{"schemaVersion":"jobsearcher.job.v1","id":"c7c4ef77e376799a79ae1907","url":"https://jobsearcher.com/jobs/c7c4ef77e376799a79ae1907","canonicalUrl":"https://jobsearcher.com/jobs/c7c4ef77e376799a79ae1907","title":"Engineer","description":"This is a U.S. based position. All of the programs we support require U.S. citizenship to be eligible for employment. All work must be conducted within the continental U.S.\n\nThis is a U.S. based position. All of the programs we support require U.S. citizenship to be eligible for employment. All work must be conducted within the continental U.S.\n\nWho we are:\nRaft (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.\n\nOur flagship AI platform, [R]AIMS (Raft AI Mission System), enables operators and engineers to rapidly build, deploy, evaluate, and govern AI-powered mission workflows across highly dynamic operational environments. We are expanding our AI/ML presence in Rome, NY to support our customers and are looking for a hands-on AI/ML Engineer to contribute directly to model development, evaluation, and operational AI delivery.\n\nAbout The Role:\nAs an Engineer embedded in Rome, NY, you will work directly on model development efforts while leveraging and extending [R]AIMS platform capabilities to accelerate experimentation, evaluation, deployment, and operational transition. This is a highly hands-on role for an engineer who wants to build real-world AI systems with direct mission impact.\n\nYou will work closely with platform engineers, AI leadership, and mission stakeholders to move models from experimentation through production. The work sits at the intersection of applied machine learning, model training and evaluation, AI platform engineering, and operational AI deployment. You will need to be comfortable operating across that full span: writing training pipelines one day, integrating a model into a containerized deployment the next, and briefing a technical stakeholder on evaluation results the day after that.\n\nWhat you’ll do:\n\nBuild and evaluate machine learning models for mission-relevant use cases working directly with government researchers and program stakeholders to understand requirements and translate them into executable technical solutions\n\nDevelop and maintain model training, fine-tuning, and benchmarking workflows that are reproducible, well-documented, and usable by teammates without hand-holding\n\nBuild and improve evaluation pipelines for repeatable, rigorous performance measurement across model architectures, datasets, and operational scenarios\n\nIntegrate models into production-ready [R]AIMS platform infrastructure, working with platform engineers to ensure deployments are containerized, observable, and operationally sustainable\n\nSupport experimentation across model architectures and datasets, maintaining clear records of results and surfacing actionable findings to AI leadership and mission stakeholders\n\nWhat we are looking for:\n\n3 to 6 years of hands‑on experience building and shipping production software or AI/ML systems\n\nStrong Python software engineering skills; writes clean, maintainable, production‑quality code rather than notebook‑only scripts\n\nDemonstrated experience developing and evaluating machine learning models, with a clear understanding of what makes an evaluation rigorous versus misleading\n\nHands‑on familiarity with modern ML frameworks such as PyTorch, TensorFlow, JAX, or Hugging Face\n\nExperience building and managing model training pipelines and experimentation workflows at a level beyond tutorial projects\n\nExperience working with distributed systems or cloud‑native environments; comfortable in infrastructure that isn’t fully managed for you\n\nStrong debugging instincts; able to diagnose failure modes in complex pipelines and explain findings clearly to both technical and non‑technical audiences\n\nAbility to work independently and manage workstreams without close supervision while staying well‑integrated with a distributed team\n\nStrong written and verbal communication skills; able to produce clear technical documentation, status updates, and evaluation summaries\n\nAbility to obtain Security+ certification within the first 90 days of employment\n\nS. citizenship required; ability to obtain and maintain a Top Secret/SCI clearance\n\nHighly Preferred:\n\nExperience fine‑tuning foundation models, LLMs, or multimodal models for specific domain tasks or constrained operational environments\n\nExperience designing or operating model evaluation frameworks and benchmarking pipelines at scale\n\nExperience with Kubernetes and containerized ML workloads, including deploying and debugging GPU‑enabled inference services\n\nExperience with distributed training or large‑scale inference systems\n\nFamiliarity with streaming or event‑driven architectures such as Kafka or Flink, particularly as they relate to real‑time model inputs or outputs\n\nExperience building secure, compliant AI systems for regulated or mission‑critical environments, including familiarity with RMF or IL requirements\n\nPrior defense, national security, or government R&D experience, particularly with AFRL or Air Force programs\n\nExperience working in prototype‑to‑production environments where research artifacts need to become operational systems\n\nActive Secret or Top Secret clearance strongly preferred\n\nWhat Success Looks Like:\n\nModels developed and evaluated at AFRL are delivered with clear, rigorous documentation of performance, limitations, and operational considerations— not handed off as black boxes\n\nEvaluation pipelines are repeatable and trusted by the broader team; results are reproducible and traceable\n\nModel integrations into [R]AIMS are clean, containerized, and maintainable by platform engineers without needing the original model developer in the loop\n\nAFRL stakeholders view Raft as a technically credible, reliable partner; your presence in Rome strengthens that relationship over time\n\nThe gap between experimentation and operational deployment shortens with each program cycle because of the infrastructure and workflows you helped build\n\nClearance Requirements:\n\nNo clearance required to start\n\nMust be eligible for and willing to obtain a Top Secret/SCI clearance; active clearance strongly preferred\n\nSalary Range: $170,000.00 - $220,000.00\nWork Type:\n\nHybrid in Rome, NY; candidates must be based in or willing to relocate to the Rome, NY area to support a hybrid schedule\n\nUp to 25% travel\n\nWhat we will offer you:\n\nHighly competitive salary\n\nFully covered healthcare, dental, and vision coverage\n\n401(k) and company match\n\nTake as you need PTO + 11 paid holidays\n\nEducation & training benefits\n\nGenerous Referral Bonuses\n\nAnd More!\n\nOur Vision Statement:\nWe bridge the gap between humans and data through radical transparency and our obsession with the mission.\n\nOur Customer Obsession:\nWe 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 into 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.\n\nHow do we get there?\nPublic‑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.\n\nRaft’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.\n\nWe’re an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.\n\n#J-18808-Ljbffr","company":"Socket","rawCompany":"socket","city":"Rome","state":"NY","isRemote":false,"isActive":true,"createdAt":"2026-08-03T03:10:26.857Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"17-2199.00","title":"Engineers, All Other","slug":"engineers-all-other"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Engineer","description":"This is a U.S. based position. All of the programs we support require U.S. citizenship to be eligible for employment. All work must be conducted within the continental U.S.\n\nThis is a U.S. based position. All of the programs we support require U.S. citizenship to be eligible for employment. All work must be conducted within the continental U.S.\n\nWho we are:\nRaft (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.\n\nOur flagship AI platform, [R]AIMS (Raft AI Mission System), enables operators and engineers to rapidly build, deploy, evaluate, and govern AI-powered mission workflows across highly dynamic operational environments. We are expanding our AI/ML presence in Rome, NY to support our customers and are looking for a hands-on AI/ML Engineer to contribute directly to model development, evaluation, and operational AI delivery.\n\nAbout The Role:\nAs an Engineer embedded in Rome, NY, you will work directly on model development efforts while leveraging and extending [R]AIMS platform capabilities to accelerate experimentation, evaluation, deployment, and operational transition. This is a highly hands-on role for an engineer who wants to build real-world AI systems with direct mission impact.\n\nYou will work closely with platform engineers, AI leadership, and mission stakeholders to move models from experimentation through production. The work sits at the intersection of applied machine learning, model training and evaluation, AI platform engineering, and operational AI deployment. You will need to be comfortable operating across that full span: writing training pipelines one day, integrating a model into a containerized deployment the next, and briefing a technical stakeholder on evaluation results the day after that.\n\nWhat you’ll do:\n\nBuild and evaluate machine learning models for mission-relevant use cases working directly with government researchers and program stakeholders to understand requirements and translate them into executable technical solutions\n\nDevelop and maintain model training, fine-tuning, and benchmarking workflows that are reproducible, well-documented, and usable by teammates without hand-holding\n\nBuild and improve evaluation pipelines for repeatable, rigorous performance measurement across model architectures, datasets, and operational scenarios\n\nIntegrate models into production-ready [R]AIMS platform infrastructure, working with platform engineers to ensure deployments are containerized, observable, and operationally sustainable\n\nSupport experimentation across model architectures and datasets, maintaining clear records of results and surfacing actionable findings to AI leadership and mission stakeholders\n\nWhat we are looking for:\n\n3 to 6 years of hands‑on experience building and shipping production software or AI/ML systems\n\nStrong Python software engineering skills; writes clean, maintainable, production‑quality code rather than notebook‑only scripts\n\nDemonstrated experience developing and evaluating machine learning models, with a clear understanding of what makes an evaluation rigorous versus misleading\n\nHands‑on familiarity with modern ML frameworks such as PyTorch, TensorFlow, JAX, or Hugging Face\n\nExperience building and managing model training pipelines and experimentation workflows at a level beyond tutorial projects\n\nExperience working with distributed systems or cloud‑native environments; comfortable in infrastructure that isn’t fully managed for you\n\nStrong debugging instincts; able to diagnose failure modes in complex pipelines and explain findings clearly to both technical and non‑technical audiences\n\nAbility to work independently and manage workstreams without close supervision while staying well‑integrated with a distributed team\n\nStrong written and verbal communication skills; able to produce clear technical documentation, status updates, and evaluation summaries\n\nAbility to obtain Security+ certification within the first 90 days of employment\n\nS. citizenship required; ability to obtain and maintain a Top Secret/SCI clearance\n\nHighly Preferred:\n\nExperience fine‑tuning foundation models, LLMs, or multimodal models for specific domain tasks or constrained operational environments\n\nExperience designing or operating model evaluation frameworks and benchmarking pipelines at scale\n\nExperience with Kubernetes and containerized ML workloads, including deploying and debugging GPU‑enabled inference services\n\nExperience with distributed training or large‑scale inference systems\n\nFamiliarity with streaming or event‑driven architectures such as Kafka or Flink, particularly as they relate to real‑time model inputs or outputs\n\nExperience building secure, compliant AI systems for regulated or mission‑critical environments, including familiarity with RMF or IL requirements\n\nPrior defense, national security, or government R&D experience, particularly with AFRL or Air Force programs\n\nExperience working in prototype‑to‑production environments where research artifacts need to become operational systems\n\nActive Secret or Top Secret clearance strongly preferred\n\nWhat Success Looks Like:\n\nModels developed and evaluated at AFRL are delivered with clear, rigorous documentation of performance, limitations, and operational considerations— not handed off as black boxes\n\nEvaluation pipelines are repeatable and trusted by the broader team; results are reproducible and traceable\n\nModel integrations into [R]AIMS are clean, containerized, and maintainable by platform engineers without needing the original model developer in the loop\n\nAFRL stakeholders view Raft as a technically credible, reliable partner; your presence in Rome strengthens that relationship over time\n\nThe gap between experimentation and operational deployment shortens with each program cycle because of the infrastructure and workflows you helped build\n\nClearance Requirements:\n\nNo clearance required to start\n\nMust be eligible for and willing to obtain a Top Secret/SCI clearance; active clearance strongly preferred\n\nSalary Range: $170,000.00 - $220,000.00\nWork Type:\n\nHybrid in Rome, NY; candidates must be based in or willing to relocate to the Rome, NY area to support a hybrid schedule\n\nUp to 25% travel\n\nWhat we will offer you:\n\nHighly competitive salary\n\nFully covered healthcare, dental, and vision coverage\n\n401(k) and company match\n\nTake as you need PTO + 11 paid holidays\n\nEducation & training benefits\n\nGenerous Referral Bonuses\n\nAnd More!\n\nOur Vision Statement:\nWe bridge the gap between humans and data through radical transparency and our obsession with the mission.\n\nOur Customer Obsession:\nWe 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 into 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.\n\nHow do we get there?\nPublic‑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.\n\nRaft’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.\n\nWe’re an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.\n\n#J-18808-Ljbffr","datePosted":"2026-08-03T03:10:26.857Z","dateModified":"2026-08-03T03:10:26.857Z","hiringOrganization":{"@type":"Organization","name":"Socket","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Rome","addressRegion":"NY","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"c7c4ef77e376799a79ae1907"},"url":"https://jobsearcher.com/jobs/c7c4ef77e376799a79ae1907"}}