1:00 PM - 2:00 PM
Senior Product Manager Interview
Sarah Jenkins
The demand for a senior AI research scientist continues to accelerate as companies across the USA invest heavily in advanced machine learning and applied research initiatives. This remote role offers 500+ open positions for professionals ready to lead innovative projects from anywhere in the country. Organizations are actively searching to hire a senior AI research scientist who can bridge cutting-edge theory with real-world deployment.
Successful candidates typically bring deep expertise in machine learning architectures, deep learning frameworks, and statistical modeling, along with strong programming skills in Python and experience with distributed computing systems. A senior-level background in publishing research, mentoring junior scientists, and translating experimental findings into scalable products is highly valued. Strong communication skills, curiosity, and the ability to collaborate across cross-functional teams remain essential, as many senior ai research scientist vacancies require both technical depth and strategic vision.
Remote work for this position generally means flexible collaboration through virtual labs, cloud-based experimentation platforms, and asynchronous research reviews with global teams. The USA market for senior ai research scientist positions remains highly competitive, driven by expanding investment in generative AI, robotics, and natural language processing. Companies increasingly offer remote-first structures to attract top-tier talent regardless of geographic location, strengthening long-term hiring outlooks nationwide.
If you're ready to shape the next generation of intelligent systems, explore senior ai research scientist jobs in the USA through Global Work AI. Whether you're advancing your research career or seeking new remote challenges, this is the moment to take the next step. Discover opportunities that match your ambition and expertise today.

Jobgether
Lead research execution and technical delivery on emerging risks related to frontier AI systems. Oversee complex research projects, ensuring quality of technical deliverables and communicating findings to clients.

Salesforce
Own full-cycle recruiting for Applied Scientist, Machine Learning Engineer, and Data Scientist roles. Partner with senior leaders to shape hiring strategy and define candidate profiles. Build and maintain talent pipelines and lead complex offer negotiations.

RAND
Lead the integration of AI into RAND's research and business processes. Recommend frameworks for AI adoption, design approaches for real projects, and advise on tools and resources. Propose governance and measurement strategies for AI deployment and assess evidence-based measures of success.

Cedars-Sinai
Participate in biomedical research projects using programming, data mining, statistics, and machine learning. Responsibilities include querying databases, data cleaning, deploying models, and leading scientific communication.

GR8_TECH
Design, build, and operate production-grade AI agent infrastructure and services on AWS. Develop agent orchestration, stateful workflows, and implement reliable execution with checkpointing and retries.

Alice
Lead the execution of red-teaming datasets and technical risk reports, ensuring quality assurance across various workflows. Allocate tasks among subject-matter experts and maintain delivery velocity under tight deadlines.

American Institutes for Research
Lead the development and maintenance of the International Data Explorer (IDE), ensuring quality assurance and technical reviews of assessment data. Manage project schedules and deliverables, coordinating tasks across teams and subcontractors.

Xperteez Technology
Evaluate AI models for dual-use biological risks, running technical assessment pipelines and analyzing model behavior. Synthesize findings into clear evaluation reports and risk summaries for partners and regulatory bodies.

Upstart
Develop and evaluate machine-learning models predicting borrower repayment behavior. Apply causal inference and experimentation to assess servicing interventions. Collaborate with Product and Engineering on payment experiences and with Servicing Operations on collections strategy.

Zillow
Own applied-science problems from hypothesis formation to production delivery. Develop and compare machine learning and LLM-based approaches to enhance customer experiences. Build datasets and design experiments linking model quality to business outcomes.

Gramian Consulting Group
Create hardware engineering problems based on industry scenarios, develop reference solutions using simulations and calculations, design tasks requiring quantitative reasoning, and validate engineering models against test data.

Horizon3
Identify and drive research problems at the intersection of AI and cybersecurity. Develop research directions, technical hypotheses, and experimental plans. Design and lead experiments, build prototypes, and evaluate results in collaboration with technical teams.

Tennessee Board of Regents
Lead analyses to understand regional workforce opportunities and employment outcomes. Develop and maintain dashboards and reports translating labor-market information into actionable resources.

FAR.AI
Lead projects in AI safety research, focusing on detecting and preventing deception in models, mitigating risks in frontier AI, and building frameworks for rapid experimentation. Conduct adversarial evaluations and develop tooling for fine-tuning workflows.

SOVRA
Plan and execute a quarterly research agenda aligned with product roadmaps. Establish research protocols, participant recruitment processes, and maintain a searchable insight library.

Humana
Design and execute outcomes studies to evaluate clinical program performance. Apply statistical and epidemiologic methods to analyze large datasets and generate evidence for decision-making.

Pathward, N.A.
Research, design, and develop AI and machine learning models to address business challenges. Identify opportunities for AI technology, optimize existing models, and prepare data for training.

Jobgether
Conduct advanced research and develop scalable reinforcement learning systems for multimodal AI applications. Design and implement reinforcement learning infrastructure, optimize reward modeling strategies, and create training datasets.

FAR.AI
Lead research projects on deception detection and monitoring, defining research questions, setting milestones, and assessing results. Conduct post-training experiments on large models, diagnose issues, and design model organisms.

RTX
Develop and implement research-grade algorithms for RF signal processing. Conduct statistical signal processing, detection techniques, and adaptive signal processing. Model RF propagation and signatures, and apply machine learning for optimal control.

Cleveland Clinic
Research, develop, administer, and evaluate programs/projects for the Division. Oversee AI implementations, promote AI literacy, and collaborate with leaders on enterprise initiatives and budget management.

Microsoft
Drive research agenda development on machine learning in molecular sciences. Develop strategies for integrating large-scale model data from simulations and experiments. Write research code for testing new approaches and prepare technical papers and presentations.

Recursion
Lead AI research initiatives in drug discovery, focusing on scalable biomedical applications. Collaborate with cross-functional teams to develop AI models that integrate real-world data for clinical care and drug discovery.

Volga Partners
Lead market research initiatives to evaluate opportunities for AI and data services in international development. Analyze funding environments, institutional demand, and emerging AI applications.

Redhorse Corporation
Lead AI/ML initiatives for Condition-Based Maintenance Plus (CBM+), ensuring alignment with mission outcomes. Architect scalable data pipelines and oversee data workflows. Design and optimize machine learning models for predictive maintenance.

A-Alpha Bio
Develop AI/ML methods for predicting and engineering protein-protein interactions. Design benchmarks to assess model performance and generate deliverables like data packages and technical reports. Contribute to the company codebase and database, ensuring effective rollout of new capabilities.

Microsoft
Lead research on adversarial AI agents and swarm-like behavior. Build environments to observe agent coordination and develop methods to detect and interrupt offensive agent swarms. Stress-test methods across various conditions to identify evasion paths.

Dscout
Design and validate rubrics for measuring AI performance, ensuring reliability and sensitivity. Develop long-term benchmarks involving real users and tasks, and maintain their integrity over time.

OpenSpace
Design and build agent systems for multi-step tasks across imagery, geometry, and documents. Own the context layer for spatially and temporally indexed site records. Develop tools for locating components, comparing captures, and querying BIM elements.

Lightly AG
Critically evaluate AI-generated ML/AI research papers for scientific contributions, technical correctness, and experimental rigor. Assess novelty and significance of proposed approaches, identify methodological flaws, and evaluate reproducibility and technical soundness.

hum.ai
Own the architecture of the AI model, evaluate and improve current approaches. Apply advanced techniques to analyze large datasets and enhance performance. Conduct experiments to validate ideas and scale successful models for large-scale training.

Shield AI
Collaborate with stakeholders to define AI use cases, analyze processes, and quantify impacts. Produce business cases comparing build vs buy options and track AI solution performance against baselines.

Red Cell Partners
Design and build evaluation frameworks and methodologies for AI models. Develop reward models and feedback systems to measure model behavior. Conduct experiments to assess the impact of datasets on model performance.

SecureBio
Conduct capability and safeguard assessments of emerging AI models, executing evaluation pipelines and analyzing data to identify risks. Manually assess models for biological knowledge and willingness, synthesizing findings into evaluation reports and risk summaries.

Flexera
Design, build, test, deploy, and improve software using AI coding tools. Implement product features, APIs, and integrations while contributing to the software development lifecycle.

Wonderlic
Lead the development of the Jobs Engine, ensuring its architecture and integrity while expanding its capabilities. Collaborate with product managers and engineers to translate scientific requirements into AI systems.

Troveo AI
Monitor and synthesize trends in AI and machine learning, conduct experiments with emerging models and tools, and identify opportunities to enrich existing data assets. Translate research into actionable outputs, advance a research program, and partner with product and engineering teams.

Abbott
Lead the development of AI and ML solutions for complex healthcare problems, collaborating with stakeholders to formalize requirements. Provide technical leadership in designing and deploying AI solutions, while also contributing hands-on to deliverables.
Texas A&M University System
Oversee the Research Intelligence Platform's development and adoption. Conduct performance benchmarking and comparative analyses of research activities. Analyze research expenditures, proposals, awards, and publications.

Edward Jones
Solve complex business problems using advanced algorithms. Design and build custom AI and machine learning models, managing solutions from development to deployment. Apply strong engineering practices including data pipelines and production monitoring.
10,000,000+ more jobs available!