secret (or above) US security clearance
• Due to the nature of this role, candidates must have US citizenship

The Wish List

We’re very interested in candidates who possess the above qualifications, and we appreciate and consider the addition of:

• Direct experience with Army battlefield technology implementations at the unit level; you’ve watched a capability land well or fail badly, and you know the difference
• Familiarity with DOD IT, network, and communications infrastructure as an operator, not just an observer
• Experience with systems-account management, system access administration, or similar on-site enablement responsibilities in a DOD environment
• Prior experience in an embedded, liaison, or resident role with a defense technology vendor or program office
• Exposure to agile software delivery practices—enough to track a sprint, understand a backlog, and ask the right questions of a technical team
• Enough familiarity with machine learning/AI capabilities in operational contexts to explain basic value propositions to a skeptical Soldier

The anticipated base pay range for this position is $155,000–$180,000/year. Striveworks’ total compensation package includes a competitive base salary, equity grants, and cash bonuses.

The Benefits

• Medical/dental/vision insurance
• Voluntary life, long-term disability, accident, and hospital indemnity insurance
• HSA and FSA (including dependent care FSA) plans 
• 401(k) plan
• Unlimited PTO
• Paid parental leave

Check us out on Built In!

Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks will not tolerate discrimination or harassment of any kind.

If you require assistance or a reasonable accommodation in the application process, please contact Operations at hr@striveworks.us.

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete an employment eligibility verification form upon hire.

Striveworks is a participating employer in the E-Verify program.

Who we are:

Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.

We’re looking for an experienced Principal ML Ops Engineer to support our customers and join our passionate team of high-impact problem solvers.

About the role:

Raft is building mission-critical AI and data platforms for the Department of Defense (DoD). Our systems ingest and process massive volumes of real-time data from hundreds of sensors and operational sources, transform that data into usable intelligence, and deliver it to operators through mission applications and common operational pictures that support time-sensitive decision-making.

Our platform operates at scale, processing billions of events per day with low-latency data pipelines and cloud-native infrastructure. As Raft expands its AI capabilities, we are investing in a more mature end-to-end machine learning platform to support model development, evaluation, deployment, monitoring, and lifecycle management across both cloud and constrained operational environments.

In this role, you will help design, deploy, and mature Raft’s ML platform and MLOps infrastructure. You will work across Kubernetes-based deployment environments, GPU-enabled infrastructure, model serving systems, CI/CD pipelines, and secure production operations to enable rapid and reliable delivery of machine learning capabilities. This role is ideal for someone who understands both the infrastructure needed to run ML systems in production and the practical needs of ML engineers building and deploying models.

What you’ll do:

• Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems
• Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support
• Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters
• Support model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systems
• Build and maintain CI/CD workflows for ML services, model artifacts, and platform components
• Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment
• Improve observability, reliability, security, and maintainability across ML infrastructure and services
• Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads
• Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environments
• Support compliance-driven deployment practices and secure software supply chain requirements in defense environments
• Get hands-on with customers at the most forward-leaning places in the Department of War

What we are looking for:

• 7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles
• 5+ years of experience with Docker and Kubernetes in production environments
• 5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environments
• Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production
• Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams
• Practical experience deploying machine learning workloads on Kubernetes
• Experience managing clusters or workloads that use GPUs
• Strong understanding of Helm and Kubernetes deployment patterns
• Strong scripting or programming skills, preferably in Python
• Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows
• Strong troubleshooting, systems thinking, and communication skills
• Ability to work independently and collaboratively in a fast-moving environment
• Ability to obtain and maintain a Top Secret clearance
• Ability to obtain Security+ certification within the first 90 days of employment

Highly preferred:

• Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies
• Experience with secure and compliant deployment practices in regulated or government environments
• Experience with Kubernetes-based ML platforms such as Kubeflow
• Familiarity with service mesh technologies such as Istio
• Experience provisioning and debugging complex CI/CD systems
• Experience with infrastructure as code tools such as Terraform
• Familiarity with software supply chain security, container hardening, vulnerability management, and runtime scanning
• Experience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edge
• Background working with machine learning engineers on model training, evaluation, packaging, and release workflows
• Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system

What success looks like:

• You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in production
• ML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to use
• Model deployments become more secure, observable, and supportable across real-world mission environments
• The organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership

Clearance Requirements:

• Ability to obtain and maintain a Top Secret clearance 

Work Type: 

• Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLY
• May require up to 40% travel
  

Salary Range: $150,000.00 - $200,000.00

What we will offer you:

• Highly competitive salary
• Fully covered healthcare, dental, and vision coverage
• 401(k) and company match
• Take as you need PTO + 11 paid holidays
• Education & training benefits
• Annual budget for your tech/gadgets needs
• Monthly box of yummy snacks to eat while doing meaningful work
• Remote, hybrid, and flexible work options
• Team off-site in fun places!
• Generous Referral Bonuses
• And More!

Our Vision Statement: 

We bridge the gap between humans and data through radical transparency and our obsession with the mission. 

Our Customer Obsession: 

We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.

How do we get there? 

Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm. 

Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration. 

Who we are:

Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.

We’re looking for an experienced Principal ML Ops Engineer to support our customers and join our passionate team of high-impact problem solvers.

About the role:

Raft is building mission-critical AI and data platforms for the Department of Defense (DoD). Our systems ingest and process massive volumes of real-time data from hundreds of sensors and operational sources, transform that data into usable intelligence, and deliver it to operators through mission applications and common operational pictures that support time-sensitive decision-making.

Our platform operates at scale, processing billions of events per day with low-latency data pipelines and cloud-native infrastructure. As Raft expands its AI capabilities, we are investing in a more mature end-to-end machine learning platform to support model development, evaluation, deployment, monitoring, and lifecycle management across both cloud and constrained operational environments.

In this role, you will help design, deploy, and mature Raft’s ML platform and MLOps infrastructure. You will work across Kubernetes-based deployment environments, GPU-enabled infrastructure, model serving systems, CI/CD pipelines, and secure production operations to enable rapid and reliable delivery of machine learning capabilities. This role is ideal for someone who understands both the infrastructure needed to run ML systems in production and the practical needs of ML engineers building and deploying models.

What you’ll do:

• Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems
• Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support
• Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters
• Support model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systems
• Build and maintain CI/CD workflows for ML services, model artifacts, and platform components
• Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment
• Improve observability, reliability, security, and maintainability across ML infrastructure and services
• Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads
• Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environments
• Support compliance-driven deployment practices and secure software supply chain requirements in defense environments
• Get hands-on with customers at the most forward-leaning places in the Department of War

What we are looking for:

• 7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles
• 5+ years of experience with Docker and Kubernetes in production environments
• 5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environments
• Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production
• Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams
• Practical experience deploying machine learning workloads on Kubernetes
• Experience managing clusters or workloads that use GPUs
• Strong understanding of Helm and Kubernetes deployment patterns
• Strong scripting or programming skills, preferably in Python
• Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows
• Strong troubleshooting, systems thinking, and communication skills
• Ability to work independently and collaboratively in a fast-moving environment
• Ability to obtain and maintain a Top Secret clearance
• Ability to obtain Security+ certification within the first 90 days of employment

Highly preferred:

• Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies
• Experience with secure and compliant deployment practices in regulated or government environments
• Experience with Kubernetes-based ML platforms such as Kubeflow
• Familiarity with service mesh technologies such as Istio
• Experience provisioning and debugging complex CI/CD systems
• Experience with infrastructure as code tools such as Terraform
• Familiarity with software supply chain security, container hardening, vulnerability management, and runtime scanning
• Experience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edge
• Background working with machine learning engineers on model training, evaluation, packaging, and release workflows
• Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system

What success looks like:

• You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in production
• ML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to use
• Model deployments become more secure, observable, and supportable across real-world mission environments
• The organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership

Clearance Requirements:

• Ability to obtain and maintain a Top Secret clearance 

Work Type: 

• Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLY
• May require up to 40% travel
  

Salary Range: $150,000.00 - $200,000.00

What we will offer you:

• Highly competitive salary
• Fully covered healthcare, dental, and vision coverage
• 401(k) and company match
• Take as you need PTO + 11 paid holidays
• Education & training benefits
• Annual budget for your tech/gadgets needs
• Monthly box of yummy snacks to eat while doing meaningful work
• Remote, hybrid, and flexible work options
• Team off-site in fun places!
• Generous Referral Bonuses
• And More!

Our Vision Statement: 

We bridge the gap between humans and data through radical transparency and our obsession with the mission. 

Our Customer Obsession: 

We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.

How do we get there? 

Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm. 

Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration. 

Who we are:

Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.

We’re looking for an experienced Principal ML Ops Engineer to support our customers and join our passionate team of high-impact problem solvers.

About the role:

Raft is building mission-critical AI and data platforms for the Department of Defense (DoD). Our systems ingest and process massive volumes of real-time data from hundreds of sensors and operational sources, transform that data into usable intelligence, and deliver it to operators through mission applications and common operational pictures that support time-sensitive decision-making.

Our platform operates at scale, processing billions of events per day with low-latency data pipelines and cloud-native infrastructure. As Raft expands its AI capabilities, we are investing in a more mature end-to-end machine learning platform to support model development, evaluation, deployment, monitoring, and lifecycle management across both cloud and constrained operational environments.

In this role, you will help design, deploy, and mature Raft’s ML platform and MLOps infrastructure. You will work across Kubernetes-based deployment environments, GPU-enabled infrastructure, model serving systems, CI/CD pipelines, and secure production operations to enable rapid and reliable delivery of machine learning capabilities. This role is ideal for someone who understands both the infrastructure needed to run ML systems in production and the practical needs of ML engineers building and deploying models.

What you’ll do:

• Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems
• Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support
• Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters
• Support model serving and inference infrastructure for a range of ML use cases, including traditional ML, computer vision, speech/audio, and LLM-based systems
• Build and maintain CI/CD workflows for ML services, model artifacts, and platform components
• Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment
• Improve observability, reliability, security, and maintainability across ML infrastructure and services
• Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML workloads
• Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted deployment environments
• Support compliance-driven deployment practices and secure software supply chain requirements in defense environments
• Get hands-on with customers at the most forward-leaning places in the Department of War

What we are looking for:

• 7+ years of relevant hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related technical roles
• 5+ years of experience with Docker and Kubernetes in production environments
• 5+ years of experience supporting enterprise cloud infrastructure or applications in AWS, Azure, or similar environments
• Strong experience provisioning, operating, and troubleshooting Kubernetes clusters in production
• Experience building and maintaining machine learning platforms, infrastructure, or pipelines used by engineering or data science teams
• Practical experience deploying machine learning workloads on Kubernetes
• Experience managing clusters or workloads that use GPUs
• Strong understanding of Helm and Kubernetes deployment patterns
• Strong scripting or programming skills, preferably in Python
• Experience with modern software engineering practices including Git, CI/CD, DevOps, and Agile/Scrum workflows
• Strong troubleshooting, systems thinking, and communication skills
• Ability to work independently and collaboratively in a fast-moving environment
• Ability to obtain and maintain a Top Secret clearance
• Ability to obtain Security+ certification within the first 90 days of employment

Highly preferred:

• Experience with ML model serving and inference platforms such as Triton Inference Server, KServe, Ray Serve, vLLM, or similar technologies
• Experience with secure and compliant deployment practices in regulated or government environments
• Experience with Kubernetes-based ML platforms such as Kubeflow
• Familiarity with service mesh technologies such as Istio
• Experience provisioning and debugging complex CI/CD systems
• Experience with infrastructure as code tools such as Terraform
• Familiarity with software supply chain security, container hardening, vulnerability management, and runtime scanning
• Experience supporting ML systems across multiple deployment environments, including cloud, on-prem, and edge
• Background working with machine learning engineers on model training, evaluation, packaging, and release workflows
• Familiarity with storage and artifact systems used in ML platforms, such as S3-compatible object stores, registries, and metadata/catalog system

What success looks like:

• You help Raft stand up a more mature and repeatable ML platform for deploying and managing models in production
• ML engineers can move faster because deployment, serving, and platform workflows are clearer, more reliable, and easier to use
• Model deployments become more secure, observable, and supportable across real-world mission environments
• The organization gains stronger infrastructure for model lifecycle management, including deployment standards, runtime patterns, and platform ownership

Clearance Requirements:

• Ability to obtain and maintain a Top Secret clearance 

Work Type: 

• Remote in DMV; McLean, VA; Boston, MA; San Antonio, TX; Colorado Springs, CO; Tampa, FL; Honolulu, HI Locations ONLY
• May require up to 40% travel
  

Salary Range: $150,000.00 - $200,000.00

What we will offer you:

• Highly competitive salary
• Fully covered healthcare, dental, and vision coverage
• 401(k) and company match
• Take as you need PTO + 11 paid holidays
• Education & training benefits
• Annual budget for your tech/gadgets needs
• Monthly box of yummy snacks to eat while doing meaningful work
• Remote, hybrid, and flexible work options
• Team off-site in fun places!
• Generous Referral Bonuses
• And More!

Our Vision Statement: 

We bridge the gap between humans and data through radical transparency and our obsession with the mission. 

Our Customer Obsession: 

We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.

How do we get there? 

Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm. 

Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration. 

Who we are:

Raft (https://TeamRaft.com) is a customer-obsessed non-traditional defense tech company dedicated to empowering U.S. military and government agencies with cutting-edge AI/ML and data solutions. We are a leader in autonomous data fusion and Agentic AI, with a purposeful focus on Distributed Data Systems, Platforms at Scale, and Complex Application Development. With headquarters in McLean, VA, our range of clients includes innovative federal and public agencies leveraging design thinking, cutting-edge tech stack, and cloud-native ecosystem. We build digital solutions that impact the lives of millions of Americans.

About the Role:

We are seeking a Platform Engineer with an active Top Secret/SCI clearance to play a pivotal role in automating and orchestrating our critical infrastructure. This position is ideal for a technical expert passionate about deploying, managing, and optimizing system infrastructures using the latest technologies in system automation, container orchestration, and open-source applications. You'll be based in San Diego, Ca and work on projects vital to national security and technological advancement.

Key Responsibilities:

• Implement and manage system automation using Ansible and Puppet, ensuring efficient configuration across RHEL and Windows platforms
• Deploy and maintain Kubernetes clusters with RKE2 and Rancher, focusing on scalability, reliability, and security
• Manage a wide array of open-source applications (NiFi, Kafka, Zookeeper, MinIO, Keycloak, Longhorn, Grafana, Prometheus, Loki, Promtail, GitLab), enhancing our capabilities in data processing, storage, and monitoring
• Ensure the highest level of system performance and security across all platforms and technologies
• Collaborate with teams to understand project requirements, providing technical solutions that align with strategic goals
• Maintain comprehensive documentation on system configurations, deployments, and operational practices

Required Qualifications:

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related discipline
• 7+ years of hands-on experience managing enterprise Linux and Windows systems, including:
  • Configuration management with Ansible and Puppet
  • Kubernetes operations (RKE2 and Rancher preferred)
• Strong troubleshooting and problem-solving skills in complex, distributed environments
• Ability to communicate effectively across technical and non-technical stakeholders and work collaboratively within cross-functional teams

Preferred Skills:

• Master’s degree in Computer Science, IT, Engineering, or a related field
• Experience operating and supporting the following technologies in production environments:
  • NiFi, Kafka, Zookeeper, MinIO, Keycloak, Longhorn
  • Grafana, Prometheus, Loki, Promtail
  • GitLab and CI/CD pipelines
• Deep understanding of containerization and cloud-native architectures
• Demonstrated experience with system performance tuning, capacity planning, and reliability engineering

Clearance Requirements:

• Active Top Secret with ability to obtain and maintain SCI

Work Type:

• Onsite in San Diego, California
• May require up to 10% travel

Salary Range: $100,000 - $170,000

• The determination of compensation is predicated upon a candidate's comprehensive experience, demonstrated skill, and proven abilities

What we will offer you: 

• Highly competitive salary
• Fully covered healthcare, dental, and vision coverage
• 401(k) with company match
• Take as you need PTO + 14 paid holidays
• Generous Referral Bonuses
• And More!

Our Vision Statement: 

We bridge the gap between humans and data through radical transparency and our obsession with the mission. 

Our Customer Obsession: 

We will approach every deliverable like it's a product. We will adopt a customer-obsessed mentality. As we grow, and our footprint becomes larger, teams and employees will treat each other not only as teammates but customers. We must live the customer-obsessed mindset, always. This will help us scale and it will translate to the interactions that our Rafters have with their clients and other product teams that they integrate with. Our culture will enable our success and set us apart from other companies.

How do we get there? 

Public-sector modernization is critical for us to live in a better world. We, at Raft, want to innovate and solve complex problems. And, if we are successful, our generation and the ones that follow us will live in a delightful, efficient, and accessible world where out-of-box thinking, and collaboration is a norm. 

Raft’s core philosophy is Ubuntu: I Am, Because We are. We support our “nadi” by elevating the other Rafters. We work as a hyper collaborative team where each team member brings a unique perspective, adding value that did not exist before. People make Raft special. We celebrate each other and our cognitive and cultural diversity. We are devoted to our practice of innovation and collaboration. 

Your Rights: California residents have the right to request information about personal data collected and to request deletion, subject to certain exceptions. Note that employment-related information is subject to specific exemptions under CCPA. Contact Us: For questions about this notice or to exercise your privacy rights, contact: operations@teamraft.com or (703)570-4820.

Build, Deploy, and Maintain AI for an Unpredictable World

Striveworks helps organizations harness the power of artificial intelligence to solve real-world national security and business challenges by serving as the command center between data, models, and business outcomes. Founded by data scientists and engineers, Striveworks set out to make the journey from deployment to ongoing optimization simple and effective.

With Striveworks, organizations aren’t just deploying AI—they’re building systems that remain reliable, adaptable, and ready to scale in an unpredictable world. Mission-critical operations require models that perform where they’re deployed, scale as workloads grow, and adapt rapidly as AI capabilities advance. Striveworks meets these demands, increasing reliability and performance while lowering costs—and enabling confident, data-driven decision-making in dynamic environments.

The Role

As a Machine Learning Engineer at Striveworks, you’ll be challenged—and trusted—on day one to be a core contributor to both the customer-driven projects and the enduring products of the company. You will represent Striveworks as a technology builder on projects and solutions that leverage Chariot, our proprietary AI operations (AIOps) platform, and you will inform and contribute to future capabilities of that platform. You will inform, envision, and help extend Striveworks’ core software products. You will work alongside data scientists, software engineers, and DevOps engineers to transform machine learning models into operational capabilities.

You’re right for this opportunity if you value and possess technical expertise and enjoy pushing the boundaries of your own capabilities. You’re outcome driven and are passionate about applying both software engineering and data science to solve real-world problems. You know that building customer-centric solutions, communicating clearly, and capturing repeatable value into productized capabilities are all important. 

Your day-to-day will include:

• Developing machine learning pipelines and custom analytics that are applied to image, video, text, geospatial, time series, and structured data
• Orchestrating and automating complex data engineering and analytic pipelines
• Envisioning, specifying, and, at times, designing and implementing core product functionality
• Conducting mission-critical fieldwork in support of customers and other stakeholders

This position offers a hybrid/on-site work environment at customer sites at Schofield Barracks in Oߵahu, Hawaiߵi. You will be expected to travel up to 30% of the time, including some international travel.

The Right Fit

In addition to the specific skills and expertise detailed below, we are looking for individuals who share our values. Sharing a set of values allows us to move at the speed of trust. 

Collectively, we value a high-trust work environment where people respect each other and use candor kindly and constructively. We value work that intersects passion and perseverance, we geek out about the potential of our contributions, and we find joy in working hard on things that matter. Finally, we value taking ownership, having agency, and feeling individual responsibility for collective results.

Here’s what we’re looking for:

• BS degree in computer science, machine learning, or a related discipline and 2+ years of relevant experience 
• Experience contributing to data-centric systems (e.g., data engineering, data cleaning, ETL pipelines, machine learning, and other production analytics)
• Proficiency in software engineering fundamentals to include algorithms, data structures, design patterns, and at least one systems programming language (e.g., Go, Rust, C++, Java, Scala, etc.)
• Proficiency in Python and exposure to libraries like TensorFlow, PyTorch, and/or scikit-learn
• Exposure to modern software engineering tools and processes (Agile, version control, issue tracking, CI/CD, debugging, etc.)
• Active Secret (or above) US security clearance
• Due to the nature of this role, candidates must have US citizenship

The Wish List

We’re very interested in candidates who possess the above qualifications, and we appreciate and consider the addition of:

• Advanced degree (e.g., MS, MEng, PhD) in computer science, machine learning, data science, or a related discipline
• Excellence in Python and deep knowledge of libraries like TensorFlow, PyTorch, and/or scikit-learn
• Knowledge of relevant architectures and design patterns for client-server systems (e.g., asynchronous programming, REST, GraphQL, React, Vue, Angular)
• Experience implementing and deploying software into containerized or cloud environments (e.g., Docker, Kubernetes [K8s], cloud architectures)
• Experience with machine learning applied to imagery and/or video data
• Experience building agentic systems, agentic workflows, or AI agents
• Experience defining, scoping, planning, and delivering complex technical solutions
• Experience delivering technology solutions in secure government environments

The anticipated base pay range for this position is $175,000–$205,000/year. Striveworks’ total compensation package includes a competitive base salary, equity grants, and cash bonuses.

The Benefits

• Medical/dental/vision insurance
• Voluntary life, long-term disability, accident, and hospital indemnity insurance
• HSA and FSA (including dependent care FSA) plans 
• 401(k) plan
• Unlimited PTO
• Paid parental leave

Check us out on Built In!

Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks will not tolerate discrimination or harassment of any kind.

If you require assistance or a reasonable accommodation in the application process, please contact Operations at hr@striveworks.us.

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete an employment eligibility verification form upon hire.

Striveworks is a participating employer in the E-Verify program.

As a Forward Deployed Engineer at AFS, you will be responsible for helping our clients solve their most pressing challenges, from the battlefield to supply chains, benefits programs, and broader government operations. You will work as part of a small team of engineers, domain experts, and other Deployment Strategists to turn a client’s vision into reality by deploying Palantir software and building tailored solutions that make a measurable impact on their operations.

Day-to-Day Responsibilities

• Collaborative Teamwork: Partner with engineers, program managers, and domain specialists to conceive, architect, build, and maintain applications that meet AFS clients’ needs.
• Data Synthesis: Understand a client’s most critical objectives and synthesize disparate information into a cohesive vision and actionable roadmap, interpreting what the data signifies and outlining an impact-based plan to rapidly go from use case to prototype to scaled deployment.
• Rapid Iteration: Quickly iterate, build from scratch, and help transform clients' operations at uncommon speed. You won’t just deploy software—you’ll help reshape how entire organizations work by putting powerful tools in the hands of executives and real operators.
• Production-Grade Solutions: Develop production-grade solutions that make sense of the client’s data and process it through an actionable workflow that can help clients make better decisions.
• Collaboration: Collaborate with technical and non-technical colleagues to define solution requirements, iterate on the solution, and ship code.

What We Look For

• Client Success Obsession: A deep commitment to helping clients succeed, even beyond the original scope. You thrive on solving hard customer problems and take pride in delivering solutions that drive real value.
• Analytical & Problem-Solving Skills: Strong abilities in breaking down complex problems and constructing end-to-end solutions that work.
• Technical Proficiency: Proficiency in relevant programming languages (e.g., Python, TypeScript) and the ability to build applications that utilize large structured and unstructured datasets in production environments.
• Independent Ownership: Capability to work autonomously while owning outcomes, with support available but a desire to take the driver’s seat.
• Real-World Impact Delivery: A proven track record of delivering meaningful outcomes through software and analytical products.
• Collaborative Skills: Strong ability to collaborate with teammates and clients of varying technical proficiency, embedding with clients and joining their teams.
• Willingness to Travel: Flexibility to travel as needed for client implementation work.

In this role, you’ll iterate quickly, build from scratch, and help organizations transform their operations at uncommon speed. You won’t just deploy software—you’ll help reshape how entire organizations function by providing powerful tools to those who can drive change.

Here’s what you need:

• Palantir Foundry: Proven experience building data pipelines, managing datasets, and deploying applications within Foundry. Specifics required are as follows: 

  • Practical skills required to build and maintain production-grade data pipelines, data connections, and ontologies 
  • General knowledge of platform capabilities and specific applications within the Foundry suite that are useful for performing the job of data engineer 
  • Data pipeline development in Foundry
    
    • Develop transforms on structured (tabular) and unstructured datasets in Foundry 
    • Apply best practices when building data pipelines 
  • Data pipeline maintenance in Foundry 
    • Effectively investigate and fix common issues in data pipelines 
    • Contribute to logic changes and performance improvements to transform pipelines feeding mission critical workflows 
    • Familiarity with recommended support structures 
  • Data connection and integration in Foundry 
    • Familiarity with architecture and capabilities of Data Connection 
    • Set up sources and syncs ingesting tabular data or raw files from external systems to Foundry 
  • Ontology design and development in Foundry 
    • Provide data engineering context during ontology design and implement pipelines backing ontology objects and links based on application requirements 
• Bachelor’s degree in Computer Science or related field
• Demonstrated ability to build production-grade code that leverages both structured and unstructured datasets  
• Strong foundation in machine learning
• Strong programming skills with demonstrated proficiency in Python, Java, C++, TypeScript/ JavaScript, or similar
• Ability to travel, dependent on client and team

Bonus points if you have: 

• Experience building solutions with large language models
• Active government security clearance #LI-DataAI

#LI-DataAI

Build, Deploy, and Maintain AI for an Unpredictable World

Striveworks helps organizations harness the power of artificial intelligence to solve real-world national security and business challenges by serving as the command center between data, models, and business outcomes. Founded by data scientists and engineers, Striveworks set out to make the journey from deployment to ongoing optimization simple and effective.

With Striveworks, organizations aren’t just deploying AI—they’re building systems that remain reliable, adaptable, and ready to scale in an unpredictable world. Mission-critical operations require models that perform where they’re deployed, scale as workloads grow, and adapt rapidly as AI capabilities advance. Striveworks meets these demands, increasing reliability and performance while lowering costs—and enabling confident, data-driven decision-making in dynamic environments.

The Role

As a Data Scientist at Striveworks, you’ll be challenged—and trusted—on day one to be a core contributor to the projects, products, and direction of the company. You will represent Striveworks as a technology builder on projects and solutions that leverage Chariot, our proprietary AI operations (AIOps) platform, and you will inform and contribute to future capabilities of that platform. You will work as part of a team of data scientists, machine learning engineers, software engineers, and DevOps engineers to transform machine learning models into functional products.

You’re right for this opportunity if you value and possess technical expertise and enjoy pushing the boundaries of your own capabilities. You’re outcome driven and are passionate about applying both software and data science to solve real-world problems. You know that being customer focused, rigorous in approach, clear in communication, and able to identify repeatable value opportunities are all critical to success. You are able to sense the needs of the customer, identify evolving demands, and then synthesize that feedback into actionable suggestions for Striveworks’ product teams.

Your day-to-day will include:

• Developing and validating machine learning models and custom analytic algorithms that are applied to image, video, text, geospatial, time series, and structured data
• Implementing AI-based software solutions for cloud and edge environments
• Conducting mission-critical fieldwork in support of customers and other stakeholders

This position offers a hybrid/on-site work environment at customer sites at Schofield Barracks in Oߵahu, Hawaiߵi. You will be expected to travel up to 30% of the time, including some international travel.

The Right Fit

In addition to the specific skills and expertise detailed below, we are looking for individuals who share our values. Sharing a set of values allows us to move at the speed of trust. 

Collectively, we value a high-trust work environment where people respect each other and use candor kindly and constructively. We value work that intersects passion and perseverance, we geek out about the potential of our contributions, and we find joy in working hard on things that matter. Finally, we value taking ownership, having agency, and feeling individual responsibility for collective results.

Here’s what we’re looking for:

• BS degree in computer science, machine learning, mathematics, or a related discipline and 2+ years of relevant experience 
• Proficiency in machine learning and data science, and applying both to image and video data
• Proficiency in implementing and analyzing data structures and algorithms
• Proficiency in programming languages and libraries common to machine learning; excellence in Python is essential, as is knowledge of libraries like TensorFlow, PyTorch, and/or scikit-learn
• Exposure to software development life cycle and tools (e.g., Git, Agile) 
• Active Secret (or above) US security clearance
• Due to the nature of this role, candidates must have US citizenship

The Wish List

We’re very interested in candidates who possess the above qualifications, and we appreciate and consider the addition of:

• Advanced degree (e.g., MS, MEng, PhD) in computer science, machine learning, mathematics, or a related discipline
• Experience deploying machine learning and data science, and applying both to production environments
• Exposure to DevOps and Cloud infrastructure (e.g., Docker, Kubernetes, CI/CD, major cloud providers)
• Experience processing a variety of unstructured data types (e.g., imagery, full-motion video, text, acoustic, sonar, RF, geospatial, graphs, or telemetry signals)
• Experience building AI agents and agentic workflows
• Experience implementing ETL pipelines, data pipelines, and/or workflow automation
• Experience developing software in a compiled programming language (e.g., Go, Rust, C++, Java, etc.)
• Experience building full-stack applications (i.e., back end, front end, REST)
• Experience delivering technology solutions in secure government environments
• Experience working with federal, state, and/or local government customers

The anticipated base pay range for this position is $175,000–$205,000/year. Striveworks’ total compensation package includes a competitive base salary, equity grants, and cash bonuses.

The Benefits

• Medical/dental/vision insurance
• Voluntary life, long-term disability, accident, and hospital indemnity insurance
• HSA and FSA (including dependent care FSA) plans 
• 401(k) plan
• Unlimited PTO
• Paid parental leave

Check us out on Built In!

Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks will not tolerate discrimination or harassment of any kind.

If you require assistance or a reasonable accommodation in the application process, please contact Operations at hr@striveworks.us.

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete an employment eligibility verification form upon hire.

Striveworks is a participating employer in the E-Verify program.

What You’ll be Owning:

• We are actively searching for Data Scientists, located in Hawaii, to support our team. We have varying levels of Data Scientist roles, depending on years of experience and education.
• Performs tasks associated with Big Data Platform management, utilizes skills in programming languages, develops prototype algorithms as well as algorithm refinements, and supports data visualization and analytics.  

What You Must Have:

• Bachelor’s Degree with 3 years of relevant experience OR Associates degree with 5 years of relevant experience 
• Bachelor’s Degree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science, Operations Research, or Computer Science or a degree in a related field (Computer Information Systems, Engineering), a degree in the physical/hard sciences (e.g. physics, chemistry, biology, astronomy), or other science disciplines with a substantial computational component (i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning)  and/or computer science (e.g. algorithms, programming, , data structures, data mining, artificial intelligence).  College-level requirements, or upper-level math courses designated as elementary or basic do not count.  Note: A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university.
• Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g., Python)), statistical analysis (e.g., variability, sampling error, inference, hypothesis testing, EDA, application of linear models), data management (e.g., data cleaning and transformation), data mining, data modeling and assessment, artificial intelligence, and/or software engineering. Experience in more than one area is strongly preferred
• Active TS/SCI w/poly

What Would Be Nice to Have:

• Foundations: (Mathematical, Computational, Statistical) 2. Data Processing: (Data management and curation, data description and visualization, workflow, and reproducibility)
• Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations)
• Devise strategies for extracting meaning and value from large datasets. Make and communicate principled conclusions from data using elements of mathematics,
• Statistics, computer science, and application specific knowledge.
• Through analytic modeling, statistical analysis, programming, and/or another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent in data holdings.
• Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data. Effectively communicate complex technical information to non-technical audiences. Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly shifting, processing, storage and analytic capabilities and limitations.