Location: San Francisco United States Title: Applied Scientist Location: Toronto, ON / San Francisco, CA / Pittsburgh, PA / Remote US & Canada Job Description: Software Autonomy & Algorithms / Full-time / Remote, Hybrid Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech. With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. At Waabi, we are building the next generation of autonomous driving technology, leveraging a revolutionary approach to Physical AI. Central to our success is the ability to monitor and report on the performance of our software, platform, and fleet with rigor and reliability. We are looking for a hands-on Applied Data Scientist to help drive a unified view of our multi-faceted evaluation methodology. This is a highly collaborative, cross-functional role that sits at the intersection of Evaluation, Systems & Safety, and the Autonomy teams. You will work alongside experts across these teams to deliver a comprehensive, cross-modal analysis of our autonomy system that translates directly into actionable insights for the entire organization. You will... - Collaborate with cross-functional teams to provide comprehensive analysis on autonomy system performance across Waabi World (Simulation), Track, and Public Road testing. - Develop and maintain sophisticated, cross-modal dashboards that provide a unified and trustworthy view of the performance of our systems, tracking progress toward critical company milestones. - Partner with Data Platform and Evaluation teams to shape the evolution of eval tooling and pipelines, ensuring our infrastructure remains scalable, automated, and capable of validating complex system requirements across all testing modalities. - Act as a key partner to Safety and Autonomy teams, ensuring that our automated reporting faithfully captures the technical intent and requirements of our system KPIs. - Proactively monitor and investigate anomalies in metrics to ensure stakeholders are making decisions based on reliable, high-fidelity data. Qualifications - Minimum of 3+ years of professional experience in an analytical role (e.g., Data Science, Systems Evaluation, or Product Analytics). - BS/MS in a quantitative field such as Computer Science, Engineering, Statistics, Physics, or similar. - Strong command of SQL, and familiarity with Python for data manipulation and prototyping. - Experience building clear, automated dashboards using modern BI tools or custom frameworks. - Experience working with internal cross-functional partners/stakeholders - Open-minded and collaborative team player with willingness to help others - Passionate about self-driving technologies, solving hard problems, and creating innovative solutions. Bonus/nice to have: - Experience in the Autonomous Vehicle or Robotics industry. - Experience with large scale databases and analytics - Practical understanding of statistical concepts (e.g., hypothesis testing, significance) as applied to real-world performance measurement The US yearly salary range for this role is: $128,000 - $184,000 USD in addition to competitive perks & benefits. Waabi (US) Inc.s yearly salary ranges are determined based on several factors in accordance with the Companys compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations. Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus. Perks/Benefits: - Competitive compensation and equity awards. - Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only). - Unlimited Vacation. - Flexible hours and Work from Home support. - Daily drinks, snacks and catered meals (when in office). - Regularly scheduled team building activities and social events both on-site, off-site & virtually. - As we grow, this list continues to evolve! Waabi is a technology start-up building technologies to transform the way the world moves. Join our talented team to be a part of the future and to make an impact!

Role Description As the Global Regulatory Project Lead, you will be a key individual contributor at the forefront of our innovation pipeline, guiding the regulatory strategy for novel farm and companion animal products. You will serve as the dedicated regulatory expert on global project teams, shaping development from the ground up and leading direct negotiations with agencies like the U.S. Food and Drug Administration's Center for Veterinary Medicine (CVM). This role requires a strategic professional who can navigate complex agency interactions, influence cross-functional partners, and ensure our submissions in the United States (US), European Union (EU), and other first-wave countries are successful. Your Responsibilities - Guide the design and development of the global regulatory strategy for development projects, with a primary focus on CVM/FDA submissions. - Serve as the dedicated regulatory subject matter expert on development teams, representing the regulatory viewpoint and providing risk/benefit evaluations to guide project strategy. - Act as the primary point of contact for and lead direct engagements with regulatory agencies (e.g., CVM, European Medicines Agency (EMA)), including pre-submission meetings and negotiations. - Partner with R&D to develop and implement clinical trial submission plans, ensuring alignment with the overall regulatory strategy. - Collaborate with internal stakeholders to provide technical leadership on Quality, Safety, and Efficacy sections for regulatory submissions. - Proactively identify and communicate project-specific regulatory risks and opportunities to the development team and leadership. - Comply with all company local and global policies including quality frameworks, Code of Conduct, anti-discrimination, harassment, and health, safety, and environment (HSE) policies. Qualifications - A Master’s degree or higher in veterinary medicine, biology, infectious diseases, immunology, animal science, or a related field. - At least 10 years of relevant experience in the animal health industry, with direct regulatory affairs experience in veterinary pharmaceuticals. - Demonstrated experience leading direct submissions and negotiations with regulatory agencies, with a strong preference for the U.S. Food and Drug Administration's Center for Veterinary Medicine (CVM). - Proven ability to serve as the primary regulatory expert on cross-functional project teams in a global environment, with exceptional communication, negotiation, and influencing skills. Requirements - Direct regulatory experience with both farm animal and companion animal products. - Broad experience with global registration processes, particularly leading first-wave submissions in the European Union and other key markets simultaneously. - Experience navigating novel regulatory pathways for innovative products. - A strong understanding of risk assessment and risk management fundamentals. - Knowledge of Continuous Improvement methodologies (e.g., Six Sigma, Lean). Benefits - Multiple relocation packages - Two weeklong shutdowns (mid-summer and year-end) in the US (in addition to PTO) - 8-week parental leave - 9 Employee Resource Groups - Annual bonus offering - Flexible work arrangements - Up to 6% 401K matching

Role Description The Intel Sector at Leidos currently has an opening for a Research Scientist to work in Fort Belvoir, VA. This is an exciting opportunity to use your experience to support the Defense Threat Reduction Agency's (DTRA) Environmental Data Enterprise (EDE). In this mission, we support the environmental modeling activities of DTRA, DoW, international partners, and private industry, with a focus on atmospheric transport and dispersion (ATD) modeling. This is a full-time remote opportunity. The successful candidate will be a subject-matter expert in atmospheric science or meteorology and will take part in research and development efforts to enhance our numerical weather prediction (NWP) and ATD capabilities. The candidate will apply their expertise by using cutting-edge artificial intelligence and machine learning techniques and best software development practices to improve current capabilities and create new state of the art techniques for the evaluation and use of environmental data. This role is pivotal in designing, developing, and deploying next-generation environmental modeling systems that are crucial for national security. - AI-Driven Model Development: Design, develop, and implement novel AI/ML methods for creating, assessing, and modifying vast amounts of meteorological data. - Advanced R&D: Conduct research on improving meteorological model inputs (e.g., planetary boundary layer, vertical mixing, ensemble forecasting) for ATD models using AI techniques to increase accuracy and efficiency. - Model Validation: Participate in research on best practices to implement and integrate verification and validation methods for NWP models for application within the ATD environment. - System & Data Integration: Explore and design new processes to assist in the intelligent selection of meteorological data based on defined Chemical, Biological, Radiological, Nuclear, and high Explosive (CBRNE) scenarios. - Data Pipeline Management: Support the ingestion, quality checking, parsing, and storage of on-demand environmental data, including ocean, surface, and upper-air observations. - Software Development: Extend, improve, and develop software that bridges the gap between research and operations, and assist in the integration of software into DoW tools. - Operational Support: Provide subject matter expertise and technical assistance on the EDE system, including monitoring system status and recommending software or hardware enhancements to streamline operations. Qualifications - Master's degree and 6 years experience or a Ph.D. and 3 years experience in Atmospheric Science, Meteorology, Data Science, Computer Science, or a related physical sciences or engineering field. - Ability to obtain and maintain a DoW security clearance. Must be a U.S. Citizen. - Proven experience in developing and applying Artificial Intelligence and Machine Learning (AI/ML) models to complex scientific problems. - Strong background in numerical weather prediction (NWP), atmospheric modeling, or a related geophysical field. - Proficiency in programming languages such as Python, R, or Java, with experience using scientific computing libraries (e.g., NumPy, SciPy, Pandas) and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). - Experience handling and processing large scientific data formats like NetCDF, HDF5, and GRIB. - Familiarity with data assimilation techniques and ensemble forecasting methods. - Strong analytical and problem-solving skills, with a demonstrated ability to conduct independent research and develop innovative solutions. Preferred Qualifications - Experience with atmospheric transport and dispersion (ATD) models (e.g., HPAC, SCIPUFF). - Familiarity with DoD cybersecurity practices and information assurance standards. - Experience working in a Linux/Unix environment. - Knowledge of space weather and its impact on terrestrial systems. - Experience with deploying and maintaining operational scientific models or software. Pay Range Pay Range $107,900.00 - $195,050.00. The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

Role Description Innodata is expanding its GenAI research capability to advance state-of-the-art evaluation and post-training methods for LLM and multimodal systems. As an Applied Research Scientist, LLM Evaluation & Post-Training, you will lead research and experimentation on how evaluation design, measurement strategies, and feedback signals influence model improvement. This role is ideal for a technically rigorous researcher who is deeply fluent in modern LLM evaluation and post-training, and who can turn research insight into practical methods for customer solutions and internal platform innovation. You will work across human-in-the-loop and AI-augmented workflows, partnering with Language Data Scientists and AI/ML Research Engineers to design and validate evaluation frameworks that drive measurable model gains. The ideal candidate combines strong experimental and statistical judgment with hands-on technical ability and can engage as a peer with research and engineering stakeholders at leading AI companies. What You’ll Own - Define the next generation of evaluation-driven model improvement workflows. - Study how different evaluation approaches (human, automated, hybrid) shape model selection and post-training outcomes. - Design experiments that produce credible, actionable conclusions. - Design benchmark datasets, develop evaluation taxonomies and protocols, define metrics and scoring methodologies, analyze failure modes, and test how changes in evaluation setup affect downstream fine-tuning results. - Support customer engagements by bringing scientific rigor to evaluation strategy, methodology review, and technical recommendations. - Define and execute a research agenda focused on LLM evaluation and post-training, especially evaluation-driven model improvement. - Design rigorous experiments to study how evaluation methodologies impact fine-tuning and post-training outcomes. - Develop and validate evaluation frameworks for LLM and multimodal systems, including: - benchmark/task design - scoring methods - judge/model-assisted evaluation - human evaluation protocols - robustness/stress testing - Lead research on advanced evaluation domains, including long-context, cross-modal, and dynamic multi-turn evaluations. - Study the effectiveness and limitations of existing evaluation techniques, and propose improved methodologies with clear validity and scalability tradeoffs. - Analyze model behavior and failure patterns; generate actionable recommendations for model improvement and evaluation redesign. - Collaborate with AI/ML Research Engineers to translate research methods into scalable evaluation and post-training pipelines. - Collaborate with Language Data Scientists to integrate human-in-the-loop and synthetic data/evaluation strategies into research programs. - Engage with customer technical stakeholders to understand evaluation goals, review methodologies, and provide expert recommendations. - Contribute to internal benchmark datasets, evaluation frameworks, and reusable research assets. - Produce high-quality technical documentation, internal research reports, and client-facing materials explaining methods, results, assumptions, and limitations. - Contribute to thought leadership and best practices in LLM evaluation, post-training, and GenAI quality measurement. Qualifications - MS/PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, AI, or a related quantitative scientific field (PhD strongly preferred). - 5+ years of relevant experience in applied research / research science in ML/AI, with substantial work in LLMs or foundation models. - Demonstrated experience with LLM evaluation, benchmarking, alignment, post-training, or model quality research. - Strong foundation in experimental design, statistical analysis, and scientific reasoning for ML systems. - Strong coding skills in Python for research experimentation and analysis (e.g., data processing, evaluation pipelines, statistical analysis, visualization). - Experience working with modern ML tooling/frameworks (e.g., PyTorch, Hugging Face, JAX/TensorFlow as applicable) sufficient to design and execute model/evaluation experiments. - Ability to evaluate and compare human and automated evaluation methods, including tradeoffs in cost, reliability, validity, and scalability. - Experience designing evaluation studies and protocols that are reproducible across datasets, model versions, and evaluation runs. - Ability to collaborate directly with technical stakeholders including research scientists, ML engineers, data scientists, and customer technical counterparts. - Strong communication skills and ability to present nuanced technical conclusions, assumptions, and limitations clearly. Requirements - The expected salary range for this position is $175,000 – $225,000 USD per year, based on experience, skills, and qualifications. Company Description Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers.