About the role

Mission Leads are customer-facing owners of mission outcomes. You will lead engagements with government stakeholders to identify high-value mission problems, shape pilots and deployments, and turn demonstrated mission value into durable, funded programs.

This role blends mission credibility with strong execution and technical intuition. You will operate with high autonomy in ambiguous environments, translate mission needs into clear technical narratives, and coordinate across functional teams (Product, Engineering, Mission, Security, and Operations) to deliver and scale.

What you’ll do

• Lead mission engagements. Build trusted relationships with operational, technical, and leadership stakeholders to understand mission needs, constraints, and success criteria.
• Translate mission problems into plans. Turn mission needs into clear problem statements, requirements, milestones, and measurable outcomes.
• Shape pilots and pathways to scale. Define objectives, timelines, and adoption plans that convert early wins into sustained programs.
• Communicate the “why” and the “how.” Create crisp technical narratives that map our agent-based capabilities to mission requirements and operational constraints.
• Run the operating cadence. Lead weekly customer syncs, internal standups, executive updates/QBRs, action-item tracking, and risk reviews, as applicable.
• Coordinate cross-functional delivery. Partner closely with Product and Engineering to ensure mission context is reflected in scope, tradeoffs, and delivery plans.
• Navigate program realities. Help stakeholders work through requirements development, budgeting cycles, contracting pathways, and coordination across organizations.
• Enable adoption. Coordinate onboarding, training, and customer success so the customer can use and sustain the capability.
• Maintain durable account knowledge. Keep high-signal documentation in Notion: stakeholders, org charts, use cases, timelines, deliverables, decisions, and lessons learned.
• Support expansion. Identify adjacent use cases and partner with Account teams where applicable.

What we’re looking for

• 6+ years owning outcomes in complex customer environments (defense, intelligence, public sector, or similarly regulated domains)
• Demonstrated ability to lead cross-functionally without consistent guidance
• Strong written and verbal communication; able to synthesize ambiguity into clear plans and execution
• Ability to scope and articulate a solution credibly: connect mission problems to software capabilities and measurable outcomes
• Sufficient technical fluency to partner effectively with Product and Engineering and translate complex concepts into mission-relevant narratives
• Strong operational skills: planning, prioritization, stakeholder management, and follow-through

What we value

• Experience with deployments or fielding in secure/regulated environments (e.g., ATO/IL environments, classified workflows, compliance constraints)
• Experience navigating within programs (requirements, budgets, authorities, timelines, contracting pathways)
• Deep expertise in a specific mission or technical domain (e.g., cyber, information warfare, ISR, networks, operations, warfare systems/command and control)
• Experience running executive-level customer updates (QBRs, steering committees)

What we offer

The salary range for this position is $150,000 - $170,000 + equity. Within the range, individual pay is determined by experience, relevant education, and/or training.

• Health, dental, and vision insurance
• Remote friendly with WeWork access
• Unlimited PTO, shared downtime during the federal holiday calendar, and company-wide off time at the end of each year
• 401(k) match
• Lifestyle & wellbeing stipends
• Salary top-up during military reserve duty
• Fully paid parental leave
• Child and pet care reimbursement during travel

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

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

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

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

Overview

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

What You’ll Do

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

An Ideal Candidate Should Have

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

What we offer

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

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

Think you’re a good fit for this job? 

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

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

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

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

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. 

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 Senior DevOps Engineer at Striveworks, you will be challenged—and trusted—on day one to take ownership of specific product deployments by maintaining, optimizing, and enhancing our on-premises and cloud computing environments. You will play a crucial role in the successful deployment of our software solutions to clients. You will be responsible for executing technical aspects of implementation projects and for ensuring the seamless integration, customization, and configuration of our software. You will be responsible for maintaining Striveworks’ software deployments using Infrastructure-as-Code (IaC) methodologies. Your expertise will play a critical role for the company as we deploy new instances of Striveworks’ AI operations (AIOps) capabilities to customer infrastructure.

You are right for this opportunity if you value and possess technical expertise and you enjoy pushing the boundaries of your capabilities. 

Your day-to-day will include:

• Automating IaC to manage virtual machines and deploy containers, services, and other infrastructure; applying your expertise to deploy custom Kubernetes clusters in AWS, Azure, GCP, on-premises, or hybrid cloud environments
• Working with platform developers, other DevOps teammates, and customer-facing teams to define requirements and build solutions for customer use cases of the platform
• Software deployments to commercial and, later, unclassified, CUI, and classified Department of Defense (DOD) networks
• Incident response and initial triage of critical system faults

The Senior DevOps Engineer works on the DevOps team. You will be responsible for monitoring, automating, and improving software reliability, performance, and availability for various projects. You will also act as a liaison between platform developers and customer-facing teams, taking on operational tasks to ensure the efficient functioning of Striveworks’ solutions. You will work alongside a team of software engineers and data scientists to help them deploy and operate their work as functional products, learning from them so that building effective AI solutions becomes second nature. You might provide guidance and leadership to junior DevOps team members.

You will directly contribute to the success of mission-critical systems within national security and commercial clients. You will be expected to wear multiple hats and to step into vacuums where improvements are needed, and you will be given the breadth to explore new technologies and solutions. 

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:

• 6+ years of direct, hands-on experience in:
• Python and/or Golang programming or other general-purpose programming languages
• Microservice deployment in Kubernetes
• Diagnosing and resolving issues within containerized environments
• Helm Chart and Kustomizations development/deployment
• Automation and IaC (e.g., Terraform, Ansible)
• Cloud infrastructure (e.g., AWS, Azure, GCP, or OpenStack)
• Managing and troubleshooting Linux systems (e.g., RHEL, Ubuntu, CentOS)
• The ability to work cross functionally to define requirements and build solutions for customer use cases of the platform
• The ability to respond professionally and competently to incident reports and triage critical system faults in environments where customers are present
• Active Secret (or above) US security clearance
• Due to the nature of this role, candidates must have US citizenship

The Wish List

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

• Experience with DOD networking, tools, infrastructure, security requirements, and policies 
• Proficiency with US federal information system security policies, including Security Technical Implementation Guides (STIGs), NIST SP 800-171, NIST SP 800-53, CMMC, and ICD 503
• Experience with software deployments to on-premises and cloud-based unclassified, CUI, and classified networks within the DOD
• Experience with DevSecOps/DevOps and CI/CD for the administration and deployment of GPU-enabled servers
• Experience deploying or maintaining Cloud Native Computing Foundation (CNCF) projects
• Experience with network-attached storage (NAS) and storage area network (SAN) technologies
• Experience with Kubernetes and cloud-native applications and services in denied, disrupted, intermittent, and limited (DDIL) impact environments 

The anticipated base pay range for this position is $200,000 to $250,000/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.

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.

Scale AI is seeking a highly skilled and motivated Mission Software Engineer to join our dynamic Federal Engineering team. As a part of this team, you will play a critical role in supporting Scale’s government customers by scoping and developing onsite solutions. Our scalable, high-performance platform is the foundation for these customer solutions, and your expertise will be instrumental in designing and implementing systems that can handle interactions with existing customer systems to help our products integrate into existing customer workflows.   

You will:

• Work directly with customers to understand their problems and translate those into features in Scale’s platform.
• Be open to >50% travel or relocation to a key customer geographic location.
• Collaborate with cross-functional teams to define and execute the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments.
• Implement end-to-end data integrations, syncing customer’s data to Scale’s platform and back
• Deploy and maintain Scale software at customer sites
• Develop customer requested features and work closely with them to ensure that they win customer love.
• Build robust and reliable backend systems that can serve as standalone products, empowering customers to accelerate their own AI ambitions.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• This role will require an active TS/SCI security clearance or the ability to obtain a security clearance.

Ideally you have:

• Track record of success as a hybrid customer facing engineer, forward deployed software engineer, and ability to quickly adapt to different roles.
• Prior experience developing with Python and JavaScript, or other modern software languages. Familiarity with Node and React is a plus.
• Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus
• Linux experience: Understanding of shell scripting, operating systems, etc
• Networking experience: Understanding of networking technologies, configuration  (ports, protocols, etc) 
• Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles

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)

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.

Mattermost Federal | TS/SCI Environments

Mattermost Federal builds secure collaboration platforms used by U.S. defense, intelligence, and national security organizations operating in the most demanding environments in the world.

We are looking for Forward Deployed Engineers (FDEs) who want to solve real operational problems alongside mission teams. In this role you will work directly with operators, analysts, and engineers to deploy and build systems that are used every day in mission environments.

This is not a traditional engineering role. You will operate close to the mission, often inside classified environments, working through ambiguity and building solutions that have immediate operational impact.

The problems you will work on here are hard, ambiguous, and consequential.

What You’ll Do

Forward Deployed Engineers operate at the intersection of engineering, operations, and mission execution.

You will:

• Work directly with defense and intelligence organizations to understand operational problems
• Deploy and integrate Mattermost in classified and mission-critical environments
• Build plugins, integrations, and automations that enable operational workflows
• Prototype new capabilities quickly and iterate based on operator feedback
• Debug complex systems operating in constrained environments
• Help shape the evolution of the Mattermost platform based on mission needs

You will move between writing code, deploying infrastructure, and working directly with operators, often within the same week.

Travel is typically approximately one week per month onsite with customers.

Commitment to the Mission

Forward Deployed Engineers at Mattermost Federal are mission partners, not external vendors.

Our customers operate in environments where coordination and decision speed matter. FDEs work side-by-side with mission teams to deliver systems that improve operational outcomes.

We are looking for engineers who:

• Care deeply about supporting national security missions
• Take ownership of outcomes, not just code
• Are comfortable operating in classified environments
• Thrive when solving complex problems with limited information

AI-Forward Engineering

Mattermost Federal is aggressively adopting AI-enabled workflows across mission operations.

FDEs will be among the first engineers deploying and operationalizing AI capabilities in secure environments.

You will help build and deploy systems such as:

• AI agents that summarize operational channels and generate SITREPs
• AI-assisted mission timelines and decision logs
• Knowledge retrieval across operational history
• AI tools that help operators understand fast-moving mission data

We are looking for engineers who are excited about experimenting with AI capabilities while maintaining mission-grade security and reliability.

What We Look For

• Strong engineering ability (Go, Python, TypeScript, or similar)
• Comfort working across the full stack from infrastructure to applications
• Ability to solve open-ended technical problems
• Strong communication skills with both engineers and operators
• Willingness to travel ~1 week per month

Ideal Background

• Experience working with DoD, IC, or national security organizations
• Experience deploying systems in secure or classified environments
• Familiarity with Kubernetes, distributed systems, and APIs
• Experience building integrations or operational tooling

Security Requirements

• U.S. Citizenship required: For candidates residing in the U.S.: This role may require the ability to obtain and maintain a U.S. government security clearance in the future. As such, U.S. applicants must be U.S. citizens and eligible under applicable clearance requirements.  
• Active TS/SCI clearance preferred or ability to obtain one
• Applicants must meet eligibility requirements for access to export-controlled information as defined by U.S. export control laws, including EAR and ITAR. 

Why This Role Exists

The best software is built close to the problem.

Forward Deployed Engineers at Mattermost Federal work directly with the people using the systems we build. You will see problems firsthand, build solutions quickly, and deploy them into environments where reliability, security, and speed matter.

If you want to build systems used in real missions and work directly with the people who depend on them, this role is for you.

Mattermost takes a market-based approach to pay and pay may vary depending on your location. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.