AI Research Scientist Remote Jobs in Washington (US)
This page tracks remote ai research scientist openings that are location-eligible for Washington.
This page tracks remote ai research scientist openings that are location-eligible for Washington.
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247 Jobs
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Role Description Are you pushing the frontier of computer vision, multimodal large models, and embodied/physical AI—and have the publications to show it? Join us to translate cutting-edge research into production systems that perceive, reason, and act in the real world. We are building state-of-the-art Vision AI across 2D/3D perception, egocentric/360° understanding, and multimodal reasoning. As an AI Research Engineer, you will own high-leverage experiments from paper → prototype → deployable module in our platform. We are seeking passionate Engineers to join our cutting-edge labs, you could be part of: - Computer Vision team: Dive into the world of 3D reconstruction, scene understanding, and visual AI. Explore innovative techniques like those used to transform real-world spaces into immersive 3D models. - Physical AI Robotics team: Work at the intersection of simulation, robotics, and AI. Leverage NVIDIA’s Omniverse for advanced 3D simulation and collaboration. What You’ll Do: - Advance Visual Perception: Build and fine-tune models for detection, tracking, segmentation (2D/3D), pose & activity recognition, and scene understanding (incl. 360° and multi-view). - Multimodal Reasoning with VLMs: Train/evaluate vision-language models (VLMs) for grounding, dense captioning, temporal QA, and tool use. - Physical AI & Embodiment: Prototype perception-in-the-loop policies that close the gap from pixels to actions. - Data & Evaluation at Scale: Curate datasets, author high-signal evaluation protocols/KPIs, and run ablations. - Systems & Deployment: Package research into reliable services on a modern stack (Kubernetes, Docker, Ray, FastAPI). - Agentic Workflows: Orchestrate multi-agent pipelines that combine perception, reasoning, simulation, and code generation. Example Problems You Might Tackle: - Long horizon video understanding from egocentric or 360° video. - 3D scene grounding: linking language queries to objects, affordances, and trajectories. - Fast, privacy-preserving perception for on-device or edge inference. - Robust multi-modal evaluation: temporal consistency, open-set detection, uncertainty. - Vision conditioned-policy evaluation in simulation with sim2real stress tests. Qualifications - Masters/Ph.D in CS/EE/Robotics (or related), actively publishing in CV/ML/Robotics. - Strong PyTorch (or JAX) and Python; comfort with CUDA profiling and mixed precision training. - Demonstrated research in computer vision and at least one of: VLMs, embodied/physical AI, 3D perception. - Proven ability to move from paper → code → ablation → result with rigorous experiment tracking. Requirements - Experience with video models (e.g., TimeSFormer/MViT/VideoMAE), diffusion or 3D GS/NeRF pipelines, or SLAM/scene reconstruction. - Prior work on multimodal grounding or temporal reasoning. - Familiarity with ROS2, DeepStream/TAO, or edge inference optimizations. - Scalable training: Ray, distributed data loaders, sharded checkpoints. - Strong software craft: testing, linting, profiling, containers, and reproducibility. - Public code artifacts (GitHub) and first-author publications or strong open source impact. Benefits - Real impact: Your research ships—powering core features in our MVPs and products. - Mentorship: Work closely with our Principal Architect and senior engineers/researchers. - Velocity + Rigor: We balance top-tier research practices with pragmatic product focus. - Salary: $140K - $150K
Aptura works with leading foundational AI labs to bring institutional finance expertise directly into AI model development. Founded by ex-Lazard and Partners Group professionals, we operate from London and San Francisco.
Role Description You'll work directly on improving how Frontier AI handles corporate finance and gain rare, early exposure to how AI labs actually develop their models. As part of the project, you will contribute your deal experience to a structured research project, which will be used to help improve AI reasoning across investment banking and capital markets. The work involves: - Generating, refining, and evaluating content that reflects how senior IB professionals think through transactions from origination and pitching through execution and close. Qualifications - 3–7 years of experience in investment banking or capital markets at a bulge bracket or elite boutique (e.g., Goldman Sachs, Morgan Stanley, J.P. Morgan, Bank of America, Citi, Barclays, UBS, Deutsche Bank, Wells Fargo, Evercore, Moelis, Centerview, Lazard, Jefferies) - Associate, VP, or Director level across M&A, industry coverage, ECM/DCM, leverage finance, or syndicate - Deep expertise in at least one of: M&A deal structuring and valuation, equity or debt capital markets execution, sector-specific coverage, or syndicate/book-running - Strong financial modeling skills (incl. LBO, 3-statement, DCF) and comfort with complex transaction analysis, fairness opinions, and client-facing materials (incl. pitch decks, market updates) - Ability to articulate investment banking judgment clearly and precisely in writing Requirements - Commitment: 20+ hours/week, flexible scheduling - Location: Fully remote - Compensation: Competitive hourly rate, commensurate with experience - Start date: Immediate / Rolling - Referral bonus: For any successful referral hired into this role How to apply - Apply using the link in the job post - Our team will review the applications and reach back out - One call to assess your fit and align expectations - Once approved, we kick off the project
• Researching and developing advanced healthcare informatics solutions with a specialization in Agentic AI. • Explore applications of Agentic and Generative AI in healthcare. • Develop, analyze, and collaborate on agentic AI projects. • Work closely with cross-functional teams to drive innovative research and practical implementation in healthcare environments.
We build space simulation and analytics solutions to bring clarity to complex environments and create a safer world.
• Engage in relevant research and development (R&D) of AI systems, models, and advanced machine learning algorithms that augment physics-driven modeling and simulation systems • Explore and implement AI-powered simulation tooling in support of AI workflows through reinforcement learning, multi-agent systems, and hybrid modeling approaches • Collaborate with research, engineering, and product teams to build AI-powered solutions that meet mission-critical modeling and decision-support needs • Engage in and support the drafting and review of conference and journal articles and presentations, sharing advances with both internal stakeholders and the wider research community. • Contribute content to technical invention disclosures, including associated narrative, graphics, and engagements in support of patent development • Perform additional responsibilities (no more than 10% of duties) in support of the company’s technology and product development initiatives.
We are Oregon's only public academic health center. In addition to caring for patients, we lead groundbreaking research. We also train the next generation of health care professionals. As Portland's largest employer, we give you opportunities to learn and advance in a system of hospitals and clinics across Oregon and Southwest Washington. All are welcome. OHSU welcomes people of all ages, ethnicities, genders, national origins, religions and sexual orientations. We are striving to build an anti-racist, multicultural institution and encourage people with diverse backgrounds to apply. To request reasonable accommodation, contact askhr@ohsu.edu.
Role Description A postdoctoral fellow position in myelin biology is available in the laboratory of Ben Emery in the Jungers Center for Neurosciences Research at Oregon Health and Science University. The position is for the bioinformatic investigation of central nervous system remyelination and neuroglial interactions in mouse models and human datasets. - Run a research project investigating CNS cell interactions during remyelination, including the use of genetic models of demyelination, snRNA-sequencing, and histological analyses. - Regularly attend and contribute to laboratory and departmental meetings. - Contribute to the preparation of scientific manuscripts. - Keep abreast of the scientific literature relevant to the project. Qualifications - PhD in Neuroscience. - Relevant skills in rodent models of CNS injury, bioinformatics, and machine learning approaches to microscopy analysis. - Excellent documentation and written communication skills. - Able to perform the essential functions of the position with or without accommodation. Benefits - Oregon's only public academic health center. - Opportunities to learn and advance in a system of hospitals and clinics across Oregon and Southwest Washington. Company Description In addition to caring for patients, we lead groundbreaking research. We also train the next generation of health care professionals. All are welcome. OHSU welcomes people of all ages, ethnicities, genders, national origins, religions, and sexual orientations. We are striving to build an anti-racist, multicultural institution and encourage people with diverse backgrounds to apply. To request reasonable accommodation, contact askhr@ohsu.edu .
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or disability.
Role Description The Machine Learning Researcher is responsible for the development, evaluation, and optimization of machine learning and deep learning algorithms that support innovative digital dentistry solutions. This role focuses on advancing artificial intelligence capabilities through research, model development, and collaboration with cross-functional teams to translate cutting-edge technologies into high-impact product features. Working closely with software engineers, data engineers, product teams, and clinical experts, the Machine Learning Researcher contributes to the full machine learning lifecycle, including: - Data preparation - Model training - Validation - Deployment support - Intellectual property development Qualifications - Bachelor’s or master’s degree in computer science, Data Science, Mathematics, Statistics, Engineering, or a related STEM discipline. - Strong understanding of machine learning, deep learning, statistics, and applied mathematics. - Minimum of 3 years of experience developing machine learning solutions, preferably within a regulated medical device, healthcare, or life sciences environment. - Proficiency in Python and machine learning development workflows. - Hands-on experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras. - Experience with software development and best practices, including source control systems (e.g., Git). - Strong analytical and problem-solving skills with the ability to independently investigate complex technical challenges. - Demonstrated ability to learn new technologies quickly and contribute effectively within cross-functional teams. - Excellent written and verbal communication skills. Requirements - Define machine learning and data science requirements for new product features and capabilities. - Design, train, validate, and optimize machine learning models, with a focus on deep neural networks and computer vision applications. - Develop algorithms utilizing dental imaging data, including 2D and 3D radiographic images, CBCT scans, and intraoral optical scans. - Evaluate and improve existing machine learning models using state-of-the-art methodologies and published research. - Establish appropriate performance metrics, validation strategies, and error analysis approaches to ensure robust model performance. - Design and implement efficient algorithms and data structures for model training and inference. - Collaborate with software engineers and data engineers to improve data pipelines, data management processes, and model deployment workflows. - Define data requirements for training, validation, and performance evaluation. - Develop data preprocessing and postprocessing pipelines aligned with product and feature requirements. - Support the integration of machine learning solutions into commercial software products. - Monitor advancements in machine learning, deep learning, computer vision, and related research domains. - Assess emerging technologies and recommend opportunities for application within product development. - Contribute to intellectual property generation, including invention disclosures, patent applications, and technical documentation. - Collaborate with legal and intellectual property teams to support patent prosecution and maintenance activities. - Ensure development activities align with applicable quality management systems and medical device regulations. - Support documentation and validation activities required for regulated software products. Benefits - Primarily remote position with occasional travel as required. - Collaboration with global cross-functional teams across multiple time zones. - Participation in research, product development, and innovation initiatives supporting digital dentistry solutions. Company Description All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or disability. Employment Type: Full Time Alternative Locations: United States : Andover (MA) Travel Percentage: 0 - 10% Requisition ID: 21283
Pioneering AI-first solutions, solving complex business challenges through expertise, cloud, data engineering, and AI.
• Deliver multi-geography projects for healthcare organizations • Collaborate with Cloud, Software, and Data Engineering teams • Design, build, and evaluate healthcare solutions • Develop high-level solution architectures • Ensure responsible AI practices • Lead technical discussions and mentor senior resources • Contribute to a collaborative team culture
Role Description We are seeking a Principal Applied AI Scientist to lead the research, development, and deployment of advanced machine learning and AI systems that power Claritev’s next generation of healthcare products. This is a hands-on technical leadership role for an experienced applied scientist who thrives at the intersection of research innovation, real-world deployment, and measurable business impact. - Architect and deliver predictive, generative, and agentic AI systems that automate complex healthcare workflows and unlock new insights from large-scale healthcare data. - Work closely with Product, Engineering, and business leaders to translate cutting-edge research into scalable production solutions that improve transparency, reduce costs, and simplify healthcare operations. - Serve as a technical thought leader and mentor, helping shape Claritev’s AI strategy and elevating the scientific rigor and innovation of the organization. Qualifications - Ph.D. or M.S. in Computer Science, Statistics, Applied Mathematics, Data Science, or a related field. - 6+ years of hands-on industry experience in applied ML / AI, with a track record of delivering solutions from prototype to production. - 2+ years of experience with Generative AI and/or agentic systems. - Experience in healthcare or other regulated environments (preferred). - Familiarity with ML Ops / LLM Ops practices (preferred). - Experience integrating predictive ML with generative/agentic systems (preferred). - Proficiency with AI coding tools (e.g., Copilot, Codex) (preferred). Requirements - Strong proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow). - Experience with agentic frameworks (e.g., LangChain, LangGraph, Autogen, crewAI). - Experience with RAG pipelines, embeddings, and retrieval systems. - Experience in agent design (tool use, planning, memory, orchestration). - Experience building evaluation pipelines for ML/LLM systems (accuracy, reliability, latency). - Strong foundation in ML theory, deep learning, statistics, and optimization. - Experience with cloud environments and large-scale data systems. - Strong product mindset, aligning technical work with business outcomes. - Ability to drive projects end-to-end with minimal oversight. - Excellent communication and collaboration skills. - Proven ability to influence cross-functional teams and mentor others. Benefits - Medical, dental and vision coverage with low deductible & copay. - Life insurance. - Short and long-term disability. - Paid Parental Leave. - 401(k) + match. - Employee Stock Purchase Plan. - Generous Paid Time Off – accrued based on years of service. - 10 paid company holidays. - Tuition reimbursement. - Flexible Spending Account. - Employee Assistance Program. - Sick time benefits – for eligible employees, one hour of sick time for every 30 hours worked, up to a maximum accrual of 40 hours per calendar year. Compensation The salary range for this position is $190K to $210K. Specific compensation offers are determined based on a variety of factors including the candidate’s education, experience, skills, work location, and internal equity considerations. In addition to base salary, this position is eligible for an annual performance bonus and a comprehensive benefits package, including health insurance and a 401(k) retirement plan. EEO Statement Claritev is an Equal Opportunity Employer and complies with all applicable laws and regulations. Qualified applicants will receive consideration for employment without regard to age, race, color, religion, gender, sexual orientation, gender identity, national origin, disability or protected veteran status. Application Deadline We will generally accept applications for at least 5 calendar days from the posting date or as long as the job remains posted.
The easiest no-code platform to build powerful portals and internal tools on top of your existing data.
Role Description As our SEO & AI Search Lead, you will own organic performance end to end: traffic, signups, and share of voice in AI answers. Your job is to make Softr the most-recommended, most-cited, and most-accurately-described platform in our category, across both classic search and the AI layer on top of it. You will report to the Head of Marketing and work closely with Content, Product Marketing, Engineering, and Brand. This is a high-ownership role with executive visibility; you will set the roadmap, run the playbook, and make the calls on where we invest next. Tasks - Own organic growth: Drive SEO and AEO/AIO performance across traffic, signups, and share of voice in AI answers; you set the targets and you hit them. - Set and run the roadmap: From keyword and prompt research to publishing priorities, programmatic systems, and link strategy; you decide what we ship and in what order. - Reposition Softr in LLMs: Move us off "no-code portal builder" and into accurate, current positioning across ChatGPT, Perplexity, Gemini, and Claude. Track it in Profound, close citation gaps, and engineer the content patterns LLMs actually quote. - Lead technical and programmatic SEO: Site health, indexation, Core Web Vitals, schema, and internal linking plus scoping programmatic page systems with engineering and managing quality at scale. - Build link, citation, and Reddit authority: Drive link and citation building across owned, earned, and partner channels, with a deliberate Reddit strategy that earns mentions LLMs and Google both trust. - Partner, report, and pitch new bets: Brief Content on structure and on-page, report monthly on SEO/AEO performance, flag risks early, and translate algorithm and LLM behavior changes into actions for the team. Qualifications - Proven organic track record: 5+ years in SEO with concrete wins you can point to meaningful traffic, signup, or revenue lifts at a SaaS or product-led company. - AEO/AIO fluency: You've actively worked on getting cited in AI answers, not just read about it. Hands-on with Profound or equivalent tooling, and a clear point of view on what makes LLMs quote one source over another. - Reddit and citation building (must-have): You understand how Reddit ranks, how it feeds both Google and LLM answers, and you've earned visibility there without burning the community. - Technical SEO chops: You can talk shop with engineers on indexation, rendering, schema, and Core Web Vitals and ship fixes, not just file tickets. - Programmatic SEO experience: You've designed and scaled page systems that hold up on quality, not just volume. - Analytical and outcome-driven: Comfortable with GSC, GA, Ahrefs/Semrush, BigQuery, and whatever tool answers the question fastest. You measure what matters and ignore vanity metrics. - Curiosity and adaptability: The search landscape is shifting monthly — you stay on top of algorithm and LLM behavior changes and turn them into action, not anxiety. - High ownership and grit: You operate like a founder of your function. You don't wait for direction, and you finish what you start. - Sharp written communication: You can brief content teams, pitch leadership, and write the kind of clear copy that both humans and LLMs reward. Benefits - Fast-growing company and opportunity to make an impact on a large scale. - Competitive salary and equity options. - Fully remote and flexible work schedule. - High ownership, zero bureaucracy. Lean team, get-things-done mindset. - Annual company retreat and team gatherings. - Work directly with the founders and leadership team. - Our customers love Softr (1M+ users and growing)! A daily dose of customer love and positive feedback that rewards your work. - Backed by the best - we are well-resourced, profitable, and backed by best investors, like FirstMark Capital and the world’s best angel investors.
Role Description We're hiring our first dedicated AI Researcher to advance the core models powering Ares. You'll work alongside our VP of AI Engineering and a small AI engineering team, with direct collaboration with our CEO — a researcher and practitioner with 26 years of offensive security experience, contributions to the OWASP API Security Top 10, and a permanent exhibit at The Mob Museum. This is a research role, not an applied ML role. You'll own original research on offensive security agents — how they reason, plan, use tools, and operate autonomously over long horizons. You'll design experiments end-to-end, build the evaluation infrastructure the field doesn't yet have, and translate research wins into capability that ships. The feedback loop is fast and adversarial. Research that proves out goes into production. Research that doesn't gets killed quickly so the next bet can start. What You'll Do - Drive original research on offensive security agents — reasoning, planning, tool use, and autonomous long-horizon operation - Advance Dagger's post-training pipeline: supervised fine-tuning, RL from verifier signals, LoRA adaptation, and evaluation against adversarial benchmarks - Extend Javelin's co-evolutionary self-training architecture: curriculum design, self-play dynamics, and reward modeling for security-specific outcomes - Design and execute experiments end-to-end, from hypothesis through writeup - Build internal evaluation harnesses that measure capability rigorously, where no public benchmark exists - Translate research into production handoffs to AI Engineering — model cards, deployment notes, and known failure modes - Contribute to Assail's external research voice through papers, talks, responsible disclosures, and technical writing - Collaborate with engineering teammates on research methodology and experimental design Qualifications - Original ML research output — published papers, widely cited preprints, significant open-source releases, or shipped research that materially advanced a production system - Hands-on post-training experience with language models at the 7B+ parameter scale, end-to-end ownership of a pipeline including data, training, and evaluation - Direct work with at least one of: RL from verifier or reward signals, preference optimization (DPO/IPO/KTO), or supervised fine-tuning with synthetic data pipelines - Experience with agentic LLM systems — tool use, multi-step reasoning, planning, or long-horizon execution - Ability to design evaluation that measures real capability and avoids contamination or specification gaming - Strong Python and PyTorch, with experience in distributed training at multi-GPU scale - Clear technical writing — research memos, experiment writeups, papers, or equivalent Requirements - Working knowledge of offensive security fundamentals (we'll teach you the rest if you bring strong ML depth) - Prior work on code-generating or code-reasoning models - Experience with sparse, delayed, or expensive reward signals in RL - Research on robustness, adversarial ML, or red-teaming of language models - Familiarity with long-horizon agent benchmarks (SWE-bench, Cybench, WebArena, or similar) What This Role Will Teach You - How to train and post-train capable models in a narrow, high-stakes domain - How to design evaluation that holds up to scrutiny when no benchmark exists yet - How agentic systems behave under adversarial conditions — including failure modes that don't appear in benign settings - The full offensive security stack — API, web, and mobile — at a depth most ML researchers never reach - How to make publication and disclosure decisions for dual-use research - How research moves from hypothesis to production in a small team where the handoff is measured in days Benefits - Competitive base salary and meaningful early-stage equity - Comprehensive health and dental coverage - Unlimited paid time off, including parental leave - Conference, publication, and continued learning budget — we want you engaged with the research community - The chance to work on a problem that matters, with people who care about doing it well
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