Research intern to investigate sim-to-sim and sim-to-real transfer for autonomous driving models.
Compensation
The pay range for this position at commencement of employment is expected to be between $45 and $65/hour for California-based roles.
Responsibilities
Conduct research to advance the state of the art in sim-to-sim and sim-to-real domain mapping
Design and run experiments using large-scale Toyota driving data, generative base models, and closed-loop simulation infrastructure
Perform closed-loop evaluations across simulators of varying fidelity and develop metrics
Collaborate with researchers and engineers to integrate tools and findings into the team’s model development and post-training workflows
Present progress and results regularly to the team and incorporate feedback
Requirements
Currently pursuing a Ph.D. or master’s degree in Computer Science, Robotics, Machine Learning, Artificial Intelligence, Engineering, or a related field
Nice to have: CARLA
Nice to have: NVIDIA DriveSim
Nice to have: world models
Nice to have: generative models for video or scene reconstruction
Join Kiewit Data Services for a summer internship applying machine learning to construction challenges. Work with a team building AI-assisted workflow automations, improving project estimates, and developing models/applications using data from ground robots, drones, fixed cameras, and connected vehicles.
Responsibilities
Work with machine learning specialists, engineers, and project teams to understand needs and develop practical solutions.
Help prepare and assess data used in machine learning models and estimation tools.
Contribute to AI-assisted workflow automations and models that support financial and schedule estimates.
Explore data from robots, drones, cameras, and connected vehicles to identify patterns and support forward-looking models.
Investigate issues, test approaches, and explain findings to technical and nontechnical teammates.
Buscamos un/a Especialista DevOps con perfil altamente técnico para disenñar, automatizar, mantener y evolucionar la infraestructura que el equipo de QA necesita para ejecutar pruebas de forma estable, repetible, desatendida y escalable.
Responsibilities
Aprovisionar y configurar ambientes de QA mediante infraestructura como código (Terraform).
Automatizar los despliegues en dichos ambientes.
Configurar y resolver incidencias (troubleshooting) de servidores Linux/Windows, servicios, bases de datos (PostgreSQL, MySQL, SQL Server, Oracle, MongoDB) y demás componentes necesarios para las pruebas.
Estandarizar los ambientes y garantizar su reproducibilidad.
Integrar las pruebas automatizadas dentro de los pipelines (Jenkins, GitLab CI, GitHub Actions, Azure DevOps).
Seeking a scientist to run data collection, engineering, and analysis for large-scale studies involving human subjects in the domains of digital health and consumer electronics.
Compensation
At the Associate and Senior Associate level, total compensation includes base salary, bi-weekly bonuses for high-intensity efforts, annual bonus and 401(k) employer contribution of 7% of base salary.
Responsibilities
Leading human-subjects data-collection programs, including study design, protocols, participant-facing interactions, and quality control
Troubleshooting prototype hardware, sensor arrays, mobile devices, operating systems, and research software in real-world study environments
Writing backend code to manage complex data flows spanning a variety of different domains and sources, often with regulatory requirements (Part 11, HIPAA, etc.)
Building lightweight tools for tracking, automation, visualization, data processing, and quality control
Developing and maintaining strong client and stakeholder relationships
Perform hands‑on laboratory testing of electronic and security technologies, develop software and controls, and apply data analysis to support defense and government clients.
Compensation
Salary Range USD $140,000.00 - USD $154,000.00 /Yr.
Responsibilities
Performing hands‑on laboratory testing of electronic devices and security technologies using instruments such as oscilloscopes, protocol analyzers, and RF equipment
Developing software in Python, LabVIEW, and other tools to automate tests, control instruments and hardware, acquire data, and build repeatable analysis pipelines
Supporting engineering projects as needed with prototyping custom fixtures, instrumentation, and data acquisition setups, systems integration, controls, thermal analysis, and mechanical design
Analyzing results with statistical methods and error analysis, visualizing and documenting them in clear, traceable technical reports, troubleshooting equipment, test setups, and data to root cause, and communicating findings to colleagues and clients
Building the practice by staying current in laboratory testing, security, and data practices, supporting marketing of its capabilities, and educating fellow consultants
Requirements
Ph.D. OR Masters plus 3+ years’ experience in Physics, Nuclear Engineering, Electrical Engineering, or a related experimental science or engineering field
Senior Full-Stack Software Engineer to design and build scalable, secure, and user-centric applications that power Versant’s next-generation platforms.
Compensation
Salary range: $110,000 - $160,000
Responsibilities
Collaborate with cross-functional teams from ideation to launch, delivering full-stack solutions that solve real business problems.
Design and build scalable, fault-tolerant microservices and modern front-end applications.
Leverage SaaS, low-code/no-code platforms where appropriate to accelerate delivery.
Participate in code reviews, pair programming, and knowledge-sharing sessions to elevate team quality.
Mentor junior engineers and contribute to a culture of continuous learning and improvement.
We are looking for a Software Engineer to join our growing engineering team. You will contribute to the design and development of scalable, secure, and user-centric applications that power Versant’s next-generation platforms.
Locations (2)
New York City, New York, United States
Englewood Cliffs, New Jersey, United States
Responsibilities
Collaborate with cross-functional teams to deliver full-stack solutions that solve real business problems.
Implement scalable, fault-tolerant microservices and modern front-end applications.
Use SaaS and low-code/no-code platforms where appropriate to accelerate delivery.
Participate in code reviews, pair programming, and team knowledge-sharing sessions.
Write secure, performant, and maintainable code.
Requirements
Nice to have: GenAI
Nice to have: SaaS platforms
Nice to have: low-code/no-code tools
Nice to have: serverless technologies
Senior Software Engineer, Full Stack (iOS & Backend)
Build and own core member-facing features end to end, set architectural patterns, partner with server engineering on API design, work with product, design, and data science to scope, experiment, and launch member-facing features, contribute across large iOS and Node.js codebases, own production health, raise engineering bar through code review, mentorship, and clear written specs.
Compensation
We offer comprehensive medical and dental coverage, $50 a day food delivery budget, equity based employment, a great culture, learning opportunities, unlimited vacation, 12 weeks paid parental leave, and we pay all employees $1,000 a year to go somewhere in the world that they've never been because of our values of human connection, empathy, and curiosity.
Responsibilities
Build and own core member-facing features end to end.
Set architectural patterns and best practices, and solve hard client-side lifecycle and state management problems.
Partner with server engineering on API design, data correctness, and client-server state sync, and implement backend components of features.
Work with product, design, and data science to scope, experiment with, and launch member-facing features.
Contribute across large, long-lived iOS and Node.js codebases: performance, testing practices, and deliberate management of tech debt.
Seeking a highly skilled Vision System Data Science Engineer (Level 4) to much the design, development, and deployment of advanced computer vision and machine learning solutions for complex industrial and manufacturing applications.
Responsibilities
Design, develop, and deploy computer vision algorithms for detection, classification, segmentation, anomaly detection, and predictive analytics.
Build scalable machine learning and deep learning models using image, video, and multimodal sensor data.
Lead the complete data science lifecycle, including data collection, labeling, feature engineering, model training, validation, deployment, and monitoring.
Develop robust image-processing pipelines utilizing modern computer vision frameworks and cloud technologies.
Define data quality standards and establish model performance metrics to ensure production readiness.
L'objectif de ce stage porte sur l'automatisation par scripting (PyAnsys) de modèles éléments finis. Vous développez une méthodologie réutilisable et proposez une solution clé en main pour industrialiser l’évaluation de la robustesse mécanique d’équipements électroniques.
Responsibilities
Optimisez la préparation des géométries : format d’import, simplifications, nettoyage et standardisations
Modélisez des cartes électroniques (PCB, composants) : règles de représentation et mise en cohérence des hypothèses
Automatisez la construction du modèle : contacts, assemblages vissés, maillage, organisation des objets
Réalisez la mise au point des modèles de fatigue à partir de résultats d’essai
Automatisez le post-traitement : déformées modales, DSP, mise en forme
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