27 jobs found

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Senior Security Engineer As a Senior Security Engineer, you will be a key contributor in establishing and maintaining robust cybersecurity for Waymo's innovative products and services. You will be responsible for evaluating system elements, defining comprehensive cybersecurity concepts, and performing threat analysis and risk assessments (TARA) in compliance with ISO/SAE 21434. You will define and manage security requirements, determine risk treatment approaches, and collaborate closely with engineering and safety teams throughout the product lifecycle to understand and mitigate practical security and safety implications. Your role will also involve ensuring continuous compliance with relevant standards across multiple projects. You will: Evaluate system elements and define item boundaries, considering their operational environments , and devise a comprehensive cybersecurity concept. Perform threat analysis and risk assessment (TARA) (e.g., Identify threats to assets, evaluate attack feasibility, impact rating, etc) in compliance with ISO/SAE 21434. Define and manage requirements and determine approaches for proper risk treatment for self-driving platform features that are based on TARA output. Work with Waymo engineering teams on understanding practical security risks, safety implications, and necessary mitigations, during the entire lifecycle of the product (e.g., concept, development, operation, and incident response) Partner with safety teams to evaluate safety impact and required interactions between standards defining cybersecurity and functional safety. Maintain compliance with standards during the entire lifecycle of multiple projects, and perform updates You have: Bachelor's degree in Electrical Engineering, Communications Engineering, Automotive Engineering, Computer Science, Physics or similar A thorough understanding of performing cybersecurity threat and risk assessments on technical designs and architectures of embedded systems or other computer systems. A solid understanding of cybersecurity fundamentals (e.g., secure communications,security technologies, etc) and their practical deployments The ability to create & negotiate targets and requirements with Waymo engineering teams. We prefer: At least 5 years experience in an security (or similar industry) role delivering software and/or hardware Thorough understanding of security best practices Experience writing security requirements for engineering teams Experience designing security features Experience working with ISO/SAE 21434 certification and/or UNR 155 type approval The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $204,000-$259,000 USD

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Waymo Onboard Infrastructure is responsible for low-level software and infrastructure on various components of the Waymo self-driving system. The team's scope covers everything from low-level system software to high-bandwidth data logging, IPC (low-latency and high-throughput), performance analysis, and full-system debugging. We work with the Hardware, Compute, Sensor, Perception, Behavior and Machine Learning teams to build the most performant and low-latency self-driving solution in the industry. We are seeking an experienced Android System Software Engineer to join our team in developing the In-Vehicle Infotainment (IVI) platform for our next-generation, in-house System-on-Chip (SOC). This role requires a strong foundation in low-level OS fundamentals, embedded software, and a proactive approach to validating and ensuring the hardware meets critical software performance requirements. In this role you will: System Bring-up & Integration: Implement and integrate low-level software, including bootloader configuration, device trees, and kernel porting during the initial hardware bring-up phase. OS/Kernel Development & Optimization: Customize, optimize, and debug the Linux Kernel and relevant parts of the Android Open Source Project (AOSP) for the partner SOC, ensuring robust and efficient operation. Hardware Abstraction Layer (HAL) Implementation: Develop and maintain reliable Vendor HALs to interface the unique in-house hardware IP (e.g., security modules, power management units, display controllers) with the Android framework. Performance Engineering: Drive system-level performance optimization, including boot time reduction, scheduling tuning, thermal management, and power efficiency based on the SOC's specific architecture. Ambiguity Resolution: Proactively manage and clarify technical requirements for features that are still actively being defined internally, rapidly documenting and stabilizing interfaces for the broader software team. At a minimum, we'd like you to have: Education: Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a closely related technical field. Minimum 3+ years of professional software development experience, with a focus on embedded systems, low-level Android, or OS development. Deep expertise in OS Fundamentals: Strong working knowledge of the Linux Kernel (e.g., device drivers, memory management, IPC, scheduling) and embedded operating systems concepts. Experience Interfacing with Hardware Teams: Proven ability to read hardware specifications (datasheets, block diagrams) and effectively communicate software requirements, providing constructive technical feedback on hardware design choices. Proficiency in C/C++ is essential, along with experience in scripting languages (Python/Shell) for tooling and automation. Solid understanding of Android System Development: Hands-on experience modifying, debugging, and building AOSP, including familiarity with Android HALs, Treble/VNDK, and system debugging tools. Adaptability and Initiative: Demonstrated ability to thrive in an environment where technical specifications are evolving, requiring proactive problem-solving and definition of solutions. It's preferred if you have: Direct experience developing or integrating systems using Android Automotive OS or Android for embedded/IVI environments. Experience with system security fundamentals, particularly implementing or debugging secure boot and trusted execution environments (TEEs). Experience with system-level virtualization technologies (e.g., KVM, hypervisors, secure separation) for embedded or automotive platforms. Experience with audio stacks (e.g., ALSA, Audio HAL, Android AudioFlinger) or visual/graphics stacks (e.g., SurfaceFlinger, V-sync, display pipelines). The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $204,000-$259,000 USD

Job Description Summary: Digital products play a central role in how we create value for customers, support the teams who serve them, and shape the consumer experience. Our product organization brings together small, empowered teams that move with clarity, speed, and purpose, enabling digital to be a meaningful source of advantage across Coca-Cola's North America Operating Unit. Our work spans customer journeys, service delivery, sales workflows, and the platforms that connect them. We are raising our standards for product craft and rebuilding the systems behind these experiences. As a Tech Lead specializing in Machine Learning and Data Engineering, you will lead the technical direction for end-to-end ML capabilities that ship as part of our product, while also ensuring the data foundations (events, pipelines, feature tables, and governance) are reliable and scalable. You'll partner with Product, Design, Data Science/Analytics, and platform teams to frame problems, define success metrics, and guide solutions from data modeling and feature engineering through model training, deployment, monitoring, and iteration. This is a hands-on leadership role for engineers who can set standards, unblock teams, and drive execution across the ML and data stack without formal people-management responsibilities. What You Will Work On: Build ML-powered data products that model transaction drivers and surface optimized actions as insights to be embedded within integrated internal and external digital experiences that shape how our beverage brands activate across retail, foodservice, and digital channels. The success of our products is tied directly to measurable transaction lift at the point of sale, a primary objective of the North America Operating Unit and The Coca-Cola Company as a whole. How We Work You'll be part of a dedicated, cross-functional team (Product, Design, Engineering) that is: Empowered to solve problems, not just build features Accountable for outcomes, not output Collaborative by default, from discovery through delivery Continuously learning, using data and customer insight to improve Key Responsibilities Technical direction for a product ML domain: problem framing, approach selection, evaluation strategy, and iteration Data and feature foundations: event/telemetry definitions, transformation logic, feature/label tables, and training/serving consistency Production ML systems: deployment patterns (batch/online), model performance/latency tradeoffs, and operational readiness Quality and reliability: data quality checks, model monitoring (drift/performance), alerting, and runbooks Engineering standards: design reviews, code review quality, documentation, and reusable patterns for ML + data workflows Mentorship and enablement: coaching engineers through complex work and unblocking delivery across teams Develop, Train & Evaluate Models Build baselines and iterate on model approaches appropriate to the product problem (e.g., gradient boosting, deep learning, ranking) Lead feature engineering with strong data discipline: define entities and joins, validate labels, and ensure training/serving consistency Run experiments and evaluate models using sound methodology (train/validation splits, cross-validation as appropriate, error analysis) Document findings and recommendations clearly for technical and non-technical audiences Deploy & Operate Models in Production Deploy models to production (batch and/or real-time) with attention to latency, reliability, and cost Implement monitoring for upstream data and feature freshness/quality, drift, and model performance; define alerting and response playbooks Automate repeatable training and evaluation workflows (versioning, reproducibility, and artifact tracking) Participate in incident response and post-incident reviews when model behavior impacts customers or operations Establish reusable patterns for feature pipelines (batch/stream), backfills, and schema evolution; raise the bar through design reviews Define and reinforce standards for data governance and responsible ML (PII handling, access controls, data contracts, bias/fairness considerations) Partner with platform teams on the data stack (warehouse/lakehouse, streaming, orchestration) and MLOps tooling (feature stores, training infrastructure, deployment, monitoring) What We're Looking For Applied ML fundamentals: Understands supervised learning, evaluation metrics, and common failure modes Strong programming skills: Comfortable in Python and writing production-quality code (testing, readability, performance) Data intuition: Able to analyze datasets with SQL and/or Python, spot issues, and reason about bias/leakage Product mindset: Cares about measurable impact, guardrails, and user experience-not just model metrics Cross-functional collaboration: Partners with Product, Data Science, and Engineering to ship and iterate on ML features MLOps + data platform fluency: Comfortable with deployment, monitoring, reproducibility, and the pipelines/warehouses/streams that feed models Key Qualifications 6+ years of experience in machine learning engineering, data engineering, or software engineering, including leading technical direction for ML/data systems Demonstrated ownership of model development and evaluation, including metric selection, error analysis, and experimentation discipline Strong engineering fundamentals in Python (and SQL) with production practices (testing, reviews, CI/CD); familiarity with ML frameworks (e.g., PyTorch/TensorFlow) and data tooling (e.g., Spark, dbt, Airflow/Dagster) is preferred Experience shipping and operating ML systems in production, including model monitoring, rollback/retraining strategies, and coordination with upstream data/feature pipelines Familiarity with data platforms (data warehouse/lakehouse concepts), and exposure to orchestration/ETL tools (e.g., Microsoft fabric, Airflow, dbt, Spark) Preferred Qualifications Experience building product ML systems such as personalization, recommendations, ranking, forecasting, or NLP Experience with experimentation and measurement (A/B testing, uplift/impact analysis, online guardrails) Experience with feature pipelines or feature stores, and patterns for training/serving consistency Experience designing and operating data pipelines that power ML (batch and streaming), with clear SLAs for freshness and quality Experience with lakehouse/warehouse modeling for analytics and ML (dimensional/event models, backfills, schema evolution, data contracts) Demonstrated tech lead behaviors: driving design reviews, setting standards, mentoring engineers, and aligning stakeholders on tradeoffs Experience with model and data observability (drift detection, performance monitoring, dashboards/alerting) Familiarity with responsible AI and data privacy considerations (PII handling, access controls, model risk) Experience with production infrastructure (e.g., Docker/Kubernetes) or workflow tooling (e.g., Airflow, Dagster) used to run ML jobs Familiarity with modern engineering practices (CI/CD, testing, observability) Education Bachelor's degree in Computer Science, Engineering, or a related field Equivalent practical experience is equally valued Who Thrives Here Enjoy leading through influence-turning ambiguous problems into clear ML + data plans and helping others execute Communicate clearly across Product, Data Science, Analytics, and Engineering-especially around definitions, tradeoffs, and risk Take pride in raising the bar: reliable models and data pipelines, strong documentation, and operational follow-through Who This Role Is Not For This role may not be the right fit if you: Want to focus only on research prototypes or only on data pipelines (instead of owning end-to-end product ML systems) Avoid leading through influence (design reviews, alignment, mentorship) and prefer not to set or uphold technical standards Prefer to avoid operational responsibility for model and data health (monitoring, incidents, data quality/freshness, and continuous improvement) The Coca-Cola Company will not offer sponsorship for employment status (including, but not limited to, H1-B visa status and other employment-based nonimmigrant visas) for this position. Accordingly, all applicants must be currently authorized to work in the United States on a full-time basis and must not require The Coca-Cola Company's sponsorship to continue to work legally in the United States. Skills: Agile Methodology, Atlassian JIRA, Business Processes, Business Process Modeling, Cloud Platform, Communication, Data Flow Diagram, DevOps, Digital Transformation, Enterprise Architecture Framework, Enterprise Content Management (ECM), Java (Programming Language) . click apply for full job details

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver -to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. The Team & Mission: In the Oracle Perception team, our mission is to build the ultimate cognitive engine for autonomous driving. We are pioneering the use of large multimodal foundation models (e.g., Gemini) to build a powerful offboard reasoning and data flywheel system. We are moving beyond traditional perception to true scene understanding and driving actions-building offboard models that can comprehend complex driving problems, predict object/scene dynamics, and deduce driving paths with logical rationale. Our core focus is advancing the VLM foundation itself. By pushing the boundaries of multimodal pre-training and state-of-the-art post-training (SFT, RL) , we are creating models capable of rich, reasoning-based autolabeling at a massive scale. This closed-loop data engine directly powers the training and evolution of Waymo's real-time onboard models. If you are passionate about defining VLM training recipes, scaling laws, and unlocking complex reasoning via RL, this is your opportunity to redefine the foundation of autonomous driving. In this hybrid role, you will report to a Senior Staff Technical Lead Manager. You Will: Drive Pre-training & Domain Adaptation: Lead the technical strategy for curating and constructing massive-scale, high-quality multimodal pre-training datasets. Define data mixture strategies to instill deep, Waymo-specific driving intuition and physics-grounded understanding into foundation models without catastrophic forgetting. Lead Post-Training & Reasoning Enhancement: Design and implement state-of-the-art fine-tuning (SFT) and Reinforcement Learning (RLHF/RLAIF, DPO/GRPO/PPO) pipelines. Drastically improve the model's instruction-following and complex reasoning capabilities (e.g., Chain-of-Thought, spatial-temporal reasoning, and driving rationale prediction). Pioneer the VLM Data Flywheel: Architect the highly scalable inference and evaluation pipelines that leverage these trained Gemini-class models to autonomously source, sample, and autolabel critical edge cases, directly accelerating the onboard perception models. Define Training Recipes & Scaling Laws: Conduct rigorous ablation studies to optimize model architectures, token budgets, and loss functions. Establish best practices for scaling multimodal training efficiently on large GPU/TPU clusters. Drive Cross-Functional AI Strategy: Act as the principal technical visionary across ML Infra, Perception, Behavior, and AI Foundation teams. Drive consensus on the data flywheel architecture and embed VLM reasoning capabilities seamlessly into the broader autonomous vehicle stack. Provide Staff-Level Technical Leadership: Own the long-term technical roadmap for foundation model development. Mentor senior engineers, lead rigorous design reviews, and establish standard-setting engineering practices from advanced prototyping to production deployment. You Have: Master's degree in Computer Science, AI, ML, or a related technical field. 8+ years of hands-on experience designing, training, and scaling deep learning models, with at least 3+ years focused deeply on training Large Language Models (LLMs) or Vision-Language Models (VLMs) . Proven expertise in the full lifecycle of Foundation Models: from pre-training data curation (interleaved formats, tokenization) and distributed training to advanced post-training techniques. Expert-level understanding of training infrastructure and distributed paradigms (e.g., FSDP, Megatron, JAX/Pax) required for training massive models reliably. Expert-level software engineering fundamentals using Python, PyTorch, or JAX, with a track record of building reliable, highly scalable ML systems. Proven ability to operate with high ambiguity, define technical roadmaps, and drive complex, multi-quarter technical initiatives across multiple teams in a fast-paced environment. We Prefer: PhD in Computer Science, Artificial Intelligence, or a related field. Strong publication record in top-tier AI venues (e.g., NeurIPS, ICML, ICLR, CVPR) focusing on foundation models, large-scale training, reinforcement learning, or reasoning. Deep experience with advanced Reinforcement Learning paradigms applied to language or vision tasks ( focusing on improving System 2 thinking, logical deduction, and model alignment ). Demonstrated experience in Data Engineering for Foundation Models at the scale of billions/trillions of tokens (e.g., deduplication, quality filtering, synthetic data generation). Familiarity with the systemic challenges of multimodal perception in robotics or autonomous driving (e.g., 3D scene understanding, trajectory prediction). A proven track record of Staff-level impact: influencing product direction, pioneering zero-to-one ML architectures, and multiplying team efficiency through technical leadership. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $251,000-$310,000 USD

Description: GXM is seeking a Senior Digital Engineer - MBSE & Data Science to support advanced defense and space-related mission programs focused on Command and Control (C2), mission systems integration, cloud modernization, data-driven decision support, and enterprise capability delivery. The selected candidate will combine Digital Engineering and Model-Based Systems Engineering (MBSE) with data science and analytics to develop and maintain authoritative digital representations of mission systems and their operational context. The role will connect mission threads, operational workflows, requirements, system architectures, interfaces, data flows, analytics, and technical baselines into a traceable digital engineering environment that supports integration, assessment, and decision-making across the system lifecycle. The candidate will use engineering models and mission data to characterize system dependencies, assess integration and operational performance, identify capability and data gaps, support technical trade studies, and evaluate analytic or AI/ML-enabled capabilities. As appropriate, the candidate will develop repeatable analysis workflows using Python, SQL, Jupyter, statistical methods, data visualization, and machine learning techniques to inform architecture and mission-engineering decisions. This role requires close collaboration with enterprise and solutions architects, systems engineers, software and data engineers, cybersecurity personnel, mission operators, and Government stakeholders to ensure engineering models, data relationships, analytic assumptions, and technical decisions are accurate, explainable, traceable, and aligned to mission outcomes. This position is onsite in Colorado Springs, CO. Hybrid flexibility may be available over time based on mission requirements, classified work requirements, program execution needs, and achievement of objectives. Responsibilities Develop, maintain, and govern MBSE models supporting mission systems, enterprise capabilities, operational architectures, and C2 integration using SysML and related digital engineering methods. Model mission threads, operational workflows, system functions, interfaces, dependencies, data exchanges, analytic services, and decision-support relationships to provide an integrated view of mission execution and system behavior. Establish and maintain digital-thread traceability from mission needs and operational use cases through requirements, architecture elements, interfaces, data sources, analytic functions, verification evidence, and mission outcomes. Develop and maintain data architecture artifacts, including logical and physical data flows, source-to-consumer mappings, data/interface relationships, schemas, metadata, data lineage, and provenance needed to support integration and analytics. Acquire, clean, transform, explore, and analyze structured and unstructured data to support engineering analysis, mission assessment, capability evaluation, and operational decision support. Apply statistical analysis, feature engineering, anomaly detection, classification, clustering, forecasting, or other machine learning techniques when appropriate; select methods based on mission need, data characteristics, and operational constraints rather than technology novelty. Evaluate analytic and AI/ML-enabled capabilities using mission-relevant measures of performance and effectiveness, including accuracy, precision/recall, latency, confidence, robustness, uncertainty, false-alarm rates, and operational utility as applicable. Support explainable and auditable AI/ML integration by maintaining traceability to source data, data transformations, model versions, analytic methods, assumptions, confidence measures, provenance, and operator actions. Assess data quality, completeness, consistency, timeliness, latency, availability, and fitness for use; identify data risks and recommend engineering or operational mitigations. Create clear technical visualizations, engineering views, analytic products, and decision-support artifacts that communicate system behavior, integration dependencies, data relationships, technical risks, and mission impact to technical and non-technical stakeholders. Support requirements engineering activities, including elicitation, decomposition, allocation, validation, verification planning, change impact analysis, and requirements-to-architecture traceability. Conduct model- and data-informed trade studies, sensitivity analyses, gap assessments, and technical evaluations to support architecture decisions, capability insertion, integration planning, and technical baseline management. Support development and management of technical baselines across hardware, software, data, infrastructure, cloud, security, and operational environments. Participate in architecture reviews, engineering working groups, technical assessments, model governance activities, configuration management, and design decisions; ensure digital engineering artifacts remain synchronized with implemented system changes. Collaborate with Agile and DevSecOps teams to integrate engineering models, requirements, data products, analytic prototypes, interfaces, and verification evidence into iterative capability releases. Requirements: Required Qualifications U.S. Citizen with an active TS/SCI security clearance and ability to maintain required access throughout employment. Bachelor's degree in Systems Engineering, Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, Operations Research, Information Systems, or a related technical or quantitative discipline. 5+ years of relevant experience in systems engineering, digital engineering, MBSE, mission engineering, data science, analytics, or architecture development, including demonstrated experience working across multiple disciplines. Hands-on experience with MBSE tools such as Cameo Systems Modeler/MagicDraw, Sparx Enterprise Architect, or comparable modeling platforms. Experience developing SysML-based architecture models, engineering artifacts, requirements relationships, interface definitions, system dependencies, and technical documentation. Demonstrated data analysis or data science experience using Python and SQL, including data manipulation, exploratory analysis, statistics, and visualization. Working knowledge of Python data-science libraries and analytic environments such as pandas, NumPy, SciPy, scikit-learn, Matplotlib/Plotly, Jupyter, or equivalent tools. Experience translating mission, operational, or engineering questions into measurable analytic approaches, identifying appropriate data, defining assumptions, and communicating limitations and results. Familiarity with data modeling, data pipelines, APIs/interfaces, structured and semi-structured data, metadata, data quality, lineage, and provenance concepts. Working knowledge of statistical methods and machine learning fundamentals, including model selection, validation, performance metrics, overfitting, uncertainty, and appropriate use of training/test data. Experience supporting requirements management, traceability, technical baseline development, configuration management, and engineering change assessment. Experience working within Agile, DevSecOps, or other iterative engineering and software-delivery environments. Strong analytical reasoning, problem-solving, technical writing, communication, and stakeholder-engagement skills. Desired Qualifications Experience supporting defense, space, intelligence, homeland defense, or multi-domain operational environments, particularly Command and Control (C2), Space Domain Awareness (SDA), mission systems, or enterprise modernization initiatives. Experience applying the DoD Digital Engineering Strategy, digital-thread concepts, mission engineering, DoDAF/UAF, or SysML-based architecture development in a DoD environment. Experience with Cameo Teamwork Cloud, model repositories, collaborative model governance, model validation, or integration of MBSE tools with requirements and lifecycle-management platforms. Experience developing or evaluating AI/ML-enabled data fusion, anomaly detection, predictive analytics, sensor/data correlation, decision-support analytics, or other operational analytics for mission environments. Experience with cloud-native or distributed data environments, data engineering platforms, containerized analytics, APIs, message/event data, or big-data technologies in secure environments. Familiarity with data engineering and MLOps concepts, including version control, reproducible pipelines, model/data versioning, test automation, monitoring, and deployment within DevSecOps environments. Master's degree in Systems Engineering, Data Science, Computer Science, Applied Mathematics, Statistics, Operations Research, or a related technical field. OCSMP, INCOSE ASEP/CSEP/ESEP, Cameo certification, cloud/data engineering certification, or recognized data science/AI certification. $130,000-$195,000 base salary + annual bonus eligibility + medical/dental/vision/STD/LTD/Life + 401(k) + PTO Equal Employment Opportunity / Legal Disclaimer GXM Technologies LLC is an Equal Opportunity Employer and participates in E-Verify to confirm employment eligibility. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy), sexual orientation, gender identity . click apply for full job details

Year Up United is a one-year or less, intensive job training program that provides young adults with in-classroom skill development, access to internships and/or job placement services, and personalized coaching and mentorship. Year Up United participants also receive an educational stipend. The program combines technical and professional training with access to internships and job placement support through our industry-leading talent placement firm YUPRO Placement. If you receive an internship, it may be at Harvard University, Wayfair, Salesforce, or Wellington Management among other leading organizations in the Greater Boston area. Are you eligible? You can apply to Year Up United if you are: - A high school graduate or GED recipient - Eligible to work in the U.S. - Available Monday-Friday throughout the duration of the program - Highly motivated to learn technical and professional skills - Have not obtained a Bachelor?s degree - You may be required to answer additional screening questions when applying What will you gain? Professional business and communication skills, interviewing and networking skills, resume building, ongoing support and guidance to help you launch your career. During the internship phase, Year Up United students earn an educational stipend of $525 per week. In-depth classes include: - Banking - Business Operations - IT Support - Financial Operations - Project Management - Network Security & Support - Customer Success Get the skills and opportunity you need to launch your professional career. 72% of Year Up United graduates are employed and/or enrolled in postsecondary education within 4 months of graduation. Employed graduates earn an average starting salary of fifty-five thousand dollars per year.

Year Up United is a one-year or less, intensive job training program that provides young adults with in-classroom skill development, access to internships and/or job placement services, and personalized coaching and mentorship. Year Up United participants also receive an educational stipend. The program combines technical and professional training with access to internships and job placement support through our industry-leading talent placement firm YUPRO Placement. If you receive an internship, it may be at Harvard University, Wayfair, Salesforce, or Wellington Management among other leading organizations in the Greater Boston area. Are you eligible? You can apply to Year Up United if you are: - A high school graduate or GED recipient - Eligible to work in the U.S. - Available Monday-Friday throughout the duration of the program - Highly motivated to learn technical and professional skills - Have not obtained a Bachelor?s degree - You may be required to answer additional screening questions when applying What will you gain? Professional business and communication skills, interviewing and networking skills, resume building, ongoing support and guidance to help you launch your career. During the internship phase, Year Up United students earn an educational stipend of $525 per week. In-depth classes include: - Banking - Business Operations - IT Support - Financial Operations - Project Management - Network Security & Support - Customer Success Get the skills and opportunity you need to launch your professional career. 72% of Year Up United graduates are employed and/or enrolled in postsecondary education within 4 months of graduation. Employed graduates earn an average starting salary of fifty-five thousand dollars per year.

Year Up United is a one-year or less, intensive job training program that provides young adults with in-classroom skill development, access to internships and/or job placement services, and personalized coaching and mentorship. Year Up United participants also receive an educational stipend. The program combines technical and professional training with access to internships and job placement support through our industry-leading talent placement firm YUPRO Placement. If you receive an internship, it may be at Harvard University, Wayfair, Salesforce, or Wellington Management among other leading organizations in the Greater Boston area. Are you eligible? You can apply to Year Up United if you are: - A high school graduate or GED recipient - Eligible to work in the U.S. - Available Monday-Friday throughout the duration of the program - Highly motivated to learn technical and professional skills - Have not obtained a Bachelor?s degree - You may be required to answer additional screening questions when applying What will you gain? Professional business and communication skills, interviewing and networking skills, resume building, ongoing support and guidance to help you launch your career. During the internship phase, Year Up United students earn an educational stipend of $525 per week. In-depth classes include: - Banking - Business Operations - IT Support - Financial Operations - Project Management - Network Security & Support - Customer Success Get the skills and opportunity you need to launch your professional career. 72% of Year Up United graduates are employed and/or enrolled in postsecondary education within 4 months of graduation. Employed graduates earn an average starting salary of fifty-five thousand dollars per year.

Year Up United is a one-year or less, intensive job training program that provides young adults with in-classroom skill development, access to internships and/or job placement services, and personalized coaching and mentorship. Year Up United participants also receive an educational stipend. The program combines technical and professional training with access to internships and job placement support through our industry-leading talent placement firm YUPRO Placement. If you receive an internship, it may be at Harvard University, Wayfair, Salesforce, or Wellington Management among other leading organizations in the Greater Boston area. Are you eligible? You can apply to Year Up United if you are: - A high school graduate or GED recipient - Eligible to work in the U.S. - Available Monday-Friday throughout the duration of the program - Highly motivated to learn technical and professional skills - Have not obtained a Bachelor?s degree - You may be required to answer additional screening questions when applying What will you gain? Professional business and communication skills, interviewing and networking skills, resume building, ongoing support and guidance to help you launch your career. During the internship phase, Year Up United students earn an educational stipend of $525 per week. In-depth classes include: - Banking - Business Operations - IT Support - Financial Operations - Project Management - Network Security & Support - Customer Success Get the skills and opportunity you need to launch your professional career. 72% of Year Up United graduates are employed and/or enrolled in postsecondary education within 4 months of graduation. Employed graduates earn an average starting salary of fifty-five thousand dollars per year.

Year Up United is a one-year or less, intensive job training program that provides young adults with in-classroom skill development, access to internships and/or job placement services, and personalized coaching and mentorship. Year Up United participants also receive an educational stipend. The program combines technical and professional training with access to internships and job placement support through our industry-leading talent placement firm YUPRO Placement. If you receive an internship, it may be at Harvard University, Wayfair, Salesforce, or Wellington Management among other leading organizations in the Greater Boston area. Are you eligible? You can apply to Year Up United if you are: - A high school graduate or GED recipient - Eligible to work in the U.S. - Available Monday-Friday throughout the duration of the program - Highly motivated to learn technical and professional skills - Have not obtained a Bachelor?s degree - You may be required to answer additional screening questions when applying What will you gain? Professional business and communication skills, interviewing and networking skills, resume building, ongoing support and guidance to help you launch your career. During the internship phase, Year Up United students earn an educational stipend of $525 per week. In-depth classes include: - Banking - Business Operations - IT Support - Financial Operations - Project Management - Network Security & Support - Customer Success Get the skills and opportunity you need to launch your professional career. 72% of Year Up United graduates are employed and/or enrolled in postsecondary education within 4 months of graduation. Employed graduates earn an average starting salary of fifty-five thousand dollars per year.

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. We build and support advanced memory products that power next generation systems across the industry. We work closely with design, validation, and customer teams, and we love solving technical challenges together! In this role, you'll be the technical connection between customers and engineering for our DRAM portfolio, including HBM, DDR, and GDDR. You'll guide product validation, improve quality, and help customers integrate memory into complex platforms. This is a great fit for someone who enjoys hands on debug, data driven problem solving, and cross functional collaboration. Responsibilities: Validate and characterize DRAM products on system platforms and next generation processors Analyze product, yield, and performance data to improve quality and reliability Support failure analysis and document corrective actions Develop application notes, design guidance, and technical training Assist customer integration efforts, including SI/PI, timing, and system bring up Minimum Qualifications: Bachelor's degree in Electrical Engineering, Computer Engineering, or related field Experience in product engineering, applications engineering, hardware validation, or system integration Understanding of memory technologies, system architecture, or platform validation Exposure to tools such as Python, Linux, or JMP Strong problem solving and communication skills Utilize AI Agents Preferred Qualifications: Experience with DDR4, DDR5, HBM, GDDR, or similar memory technologies Familiarity with lab equipment, electrical validation, or SI/PI fundamentals Master's degree in Electrical Engineering, Computer Engineering, or related field Experience supporting customer bring up or system level debug The US base salary range that Micron Technology estimates it could pay for this full-time position is: $177,000.00 - $302,000.00 a year Additional compensation may include benefits, bonuses and equity. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target base pay for new hire salaries of the position across all US locations. Within the range, individual pay is determined by work location and additional job-related factors, including knowledge, skills, experience, tenure and relevant education or training. The pay scale is subject to change depending on business needs. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. As a world leader in the semiconductor industry, Micron is dedicated to your personal wellbeing and professional growth. Micron benefits are designed to help you stay well, provide peace of mind and help you prepare for the future. We offer a choice of medical, dental and vision plans in all locations enabling team members to select the plans that best meet their family healthcare needs and budget. Micron also provides benefit programs that help protect your income if you are unable to work due to illness or injury, and paid family leave. Additionally, Micron benefits include a robust paid time-off program and paid holidays. For additional information regarding the Benefit programs available, please see the Benefits Guide posted on . Micron is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, citizenship status, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state, or local laws. To learn about your right to work click here. To learn more about Micron, please visit US Sites Only: To request assistance with the application process and/or for reasonable accommodations, please contact Micron's People Organization at or 1- (select option ) Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards. Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron. AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification. Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. We build and support advanced memory products that power next generation systems across the industry. We work closely with design, validation, and customer teams, and we love solving technical challenges together! In this role, you'll be the technical connection between customers and engineering for our DRAM portfolio, including HBM, DDR, and GDDR. You'll guide product validation, improve quality, and help customers integrate memory into complex platforms. This is a great fit for someone who enjoys hands on debug, data driven problem solving, and cross functional collaboration. Responsibilities: Validate and characterize DRAM products on system platforms and next generation processors Analyze product, yield, and performance data to improve quality and reliability Support failure analysis and document corrective actions Develop application notes, design guidance, and technical training Assist customer integration efforts, including SI/PI, timing, and system bring up Minimum Qualifications: Bachelor's degree in Electrical Engineering, Computer Engineering, or related field Experience in product engineering, applications engineering, hardware validation, or system integration Understanding of memory technologies, system architecture, or platform validation Exposure to tools such as Python, Linux, or JMP Strong problem solving and communication skills Utilize AI Agents Preferred Qualifications: Experience with DDR4, DDR5, HBM, GDDR, or similar memory technologies Familiarity with lab equipment, electrical validation, or SI/PI fundamentals Master's degree in Electrical Engineering, Computer Engineering, or related field Experience supporting customer bring up or system level debug The US base salary range that Micron Technology estimates it could pay for this full-time position is: $177,000.00 - $302,000.00 a year Additional compensation may include benefits, bonuses and equity. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target base pay for new hire salaries of the position across all US locations. Within the range, individual pay is determined by work location and additional job-related factors, including knowledge, skills, experience, tenure and relevant education or training. The pay scale is subject to change depending on business needs. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. As a world leader in the semiconductor industry, Micron is dedicated to your personal wellbeing and professional growth. Micron benefits are designed to help you stay well, provide peace of mind and help you prepare for the future. We offer a choice of medical, dental and vision plans in all locations enabling team members to select the plans that best meet their family healthcare needs and budget. Micron also provides benefit programs that help protect your income if you are unable to work due to illness or injury, and paid family leave. Additionally, Micron benefits include a robust paid time-off program and paid holidays. For additional information regarding the Benefit programs available, please see the Benefits Guide posted on . Micron is proud to be an equal opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, citizenship status, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state, or local laws. To learn about your right to work click here. To learn more about Micron, please visit US Sites Only: To request assistance with the application process and/or for reasonable accommodations, please contact Micron's People Organization at or 1- (select option ) Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards. Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron. AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification. Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.

Year Up United is a one-year or less, intensive job training program that provides young adults with in-classroom skill development, access to internships and/or job placement services, and personalized coaching and mentorship. Year Up United participants also receive an educational stipend. The program combines technical and professional training with access to internships and job placement support through our industry-leading talent placement firm YUPRO Placement. If you receive an internship, it may be at Citizens, Amica Mutual Insurance Company, Lifespan, or Fidelity, among other leading organizations in the Providence area. Are you eligible? You can apply to Year Up United if you are: - A high school graduate or GED recipient - Eligible to work in the U.S. - Available Monday-Friday throughout the duration of the program - Highly motivated to learn technical and professional skills - Have not obtained a Bachelors degree - You may be required to answer additional screening questions when applying What will you gain? Professional business and communication skills, interviewing and networking skills, resume building, ongoing support and guidance to help you launch your career. During the internship phase, Year Up United students earn an educational stipend of $525 per week. In-depth classes include: - Business Operations - IT Support - Financial Operations - Banking - Project Management - Customer Success Get the skills and opportunity you need to launch your professional career. 72% of Year Up United graduates are employed and/or enrolled in postsecondary education within 4 months of graduation. Employed graduates earn an average starting salary of fifty-five thousand dollars per year. Year Up United is a one-year or less, intensive job training program that provides young adults with in-classroom skill development, access to internships and/or job placement services, and personalized coaching and mentorship. Year Up United participants also receive an educational stipend. The program combines technical and professional training with access to internships and job placement support through our industry-leading talent placement firm YUPRO Placement. If you receive an internship, it may be at Citizens, Amica Mutual Insurance Company, Lifespan, or Fidelity, among other leading organizations in the Providence area. Are you eligible? You can apply to Year Up United if you are: - A high school graduate or GED recipient - Eligible to work in the U.S. - Available Monday-Friday throughout the duration of the program - Highly motivated to learn technical and professional skills - Have not obtained a Bachelors degree - You may be required to answer additional screening questions when applying What will you gain? Professional business and communication skills, interviewing and networking skills, resume building, ongoing support and guidance to help you launch your career. During the internship phase, Year Up United students earn an educational stipend of $525 per week. In-depth classes include: - Business Operations - IT Support - Financial Operations - Banking - Project Management - Customer Success Get the skills and opportunity you need to launch your professional career. 72% of Year Up United graduates are employed and/or enrolled in postsecondary education within 4 months of graduation. Employed graduates earn an average starting salary of fifty-five thousand dollars per year.

Description: GXM is seeking a Senior Digital Engineer - MBSE & Data Science to support advanced defense and space-related mission programs focused on Command and Control (C2), mission systems integration, cloud modernization, data-driven decision support, and enterprise capability delivery. The selected candidate will combine Digital Engineering and Model-Based Systems Engineering (MBSE) with data science and analytics to develop and maintain authoritative digital representations of mission systems and their operational context. The role will connect mission threads, operational workflows, requirements, system architectures, interfaces, data flows, analytics, and technical baselines into a traceable digital engineering environment that supports integration, assessment, and decision-making across the system lifecycle. The candidate will use engineering models and mission data to characterize system dependencies, assess integration and operational performance, identify capability and data gaps, support technical trade studies, and evaluate analytic or AI/ML-enabled capabilities. As appropriate, the candidate will develop repeatable analysis workflows using Python, SQL, Jupyter, statistical methods, data visualization, and machine learning techniques to inform architecture and mission-engineering decisions. This role requires close collaboration with enterprise and solutions architects, systems engineers, software and data engineers, cybersecurity personnel, mission operators, and Government stakeholders to ensure engineering models, data relationships, analytic assumptions, and technical decisions are accurate, explainable, traceable, and aligned to mission outcomes. This position is onsite in Colorado Springs, CO. Hybrid flexibility may be available over time based on mission requirements, classified work requirements, program execution needs, and achievement of objectives. Responsibilities Develop, maintain, and govern MBSE models supporting mission systems, enterprise capabilities, operational architectures, and C2 integration using SysML and related digital engineering methods. Model mission threads, operational workflows, system functions, interfaces, dependencies, data exchanges, analytic services, and decision-support relationships to provide an integrated view of mission execution and system behavior. Establish and maintain digital-thread traceability from mission needs and operational use cases through requirements, architecture elements, interfaces, data sources, analytic functions, verification evidence, and mission outcomes. Develop and maintain data architecture artifacts, including logical and physical data flows, source-to-consumer mappings, data/interface relationships, schemas, metadata, data lineage, and provenance needed to support integration and analytics. Acquire, clean, transform, explore, and analyze structured and unstructured data to support engineering analysis, mission assessment, capability evaluation, and operational decision support. Apply statistical analysis, feature engineering, anomaly detection, classification, clustering, forecasting, or other machine learning techniques when appropriate; select methods based on mission need, data characteristics, and operational constraints rather than technology novelty. Evaluate analytic and AI/ML-enabled capabilities using mission-relevant measures of performance and effectiveness, including accuracy, precision/recall, latency, confidence, robustness, uncertainty, false-alarm rates, and operational utility as applicable. Support explainable and auditable AI/ML integration by maintaining traceability to source data, data transformations, model versions, analytic methods, assumptions, confidence measures, provenance, and operator actions. Assess data quality, completeness, consistency, timeliness, latency, availability, and fitness for use; identify data risks and recommend engineering or operational mitigations. Create clear technical visualizations, engineering views, analytic products, and decision-support artifacts that communicate system behavior, integration dependencies, data relationships, technical risks, and mission impact to technical and non-technical stakeholders. Support requirements engineering activities, including elicitation, decomposition, allocation, validation, verification planning, change impact analysis, and requirements-to-architecture traceability. Conduct model- and data-informed trade studies, sensitivity analyses, gap assessments, and technical evaluations to support architecture decisions, capability insertion, integration planning, and technical baseline management. Support development and management of technical baselines across hardware, software, data, infrastructure, cloud, security, and operational environments. Participate in architecture reviews, engineering working groups, technical assessments, model governance activities, configuration management, and design decisions; ensure digital engineering artifacts remain synchronized with implemented system changes. Collaborate with Agile and DevSecOps teams to integrate engineering models, requirements, data products, analytic prototypes, interfaces, and verification evidence into iterative capability releases. Requirements: Required Qualifications U.S. Citizen with an active TS/SCI security clearance and ability to maintain required access throughout employment. Bachelor's degree in Systems Engineering, Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, Operations Research, Information Systems, or a related technical or quantitative discipline. 5+ years of relevant experience in systems engineering, digital engineering, MBSE, mission engineering, data science, analytics, or architecture development, including demonstrated experience working across multiple disciplines. Hands-on experience with MBSE tools such as Cameo Systems Modeler/MagicDraw, Sparx Enterprise Architect, or comparable modeling platforms. Experience developing SysML-based architecture models, engineering artifacts, requirements relationships, interface definitions, system dependencies, and technical documentation. Demonstrated data analysis or data science experience using Python and SQL, including data manipulation, exploratory analysis, statistics, and visualization. Working knowledge of Python data-science libraries and analytic environments such as pandas, NumPy, SciPy, scikit-learn, Matplotlib/Plotly, Jupyter, or equivalent tools. Experience translating mission, operational, or engineering questions into measurable analytic approaches, identifying appropriate data, defining assumptions, and communicating limitations and results. Familiarity with data modeling, data pipelines, APIs/interfaces, structured and semi-structured data, metadata, data quality, lineage, and provenance concepts. Working knowledge of statistical methods and machine learning fundamentals, including model selection, validation, performance metrics, overfitting, uncertainty, and appropriate use of training/test data. Experience supporting requirements management, traceability, technical baseline development, configuration management, and engineering change assessment. Experience working within Agile, DevSecOps, or other iterative engineering and software-delivery environments. Strong analytical reasoning, problem-solving, technical writing, communication, and stakeholder-engagement skills. Desired Qualifications Experience supporting defense, space, intelligence, homeland defense, or multi-domain operational environments, particularly Command and Control (C2), Space Domain Awareness (SDA), mission systems, or enterprise modernization initiatives. Experience applying the DoD Digital Engineering Strategy, digital-thread concepts, mission engineering, DoDAF/UAF, or SysML-based architecture development in a DoD environment. Experience with Cameo Teamwork Cloud, model repositories, collaborative model governance, model validation, or integration of MBSE tools with requirements and lifecycle-management platforms. Experience developing or evaluating AI/ML-enabled data fusion, anomaly detection, predictive analytics, sensor/data correlation, decision-support analytics, or other operational analytics for mission environments. Experience with cloud-native or distributed data environments, data engineering platforms, containerized analytics, APIs, message/event data, or big-data technologies in secure environments. Familiarity with data engineering and MLOps concepts, including version control, reproducible pipelines, model/data versioning, test automation, monitoring, and deployment within DevSecOps environments. Master's degree in Systems Engineering, Data Science, Computer Science, Applied Mathematics, Statistics, Operations Research, or a related technical field. OCSMP, INCOSE ASEP/CSEP/ESEP, Cameo certification, cloud/data engineering certification, or recognized data science/AI certification. $130,000-$195,000 base salary + annual bonus eligibility + medical/dental/vision/STD/LTD/Life + 401(k) + PTO Equal Employment Opportunity / Legal Disclaimer GXM Technologies LLC is an Equal Opportunity Employer and participates in E-Verify to confirm employment eligibility. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy), sexual orientation, gender identity . click apply for full job details

Year Up United is a one-year or less, intensive job training program that provides young adults with in-classroom skill development, access to internships and/or job placement services, and personalized coaching and mentorship. Year Up United participants also receive an educational stipend. The program combines technical and professional training with access to internships and job placement support through our industry-leading talent placement firm YUPRO Placement. If you receive an internship, it may be at Citizens, Amica Mutual Insurance Company, Lifespan, or Fidelity, among other leading organizations in the Providence area. Are you eligible? You can apply to Year Up United if you are: - A high school graduate or GED recipient - Eligible to work in the U.S. - Available Monday-Friday throughout the duration of the program - Highly motivated to learn technical and professional skills - Have not obtained a Bachelors degree - You may be required to answer additional screening questions when applying What will you gain? Professional business and communication skills, interviewing and networking skills, resume building, ongoing support and guidance to help you launch your career. During the internship phase, Year Up United students earn an educational stipend of $525 per week. In-depth classes include: - Business Operations - IT Support - Financial Operations - Banking - Project Management - Customer Success Get the skills and opportunity you need to launch your professional career. 72% of Year Up United graduates are employed and/or enrolled in postsecondary education within 4 months of graduation. Employed graduates earn an average starting salary of fifty-five thousand dollars per year. Year Up United is a one-year or less, intensive job training program that provides young adults with in-classroom skill development, access to internships and/or job placement services, and personalized coaching and mentorship. Year Up United participants also receive an educational stipend. The program combines technical and professional training with access to internships and job placement support through our industry-leading talent placement firm YUPRO Placement. If you receive an internship, it may be at Citizens, Amica Mutual Insurance Company, Lifespan, or Fidelity, among other leading organizations in the Providence area. Are you eligible? You can apply to Year Up United if you are: - A high school graduate or GED recipient - Eligible to work in the U.S. - Available Monday-Friday throughout the duration of the program - Highly motivated to learn technical and professional skills - Have not obtained a Bachelors degree - You may be required to answer additional screening questions when applying What will you gain? Professional business and communication skills, interviewing and networking skills, resume building, ongoing support and guidance to help you launch your career. During the internship phase, Year Up United students earn an educational stipend of $525 per week. In-depth classes include: - Business Operations - IT Support - Financial Operations - Banking - Project Management - Customer Success Get the skills and opportunity you need to launch your professional career. 72% of Year Up United graduates are employed and/or enrolled in postsecondary education within 4 months of graduation. Employed graduates earn an average starting salary of fifty-five thousand dollars per year.

The Annapurna Labs team at Amazon Web Services (AWS) builds AWS Neuron, the software development kit used to accelerate deep learning and GenAI workloads on Amazon's custom machine learning accelerators, Inferentia and Trainium. The AWS Neuron SDK, developed by the Annapurna Labs team at AWS, is the backbone for accelerating deep learning and GenAI workloads on Amazon's Inferentia and Trainium ML accelerators. This comprehensive toolkit includes an ML compiler, runtime, and application framework that seamlessly integrates with popular ML frameworks like PyTorch and JAX enabling unparalleled ML inference and training performance. The Inference Enablement and Acceleration team is at the forefront of running a wide range of models and supporting novel architecture alongside maximizing their performance for AWS's custom ML accelerators. Working across the stack from PyTorch till the hardware-software boundary, our engineers build systematic infrastructure, innovate new methods and create high-performance kernels for ML functions, ensuring every compute unit is fine tuned for optimal performance for our customers' demanding workloads. We combine deep hardware knowledge with ML expertise to push the boundaries of what's possible in AI acceleration. As part of the broader Neuron organization, our team works across multiple technology layers - from frameworks and kernels and collaborate with compiler to runtime and collectives. We not only optimize current performance but also contribute to future architecture designs, working closely with customers to enable their models and ensure optimal performance. This role offers a unique opportunity to work at the intersection of machine learning, high-performance computing, and distributed architectures, where you'll help shape the future of AI acceleration technology You will architect and implement business critical features, and mentor a brilliant team of experienced engineers. We operate in spaces that are very large, yet our teams remain small and agile. There is no blueprint. We're inventing. We're experimenting. It is a very unique learning culture. The team works closely with customers on their model enablement, providing direct support and optimization expertise to ensure their machine learning workloads achieve optimal performance on AWS ML accelerators. The team collaborates with open source ecosystems to provide seamless integration and bring peak performance at scale for customers and developers. This role is responsible for development, enablement and performance tuning of a wide variety of LLM model families, including massive scale large language models like the Llama family, DeepSeek and beyond. The Inference Enablement and Acceleration team works side by side with compiler engineers and runtime engineers to create, build and tune distributed inference solutions with Trainium and Inferentia. Experience optimizing inference performance for both latency and throughput on such large models across the stack from system level optimizations through to Pytorch or JAX is a must have. You can learn more about Neuron Key job responsibilities This role will help lead the efforts in building distributed inference support for Pytorch in the Neuron SDK. This role will tune these models to ensure highest performance and maximize the efficiency of them running on the customer AWS Trainium and Inferentia silicon and servers. Strong software development using Python, System level programming and ML knowledge are both critical to this role. Our engineers collaborate across compiler, runtime, framework, and hardware teams to optimize machine learning workloads for our global customer base. Working at the intersection of software, hardware, and machine learning systems, you'll bring expertise in low-level optimization, system architecture, and ML model acceleration. In this role, you will: Design, develop, and optimize machine learning models and frameworks for deployment on custom ML hardware accelerators. Participate in all stages of the ML system development lifecycle including distributed computing based architecture design, implementation, performance profiling, hardware-specific optimizations, testing and production deployment. Build infrastructure to systematically analyze and onboard multiple models with diverse architecture. Design and implement high-performance kernels and features for ML operations, leveraging the Neuron architecture and programming models Analyze and optimize system-level performance across multiple generations of Neuron hardware Conduct detailed performance analysis using profiling tools to identify and resolve bottlenecks Implement optimizations such as fusion, sharding, tiling, and scheduling Conduct comprehensive testing, including unit and end-to-end model testing with continuous deployment and releases through pipelines. Work directly with customers to enable and optimize their ML models on AWS accelerators Collaborate across teams to develop innovative optimization techniques A day in the life You will collaborate with a cross-functional team of applied scientists, system engineers, and product managers to deliver state-of-the-art inference capabilities for Generative AI applications. Your work will involve debugging performance issues, optimizing memory usage, and shaping the future of Neuron's inference stack across Amazon and the Open Source Community. As you design and code solutions to help our team drive efficiencies in software architecture, you'll create metrics, implement automation and other improvements, and resolve the root cause of software defects. You will also build high-impact solutions to deliver to our large customer base and participate in design discussions, code review, and communicate with internal and external stakeholders. You will work cross-functionally to help drive business decisions with your technical input. You will work in a startup-like development environment, where you're always working on the most important initiative. About the team The Inference Enablement and Acceleration team fosters a builder's culture where experimentation is encouraged, and impact is measurable. We emphasize collaboration, technical ownership, and continuous learning. Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future. Join us to solve some of the most interesting and impactful infrastructure challenges in AI/ML today. BASIC QUALIFICATIONS - Bachelor's degree in computer science or equivalent - 3+ years of non-internship professional software development experience - 3+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Fundamentals of Machine learning and LLMs, their architecture, training and inference lifecycles along with work experience on some optimizations for improving the model execution. - Software development experience in C++, Python (experience in at least one language is required). - Strong understanding of system performance, memory management, and parallel computing principles. - Proficiency in debugging, profiling, and implementing best software engineering practices in large-scale systems. PREFERRED QUALIFICATIONS - Familiarity with PyTorch, JIT compilation, and AOT tracing. - Familiarity with CUDA kernels or equivalent ML or low-level kernels - Candidates with performant kernel development such as CUTLASS, FlashInfer etc., would be well suited. - Familiar with syntax and tile-level semantics similar to Triton. - Experience with online/offline inference serving with vLLM, SGLang, TensorRT or similar platforms in production environments. - Deep understanding of computer architecture, operation systems level software and working knowledge of parallel computing. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company's reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers . click apply for full job details

The MLIL DataPlane team is looking for a Software Development Engineer to own the design and implementation of our inference data plane. We build the software that makes large models run efficiently on custom hardware - spanning model execution, memory management, data movement, and serving integration. Our work covers the full inference path: integrating serving engines with custom hardware, developing high-performance compute kernels, enabling efficient data movement, and driving models from early validation through production. We operate at frontier scale with large distributed models. This is a ground-up effort with rapidly evolving hardware and software. We are looking for an individual contributor who can write and optimize low-level code for custom hardware, validate model architectures end-to-end, build test and profiling infrastructure, and drive performance across the stack. Key job responsibilities - Develop and optimize compute kernels for a custom ML accelerator architecture, targeting production-level performance for large language model inference. - Implement and validate LLM architectures end-to-end - from PyTorch model definition through distributed execution on custom hardware. - Integrate custom accelerator backends into open-source ML serving frameworks (vLLM, PyTorch), including scheduler extensions, memory management, and model parallelism. - Build and maintain test infrastructure for model correctness validation across CPU, GPU, simulator, and hardware targets. - Profile and optimize inference workloads - identify bottlenecks, instrument critical paths, and drive latency and throughput improvements from simulation through hardware bring-up. - Own features end-to-end: from design through implementation, testing, and integration into the broader software stack. - Contribute to CI/CD pipelines that gate model and kernel changes on correctness and performance regressions. BASIC QUALIFICATIONS - Bachelor's degree or equivalent - 4+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Knowledge of computer architecture, operating systems, and parallel computing - Knowledge of Linux fundamentals - Strong proficiency in C/C++ - Experience developing compute kernels for GPUs, DSPs, or custom accelerators - Proven track record of owning and delivering complex software features end-to-end PREFERRED QUALIFICATIONS - Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques - Knowledge of ML frameworks including JAX, PyTorch, vLLM, SGLang, Dynamo, TorchXLA, and TensorRT - Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware - Experience with distributed systems - collective communication, RDMA, or high-speed interconnect programming - Experience with hardware simulation environments and model validation workflows - Demonstrated early adopter of AI-assisted development tools - uses LLMs or code-generation agents as part of daily workflow Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company's reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at . USA, CA, Cupertino - 165 600.00 USD annually

Year Up United is a one-year or less, intensive job training program that provides young adults with in-classroom skill development, access to internships and/or job placement services, and personalized coaching and mentorship. Year Up United participants also receive an educational stipend. The program combines technical and professional training with access to internships and job placement support through our industry-leading talent placement firm YUPRO Placement. If you receive an internship, it may be at Amazon, Dell Technologies, Merck, or The University of Texas System among many other leading organizations in the Austin area. Are you eligible? You can apply to Year Up United if you are: - A high school graduate or GED recipient - Eligible to work in the U.S. - Available Monday-Friday throughout the duration of the program - Highly motivated to learn technical and professional skills - Have not obtained a Bachelor?s degree - You may be required to answer additional screening questions when applying What will you gain? Professional business and communication skills, interviewing and networking skills, resume building, ongoing support and guidance to help you launch your career. During the internship phase, Year Up United students earn an educational stipend of $525 per week. In-depth classes include: - IT Support - Application Development - Project Management - Business Operations - Data Analysis Get the skills and opportunity you need to launch your professional career. 72% of Year Up United graduates are employed and/or enrolled in postsecondary education within 4 months of graduation. Employed graduates earn an average starting salary of fifty-five thousand dollars per year.

Job Description Job Description Description: GXM is seeking a Senior Digital Engineer - MBSE & Data Science to support advanced defense and space-related mission programs focused on Command and Control (C2), mission systems integration, cloud modernization, data-driven decision support, and enterprise capability delivery. The selected candidate will combine Digital Engineering and Model-Based Systems Engineering (MBSE) with data science and analytics to develop and maintain authoritative digital representations of mission systems and their operational context. The role will connect mission threads, operational workflows, requirements, system architectures, interfaces, data flows, analytics, and technical baselines into a traceable digital engineering environment that supports integration, assessment, and decision-making across the system lifecycle. The candidate will use engineering models and mission data to characterize system dependencies, assess integration and operational performance, identify capability and data gaps, support technical trade studies, and evaluate analytic or AI/ML-enabled capabilities. As appropriate, the candidate will develop repeatable analysis workflows using Python, SQL, Jupyter, statistical methods, data visualization, and machine learning techniques to inform architecture and mission-engineering decisions. This role requires close collaboration with enterprise and solutions architects, systems engineers, software and data engineers, cybersecurity personnel, mission operators, and Government stakeholders to ensure engineering models, data relationships, analytic assumptions, and technical decisions are accurate, explainable, traceable, and aligned to mission outcomes. This position is onsite in Colorado Springs, CO. Hybrid flexibility may be available over time based on mission requirements, classified work requirements, program execution needs, and achievement of objectives. Responsibilities Develop, maintain, and govern MBSE models supporting mission systems, enterprise capabilities, operational architectures, and C2 integration using SysML and related digital engineering methods. Model mission threads, operational workflows, system functions, interfaces, dependencies, data exchanges, analytic services, and decision-support relationships to provide an integrated view of mission execution and system behavior. Establish and maintain digital-thread traceability from mission needs and operational use cases through requirements, architecture elements, interfaces, data sources, analytic functions, verification evidence, and mission outcomes. Develop and maintain data architecture artifacts, including logical and physical data flows, source-to-consumer mappings, data/interface relationships, schemas, metadata, data lineage, and provenance needed to support integration and analytics. Acquire, clean, transform, explore, and analyze structured and unstructured data to support engineering analysis, mission assessment, capability evaluation, and operational decision support. Apply statistical analysis, feature engineering, anomaly detection, classification, clustering, forecasting, or other machine learning techniques when appropriate; select methods based on mission need, data characteristics, and operational constraints rather than technology novelty. Evaluate analytic and AI/ML-enabled capabilities using mission-relevant measures of performance and effectiveness, including accuracy, precision/recall, latency, confidence, robustness, uncertainty, false-alarm rates, and operational utility as applicable. Support explainable and auditable AI/ML integration by maintaining traceability to source data, data transformations, model versions, analytic methods, assumptions, confidence measures, provenance, and operator actions. Assess data quality, completeness, consistency, timeliness, latency, availability, and fitness for use; identify data risks and recommend engineering or operational mitigations. Create clear technical visualizations, engineering views, analytic products, and decision-support artifacts that communicate system behavior, integration dependencies, data relationships, technical risks, and mission impact to technical and non-technical stakeholders. Support requirements engineering activities, including elicitation, decomposition, allocation, validation, verification planning, change impact analysis, and requirements-to-architecture traceability. Conduct model- and data-informed trade studies, sensitivity analyses, gap assessments, and technical evaluations to support architecture decisions, capability insertion, integration planning, and technical baseline management. Support development and management of technical baselines across hardware, software, data, infrastructure, cloud, security, and operational environments. Participate in architecture reviews, engineering working groups, technical assessments, model governance activities, configuration management, and design decisions; ensure digital engineering artifacts remain synchronized with implemented system changes. Collaborate with Agile and DevSecOps teams to integrate engineering models, requirements, data products, analytic prototypes, interfaces, and verification evidence into iterative capability releases. Requirements: Required Qualifications U.S. Citizen with an active TS/SCI security clearance and ability to maintain required access throughout employment. Bachelor's degree in Systems Engineering, Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, Operations Research, Information Systems, or a related technical or quantitative discipline. 5+ years of relevant experience in systems engineering, digital engineering, MBSE, mission engineering, data science, analytics, or architecture development, including demonstrated experience working across multiple disciplines. Hands-on experience with MBSE tools such as Cameo Systems Modeler/MagicDraw, Sparx Enterprise Architect, or comparable modeling platforms. Experience developing SysML-based architecture models, engineering artifacts, requirements relationships, interface definitions, system dependencies, and technical documentation. Demonstrated data analysis or data science experience using Python and SQL, including data manipulation, exploratory analysis, statistics, and visualization. Working knowledge of Python data-science libraries and analytic environments such as pandas, NumPy, SciPy, scikit-learn, Matplotlib/Plotly, Jupyter, or equivalent tools. Experience translating mission, operational, or engineering questions into measurable analytic approaches, identifying appropriate data, defining assumptions, and communicating limitations and results. Familiarity with data modeling, data pipelines, APIs/interfaces, structured and semi-structured data, metadata, data quality, lineage, and provenance concepts. Working knowledge of statistical methods and machine learning fundamentals, including model selection, validation, performance metrics, overfitting, uncertainty, and appropriate use of training/test data. Experience supporting requirements management, traceability, technical baseline development, configuration management, and engineering change assessment. Experience working within Agile, DevSecOps, or other iterative engineering and software-delivery environments. Strong analytical reasoning, problem-solving, technical writing, communication, and stakeholder-engagement skills. Desired Qualifications Experience supporting defense, space, intelligence, homeland defense, or multi-domain operational environments, particularly Command and Control (C2), Space Domain Awareness (SDA), mission systems, or enterprise modernization initiatives. Experience applying the DoD Digital Engineering Strategy, digital-thread concepts, mission engineering, DoDAF/UAF, or SysML-based architecture development in a DoD environment. Experience with Cameo Teamwork Cloud, model repositories, collaborative model governance, model validation, or integration of MBSE tools with requirements and lifecycle-management platforms. Experience developing or evaluating AI/ML-enabled data fusion, anomaly detection, predictive analytics, sensor/data correlation, decision-support analytics, or other operational analytics for mission environments. Experience with cloud-native or distributed data environments, data engineering platforms, containerized analytics, APIs, message/event data, or big-data technologies in secure environments. Familiarity with data engineering and MLOps concepts, including version control, reproducible pipelines, model/data versioning, test automation, monitoring, and deployment within DevSecOps environments. Master's degree in Systems Engineering, Data Science, Computer Science, Applied Mathematics, Statistics, Operations Research, or a related technical field. OCSMP, INCOSE ASEP/CSEP/ESEP, Cameo certification, cloud/data engineering certification, or recognized data science/AI certification. $130,000-$195,000 base salary+ annual bonus eligibility + medical/dental/vision/STD/LTD/Life + 401(k) + PTO Equal Employment Opportunity / Legal Disclaimer GXM Technologies LLC is an Equal Opportunity Employer and participates in E-Verify to confirm employment eligibility. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy), sexual orientation . click apply for full job details

Job Description Job Description About the Role: The Network Engineer is responsible for the design, implementation, configuration, and troubleshooting of the organization's network infrastructure. This role involves ensuring the stability and performance of the network. The Network Engineer works to maintain network reliability, resolve issues promptly, and collaborate with other IT teams to ensure that networking systems support the organization's operational needs. The Network Engineer will monitor equipment, update configurations, and repair equipment as necessary. This role requires hands-on experience with the Palo Alto firewall platform. This position is ONSITE in Washington, DC and requires an ACTIVE Secret clearance. Responsibilities: Responsibilities include, but are not limited to the following: Assist in the design, implementation, and maintenance of network infrastructure Maintain documentation of network architecture and configurations Extract network configuration reports as needed Monitor network performance and troubleshoot issues proactively Manage and maintain firewall platforms (e.g., Palo Alto , Cisco ASA/Firepower), including rule base administration, NAT policy updates, and object/group management Implement and support firewall change management processes, including risk/impact assessment, maintenance windows, validation testing, and rollback planning Monitor firewall health, throughput, and logs; investigate alerts and coordinate incident response activities Ensure firewall configurations align with security baselines and compliance requirements, support periodic access reviews, audits, and vulnerability remediation Support firewall security services (e.g., IPS/IDS, URL filtering, application control) and tune policies to reduce false positives while maintaining protection Assist with performing system upgrades and patches Provide escalation technical support and incident resolution to include field operations support Assist in planning and executing disaster recovery and back up strategies Ensure the network is robust, secure, scalable, and optimized for business operations Assist in the development of Standard Operating Procedures and processes Qualifications: Bachelor's degree in IT or related field of study or equivalent relevant experience plus 5 years of experience as a Network Engineer. Active Secret Clearance or equivalent . Experience with Palo Alto firewall platform. Strong technical expertise in network engineering including firewall management, service desk setup, and multicasting Hands-on experience administering next-generation firewalls (NGFW) (e.g., Palo Alto, Cisco Firepower/ASA), including policy creation/updates and object/group management Working knowledge of firewall rule base design best practices (least privilege, segmentation, documentation/standards) and periodic access/rule reviews Proficiency with firewall logging/monitoring and traffic analysis (e.g., syslog, NetFlow) Familiarity with firewall hardening, patching, and configuration compliance, including implementing changes through formal change control and supporting audits. Strong experience with Palo Alto and Cisco products and tools Strong experience with SolarWinds and its modules Familiar with various applications, such as Wireshark and Dameware Strong problem solving and communication skills Cisco Certified Network Professional (CCNP) - Security certification strongly preferred Other Preferred certifications and training (or similar equivalents): Microsoft Certified Solutions Expert (MCSE) Microsoft Certified: Windows Server Hybrid Administrator Associate Microsoft 365 Certified: Administrator Expert Microsoft Certifications and Applied Skills Certified Cloud Security Professional (CCSP) Cisco Certified Network Associate (CCNA) CompTIA Network+ CompTIA A+ Azure Database Administrator Associate Microsoft 365 Certified: Fundamentals Benefits: Competitive salary: $120,000.00 - $128,000.00 Paid Time Off & Holiday Pay Medical Insurance Dental Insurance Vision Insurance Disability, Life Insurance, and AD&D Flexible Spending Accounts Pre-Tax 401K and/or After-Tax Roth IRA (with employer matching contribution) Tuition and Technical Training Reimbursement Exercise Reimbursement Employee Assistance Program Collaborative and dynamic work environment Physical Demands : The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this job, the employee may be regularly required to stand, sit, talk, hear, reach, stoop, kneel, and use hands and fingers to operate a computer, telephone, keyboard, and standard office equipment. Specific vision abilities required by this job include close vision requirements due to computer work. The employee must occasionally lift and/or move up to fifteen (15) pounds. Fine hand manipulation (keyboarding). Company Description Edgewater Federal Solutions is a privately held government contracting firm located in Frederick, MD. The company was founded in 2002 with the vision of being highly recognized and admired for supporting customer missions through employee empowerment, exceptional services and timely delivery. Edgewater Federal Solutions is ISO 9001, 20000-1, 270001 certified, appraised at CMMI Level 3 Maturity for Development and Services, and has been named in the Top Workplaces in the Greater Washington Area since 2018. It has been and continues to be the policy of Edgewater Federal Solutions to provide equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, national origin, age, disability, marital status, veteran status, and/or other statuses protected by applicable law. Company Description Edgewater Federal Solutions is a privately held government contracting firm located in Frederick, MD. The company was founded in 2002 with the vision of being highly recognized and admired for supporting customer missions through employee empowerment, exceptional services and timely delivery. Edgewater Federal Solutions is ISO 9001, 20000-1, 270001 certified, appraised at CMMI Level 3 Maturity for Development and Services, and has been named in the Top Workplaces in the Greater Washington Area since 2018. It has been and continues to be the policy of Edgewater Federal Solutions to provide equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, national origin, age, disability, marital status, veteran status, and/or other statuses protected by applicable law.