ARKA Group L.P. (“ARKA”) is an advanced technologies company serving the U.S. military, intelligence community, and commercial space industry delivering next-generation solutions to support the national security space enterprise. Built on more than six decades of excellence, ARKA brings modern approaches and a culture of innovation to the challenges of today. Join the ARKA team to learn how Beyond Begins Here. Discover your next career opportunity now! Position Overview: Our AI Center of Excellence builds the next generation of Agentic AI products that autonomously reason, plan, and act on behalf of our customers.  To deliver these capabilities at scale, we need a platform engineering group that provides a robust, secure, and highly available MLOps foundation across both on premise clusters and AWS.  The team works closely with data scientists, product engineers, and SREs to turn experimental models into reliable services that power mission critical applications. In support of work/life balance, many positions are available for a flexible schedule within the pay period. Ask us about the opportunity for flex scheduling if that’s of interest to you. Why join us - Shape the end-to-end lifecycle of cutting-edge AI services—from model training to production inference. - Influence architecture decisions for a hybrid cloud environment that will serve thousands of concurrent agents. - Collaborate with world-class researchers and product teams while enjoying a strong engineering culture focused on automation, observability, and reliability. Responsibilities: - Design, implement, and operate a unified MLOps platform that supports both on-premise Kubernetes clusters and AWS. The platform should enable rapid onboarding of new Agentic AI services and provide consistent governance across environments. - Develop reusable CI/CD pipelines (GitLab CI) for model packaging, containerization, automated testing, canary releases, and rollbacks. - Build observability, monitoring, and alerting stacks (Prometheus, Grafana, OpenTelemetry, CloudWatch) to track inference latency, throughput, resource utilization, and data drift for real time and batch workloads. - Create self-service tooling (CLI, SDKs, UI dashboards) that allows data science and product teams to register models, define inference endpoints, and manage versioning without deep DevOps involvement. - Architect and maintain data pipelines that feed training data, model artifacts, and inference logs into a governed data lake (S3, on prem object store). - Collaborate with research and product engineers to translate experimental Agentic AI prototypes into production grade services, ensuring reproducibility, security, and compliance. - Drive performance optimization for inference workloads (GPU/CPU scaling, model quantization, batching strategies) - Champion best practices in security (IAM, network policies, secret management), cost efficiency, and disaster recovery for the hybrid infrastructure. - Mentor junior engineers and contribute to internal knowledge bases, upskilling, and review processes. Required Qualifications: - BS in computer science or related engineering field - 5+ years of experience building and operating production grade software infrastructure, preferably in a hybrid onprem / cloud environment - Deep expertise with Kubernetes (cluster provisioning, Helm, operators, custom resources) and container runtimes (Docker, OCI) - Hands on experience with AWS services (EKS, SageMaker, S3, IAM, CloudWatch, Step Functions) and the ability to bridge onprem resources with AWS via VPN/Direct Connect - Strong software engineering skills in Python and at least one compiled language (Go, Rust, or Java) for building platform components and SDKs - Proficiency with CI/CD and GitOps tooling (Argo CD, Flux, Gitlab, GitHub Actions, or similar) - Solid understanding of distributed systems (consensus, fault tolerance, load balancing) and experience tuning high throughput, low latency inference pipelines - Experience with data engineering frameworks (Airflow, Prefect, Kafka, Spark, Flink) and building robust, versioned data pipelines - Familiarity with observability stacks (Prometheus, Grafana, OpenTelemetry, ELK) and the ability to define meaningful SLIs/SLOs for AI services - Track record of collaborating with research or product teams to move prototypes to production, translating experimental code into maintainable services - Strong problem solving mindset, excellent written and verbal communication, and a passion for building scalable AI platforms Preferred Qualifications: - Working knowledge of Scrum and Agile software development methodology Location: Remote This is a remote position that will primarily be supporting our Aurora, CO and King of Prussia, PA locations. Due to contract requirements, the job has to be performed from a remote location in the United States. What We Offer: - Comprehensive medical/vision/dental insurance packages - Company contributions to qualified HSA accounts - 401k retirement plan with industry leading company contributions - 3 weeks of vacation accrual per year plus time off for sick leave and unscheduled life events - 13 paid holidays - Upfront tuition assistance for approved degree programs - Annual bonus program based on company and employee performance - Company paid life insurance, AD&D, Short-Term and Long-Term disability insurance - 4 weeks paid Parental Leave - Employee assistance program (EAP) EHS/Environmental Requirements: This job operates alongside a professional office environment. While performing the duties of this job, the employee routinely is required to use hands to keyboard, communicate, listen to, and interpret instructions and remain stationary for extended periods of the time. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions of the job. Applicants are invited to apply for a reasonable accommodation to perform the essential duties of the job. To apply, send a request to staffing@arka.org or contact 203-797-5000 and press 2 for Human Resources. ITC & Security Clearance Requirements: This position requires the incumbent to access export-controlled information. If you are not a U.S. Person, any offer is contingent upon the Company's ability to obtain a special license granting you access. This could take several months. You will not be able to begin employment until such license is obtained. Visa Restrictions: No visa sponsorship is available for this position. Pre-employment Screenings: Employment with any ARKA companies in the U.S. is contingent upon satisfactory completion of several pre-employment requirements to include a credit check, background check, and drug screen.

Logistics at full potential. At GXO, we’re constantly looking for talented individuals at all levels who can deliver the caliber of service our company requires. You know that a positive work environment creates happy employees, which boosts productivity and dedication. On our team, you’ll have the support to excel at work and the resources to build a career you can be proud of. We’re out to transform transportation logistics through technology, and our multimillion-dollar commitment to IT underscores its importance to our vision. As a Machine Learning Engineer, you will be responsible for designing, building, and maintaining scalable machine learning systems. You will work closely with data scientists, software engineers, and business stakeholders to deploy models into production, ensure system reliability, and optimize performance across GXO’s operations. Pay, benefits and more. We are eager to attract the best, so we offer competitive compensation and a generous benefits package, including full health insurance (medical, dental and vision), 401(k), life insurance, disability and more. What you’ll do on a typical day: - Design, develop, deploy, and maintain ML systems, microservices, and software components that enhance and support supply chain operations and technology. - Ensure software engineering, DevOps, and cybersecurity best practices in development and deployment, including CI/CD pipelines, source control, and secure coding standards. - Design and build, and/or collaborate with data engineering teams to develop data models, pipelines, and integration layers that support and feed ML solutions, ensuring scalability, reliability, and data quality. - Develop ML integration APIs and services using Python, SQL, and frameworks such as Flask and FastAPI with a focus on reliability, latency, and maintainability. - Build agile and portable ML solutions using containerization tools like Docker and Kubernetes. - Implement monitoring, alerting, and observability for ML services. - Collaborate with business and product stakeholders to understand use cases and educate teams on ML capabilities. - Work closely with IT teams (infrastructure, InfoSec, data engineering) to define internal requirements and ensure seamless integration. - Communicate effectively with leadership to secure resources, address issues, and provide project updates. - Take ownership of projects end-to-end with minimal supervision. - Mentor junior engineers on best practices in ML and software development through pair programming, code reviews, and architectural guidance. - Stay current on emerging ML and platform technologies and contribute to the organization’s ML roadmap. - Maintain high-quality technical documentation across systems, services, pipelines, and deployment workflows. What you need to succeed at GXO: At a minimum, you’ll need: - Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, Economics, Physics or another analytics-related field, or equivalent related work or military experience - 3–5 years of experience in software engineering, ML engineering, or data science, with at least 2 years focused on designing, building, and deploying scalable, production-grade machine learning systems. - Strong proficiency in cloud environments (GCP preferred; AWS and Azure acceptable). - Expertise in Python, APIs, SQL, system design, DevOps/MLOps, and familiarity with distributed systems. - Familiarity with common ML frameworks such as TensorFlow, scikit-learn, PyTorch, and related tooling. - Experience in monitoring, troubleshooting, and optimizing deployed solutions. - Strong analytical and problem-solving skills. - Strong understanding of all stages of the ML lifecycle. It’d be great if you also had: - Familiarity with logistics systems and supply chain systems (e.g., WMS, OMS, TMS). - Experience with Snowflake and its ecosystem. - Hands-on experience with GCP Vertex AI. - Experience with JavaScript and integrating ML outputs in user-facing applications. We engineer faster, smarter, leaner supply chains. GXO is a leading provider of cutting-edge supply chain solutions to the most successful companies in the world. We help our customers manage their goods most efficiently using our technology and services. Our greatest strength is our global team – energetic, innovative people of all experience levels and talents who make GXO a great place to work. We are proud to be an Equal Opportunity/Affirmative Action employer. Qualified applicants will receive consideration for employment without regard to race, sex, disability, veteran or other protected status. GXO adheres to CDC, OSHA and state and local requirements regarding COVID safety. All employees and visitors are expected to comply with GXO policies which are in place to safeguard our employees and customers. All applicants who receive a conditional offer of employment may be required to take and pass a pre-employment drug test. The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified. All employees may be required to perform duties outside of their normal responsibilities from time to time, as needed. Review GXO's candidate privacy statement here.

Role Description En tant qu’ingénieur·e en apprentissage automatique, II - Routes et voies, vous aiderez à développer les modèles de prochaine génération qui estiment les surfaces des routes ainsi que la géométrie et la topologie des voies au sein de la pile d’autonomie de Torc. Vous travaillerez étroitement avec les équipes de perception, de cartographie et de planification afin d’offrir des modèles de perception de voies de grande qualité et prêts pour la production, permettant une conduite autonome sécuritaire et fiable des camions. - Développer et entraîner la vision par ordinateur et les modèles d’apprentissage profond pour la détection des voies de la route à l’aide de données des capteurs monoculaires et multimodaux (caméras, LiDARs et radars). - Concevoir des modèles de surface des routes en 3D et de géométrie des voies dans l’espace BEV, et intégrer le tout au pipeline d’autonomie de Torc. - Analyser le rendement des modèles, identifier les « corner cases » et améliorer la robustesse dans diverses conditions environnementales et longue traîne. - Développer et optimiser des flux de travail de traitement des données à grande échelle, y compris les annotations, le pseudo-étiquetage et l’augmentation des données. - Mettre en œuvre des pipelines adaptatifs d’entraînement et d’évaluation pour les modèles de perception des voies. - Prendre la responsabilité du travail de déploiement afin d’optimiser les modèles pour l’exécution en temps réel sur le matériel de grade automobile. - Exploiter les cartes SD et HD connues afin d’améliorer l’exactitude et la stabilité de l’estimation des voies. - Contribuer aux discussions architecturales, aux révisions de modèles et aux efforts d’intégration au niveau système. Qualifications - Baccalauréat en informatique, robotique, génie électrique, apprentissage automatique ou autre domaine connexe avec au moins 4 ans d’expérience ou une maîtrise avec au moins 2 ans d’expérience. - Expérience pratique en développement de modèles d’AA pour les tâches de perception comme la détection de voies, la modélisation des surfaces de la route, la fusion de plusieurs caméras ou l’estimation de la géométrie connexe. - Grande compréhension de l’étalonnage de caméras, d’alignement de plusieurs capteurs et de projection entre les espaces d’images et BEV. - Compétences avec Python et PyTorch, avec de l’expérience en codage d’AA de qualité production. - Expérience en entraînement de modèles sur de grands ensembles de données et en utilisation d’environnements informatiques adaptatifs. - Compréhension des architectures d’AA pertinentes, comme les CNN, les transformateurs et les réseaux de perception sur les BEV. - Capacité à analyser les données métriques du rendement des modèles, déboguer les cas d’échec et itérer efficacement. - Capacité à travailler avec les équipes d’autonomie, de perception et d’ingénierie logicielle. Requirements - Expérience de travail spécifique à la perception de voies, aux réseaux BEV ou à l’estimation de topologie des routes. - Expérience en opérations de noyaux CUDA ou PyTorch sur mesure. - Familiarité avec les cartes SD, les pipelines de localisation ou les données antécédentes à base de cartes. - Expérience avec l’entraînement distribué ou les cadres de travail d’expérimentation à grande échelle (par ex., Ray). - Publications pour des conférences de premier ordre AA/VO (CVPR, ICCV, NeurIPS). Benefits - Un programme de rémunération concurrentiel incluant un volet de primes et des options d’achat d’actions. - Une couverture médicale, dentaire et de la vue pour les employés à temps plein. - Un régime d’épargne-retraite (REER) avec une contribution de l’employeur de 4 %. - Une subvention pour le transport en commun (uniquement dans la région de Montréal). - Une flexibilité des horaires et des vacances payées généreuses. - Des fermetures de bureau pendant les congés fériés à l’échelle de l’entreprise. - Une assurance-vie.

• Design, develop, and deploy advanced AI/ML solutions that power the next generation of financial technology. • Implement GenAI, agent-based systems, and sophisticated ML models to enhance our platform capabilities. • Own the Full AI Lifecycle: Design and implement robust data models that support AI/ML initiatives. • Collaborate with cross-functional teams to integrate AI/ML functionalities into our multi-product, multi-issuer platform. • Develop scalable machine learning pipelines and data processing workflows. • Build, test, and optimize AI models on various cloud platforms; AWS experience (including SageMaker and Bedrock) is a bonus. • Ensure robust deployment practices and maintain the performance and scalability of AI systems. • Architect and implement an Agentic Framework tailored specifically for the needs of Financial Advisors, enabling autonomous reasoning, planning, and execution across complex financial scenarios. • Develop and enhance OCR capabilities and integrate these with vector databases. • Champion MLOps best practices to streamline the continuous integration, delivery, and deployment of machine learning models. • Provide technical guidance and mentorship to team members.