Research, develop, integrate, and improve proof-of-concept and production embedded electronic control systems for CAN-based complex rehabilitation electric power wheelchairs.
Responsibilities
Design, model, simulate, implement, and validate closed-loop control systems for complex rehabilitation electric power wheelchairs
Develop discrete-time state-space models, control algorithms, observers, and state-estimation methods for vehicle motion and electromechanical functions
Develop stochastic filtering and sensor-fusion models using inertial, position, velocity, distance, environmental, and vehicle-state data
Perform mechatronics analysis and simulation using closed-loop sensory feedback
Develop multi-rate digital signal and image processing algorithms, filters, sampling methods, and transforms
Team Bio: ServiceNow’s Applied AI Forward Deployed Engineering (FDE) team is where bold ideas meet transformative action. We partner with our most strategic customers to shape the future of enterprise AI. Together, we identify high-value opportunities, accelerate business outcomes, and build reusable AI-native solutions that advance the Now AI Platform.
Responsibilities
Build solution-ready LLM-enabled applications that span backend logic, data orchestration, and front-end UI
Operate in the field, working side-by-side with customers to adapt, deploy, and iterate in live environments
Lead architect and technical lead for autonomous marketplace decisioning systems, guiding research-to-production ML/RL pipelines and generative AI tools.
Responsibilities
Architect and implement end-to-end reinforcement learning pipelines for pricing, dispatch, and supply repositioning
Design latent world models and spatio-temporal marketplace state representations
Establish off-policy evaluation frameworks and safety guardrails
Build behavioural simulation systems using fine-tuned LLMs
Partner with backend, streaming, and platform engineering teams to deploy low-latency decision agents
Requirements
PhD in Computer Science, Operations Research, Applied Mathematics, or related quantitative discipline
Master’s degree with 12+ years of equivalent experience
Lead research on hyper-personalization and memory evolution for AI agents, developing algorithms, models, and prototypes to enhance user understanding and personalization across tasks.
Responsibilities
Conduct research on long-term memory and personalization modeling
Develop and evaluate multi-modal interaction trajectories and skill learning
Design and implement multi-agent collaborative memory systems
Adapt large models for personalization and memory read/write
Create high-quality training data and conduct supervised fine-tuning
Requirements
Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Mathematics or related field
Apply generative AI models across image, video, audio, and language to build creative workflows, demos, and product experiences that drive user engagement and revenue growth.
ILS-ingenjör hos Saab Dynamics som arbetar med Integrated Logistics Support för avancerade tekniska system.
Responsibilities
Analysera driftsäkerhet, tillgänglighet och underhållsbehov för tekniska system
Ta fram underhålls- och supportkoncept för nya och befintliga produkter
Tolka system- och kundkrav och omsätta dem till lösningar och specifikationer för logistikstöd
Arbeta med reservdelsförsörjning, teknisk dokumentation och utbildningslösningar
Genomföra analyser kopplade till exempelvis driftsäkerhet, underhåll, livscykelkostnader och reservdelsoptimering, såsom FMEA/FMECA, LCC, LORA och reservdelsanalyser
As an ILS engineer at Saab Dynamics, you work with Integrated Logistics Support (ILS) for advanced technical systems to ensure products are reliable, user-friendly, and maintainable throughout their lifecycle.
Locations (2)
Karlstad, Värmland, Sweden
Karlskoga, Nästästland, Sweden
Responsibilities
Analyze operational reliability, availability, and maintenance needs for technical systems
Develop maintenance and support concepts for new and existing products
Interpret system and customer requirements and translate them into solutions and specifications for logistics support
Work with spare parts supply, technical documentation, and training solutions
Conduct analyses related to operational reliability, maintenance, lifecycle costs, and spare parts optimization, such as FMEA/FMECA, LCC, LORA, and spare parts analysis
Requirements
Technical high school or university degree
Nice to have: Experience with complex technical systems
The salary range for this job is:
New York City, Boston, and Washington DC Metro Areas, Washington State, and Southern California offices – $166,900 to $278,100
Bay Area California offices – $173,800 to $289,700
All other offices locations in the US, including Sacramento – $139,100 to $254,900
Individual salaries within these ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.
Responsibilities
Partner with client stakeholders to understand business objectives, challenges, and opportunities.
Lead discovery, requirements definition, solution design, and implementation activities.
Design and deliver solutions across AI, cloud, data, digital, and platform engineering domains.
Translate business requirements into scalable architectures, delivery plans, and engineering workstreams.
Own solution delivery end-to-end, from problem definition through deployment and adoption.
Requirements
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience
Nice to have: Experience delivering AI solutions in financial services or another regulated industry
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