Research Scientist, Agent Robustness Job at Scale (San Francisco)

Research Scientist / Engineer — Multimodal Agent

This is a rare and foundational opportunity to define the future of multimodal A...

Location

United States , Palo Alto

Salary:

250000.00 - 450000.00 USD / Year

Luma AI

Expiration Date

Until further notice

Requirements

Strong foundation in machine learning, foundation models and agentic systems
Deep understanding of agentic systems and approaches in LLM/VLM reasoning, coding models, LLM/VLM tool calling
Hands-on experience with PyTorch and large-scale training (distributed, mixed precision, large datasets)

Job Responsibility

Architect large-scale multimodal agentic models that use reasoning, planning, coding, and tool calling to achieve complex, multi-step multimodal work
Hillclimbing existing tasks and formulating new tasks through data
Design, implement, and run robust data pipelines for constructing, enriching, and filtering massive pixel datasets
Train large-scale multimodal models on massive datasets and GPU clusters
Define and build novel evaluation frameworks to measure multimodal agents

Fulltime

Research Scientist - Large Language Model

This is a rare opportunity to help define the future of large-scale language mod...

Location

United States , Palo Alto

Salary:

250000.00 - 450000.00 USD / Year

Luma AI

Expiration Date

Until further notice

Requirements

Strong foundation in machine learning and large language models
Deep understanding of autoregressive transformers and large-scale training dynamics
Experience with pre-training large models and/or post-training techniques such as instruction tuning, RLHF, preference optimization, or distillation
Hands-on experience with PyTorch and distributed training at scale
Comfortable operating across research and production environments

Job Responsibility

Architect and scale large autoregressive language models
Design improved pre-training objectives to enhance reasoning, knowledge retention, and compositional generalization
Develop mid-training strategies such as continued pre-training, domain adaptation, curriculum learning, and synthetic data integration
Advance post-training techniques, including instruction tuning, preference optimization, reinforcement learning, distillation, and inference-time compute scaling
Study and improve long-context modeling, planning depth, and multi-step reasoning behavior
Curate and construct massive, high-quality text corpora for pre-training
Design synthetic data pipelines for reasoning, tool use, mathematics, coding, and structured problem solving
Develop filtering, mixture weighting, and curriculum strategies that shape emergent capabilities
Formulate new tasks that improve coherence, logical consistency, factual grounding, and robustness
Train frontier-scale language models across large GPU clusters

Fulltime

Ai Research Scientist, Video Generation And Post Training, Fair

Meta is seeking a Research Scientist to join the Fundamental AI Research (FAIR) ...

Location

United States , Menlo Park

Salary:

154000.00 - 217000.00 USD / Year

Staff Applied Research Scientist - Martech AI

We are seeking a highly experienced and strategic Staff Applied Research Scienti...

Location

United States , New York City; Palo Alto; Chevy Chase; Dallas; Seattle; Chicago; Austin

Salary:

130000.00 - 260000.00 USD / Year

Geico

Expiration Date

Until further notice

Requirements

BS in Computer Science, Machine Learning, Statistics, Mathematics, or a related quantitative field, PhD is preferred
At least 6+ years of professional experience delivering applied AI/ML solutions in production, including leading cross-functional initiatives with enterprise impact
Demonstrated ability to leverage LLMs and agentic AI systems to develop and deploy personalized marketing solutions, including individualized content generation, campaign targeting, and optimization of customer engagement/retention/conversion strategies
Strong proficiency in Python and SQL
deep experience with ML frameworks such as PyTorch, TensorFlow, and Scikit-learn
Demonstrated experience establishing KPI frameworks, experimentation, and causal analysis to quantify model impact and inform prioritization
Excellent stakeholder management skills with a track record of driving alignment and adoption across product, engineering, and business teams
Strong written and verbal communication skills
ability to set the right context and explain complex technical topics to varied audiences, including executives

Job Responsibility

Identify High-Impact Opportunities: Proactively surface and shape high-value AI/ML initiatives by engaging with product, engineering, and operations to align technical roadmaps with strategic business goals
Architecture & Technical Direction: Provide architectural leadership for AI/ML solutions impacting multiple stakeholders. Establish standards for scalability, reliability, observability, compliance, and cost efficiency across online and batch systems
Development & Productionization: Lead end-to-end delivery of AI/ML solutions, including model design, data pipelines, feature stores, evaluation, deployment, A/B testing, and monitoring in real-time and batch environments. Ensure clear plans, milestones, and on-time delivery
ROI Measurement & Experimentation: Establish robust mechanisms to quantify business impact, including KPI definition, experimentation frameworks, and causal inference approaches to guide decision-making and prioritize investments
Innovation & Research Integration: Stay current with cutting-edge research in ML, GenAI, and optimization. Prototype and harden novel techniques that push the boundaries of innovation within GEICO’s insurance ecosystem
Set technical direction for multi-quarter research initiatives
build evaluation frameworks, ensure reproducibility/responsible AI, and drive cross-functional adoption
shepherd patents
Cross-Functional Collaboration: Champion collaboration across Product, Engineering, Data Platform, Governance, Legal, and Operations to ensure responsible, compliant, and effective adoption of AI systems
Mentorship & Capability Building: Mentor junior and senior scientists, elevate technical standards (coding, testing, documentation, reproducibility), and foster a culture of scientific rigor and engineering excellence

What we offer

Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family’s overall well-being
Financial benefits including market-competitive compensation
a 401K savings plan vested from day one that offers a 6% match
performance and recognition-based incentives
and tuition assistance
Access to additional benefits like mental healthcare as well as fertility and adoption assistance
Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year

Fulltime

Research Scientist / Engineer — Foundation Model

This is a rare and foundational opportunity to define the future of multimodal A...

Location

United States , Palo Alto

Salary:

Not provided

Luma AI

Expiration Date

Until further notice

Requirements

Strong foundation in machine learning, foundation models and agentic systems
Deep understanding of agentic systems and approaches in LLM/VLM reasoning, coding models, LLM/VLM tool calling
Hands-on experience with PyTorch and large-scale training (distributed, mixed precision, large datasets)
Able to contribute continuous 6 months in the internship

Job Responsibility

Architect large-scale multimodal agentic models that use reasoning, planning, coding, and tool calling to achieve complex, multi-step multimodal work
Design, implement, and run robust data pipelines for constructing, enriching, and filtering agentic datasets
Train large-scale multimodal agents on massive datasets and GPU clusters
Define and build novel evaluation frameworks to measure multimodal agents

Fulltime

Research Scientist II

Microsoft is a company where passionate innovators come to collaborate, envision...

Location

India , Hyderabad

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Master's Degree in relevant field AND 1+ year(s) related research experience
Bachelor's Degree in relevant field AND 2+ years related research experience
OR equivalent experience
Proven ability to communicate complex technical concepts to diverse stakeholders
Ability to meet Microsoft, customer and/or government security screening requirements
Microsoft Cloud Background Check
Doctorate in relevant field OR Master's Degree in relevant field AND 3+ years related research experience OR Bachelor's Degree in relevant field AND 5+ years related research experience OR equivalent experience
Experience publishing academic papers as a lead author or essential contributor
Experience participating in a top conference in relevant research domain
Strong track record in cross-functional product development and delivering measurable impact through data-driven iteration

Job Responsibility

Build and expand collaborative partnerships across product, engineering, and research groups inside and outside Microsoft
Provide growing expertise that accelerates technology transfer, strengthens data security practices, and advances internal tools, benchmarking efforts, patent filings, and whitepaper development
Contribute to cutting-edge research by collaborating with peers and engineering teams to advance existing projects, develop new ideas, and publish high-quality papers
Coauthor or lead publications for top-tier conferences and journals with impact on par with postdoctoral research output
Drive research projects to completion, delivering novel algorithms, prototypes, theories, datasets, tools, or insights that meaningfully advance one or more open research problems
Uphold Microsoft’s commitments to security, ethics, and privacy by incorporating responsible research practices into data collection, experimentation, and system design
Support the development of trustworthy, robust, privacy-preserving, and ethically aligned technologies
Help define clear research problems and goals, contributing to the formulation of compelling problem statements and feasible research plans with measurable impact
Develop deep understanding of the state of the art, tracking new methods, tools, and breakthroughs in the research community
Contribute domain expertise in multiple specialized techniques to guide project planning, scoping, and execution

Fulltime

Data Scientist - Applied AI Research

The Data Scientist - Applied AI Research will ideate, design, and develop NLP ac...

Location

United States , Westlake

Salary:

Not provided

Fidelity Investments

Expiration Date

Until further notice

Requirements

1+ years of Data Science experience, specializing with NLP
1+ years of generative AI experience including LLMs, Agents, MCPs, etc
1+ years of experience working in an Agile environment
1+ years of experience with AWS products in a Linux environment
Experience developing and optimizing solutions from transformer-based, fastText-based or ensemble based models
Experience with Pytorch
Understanding of text representation techniques and classification algorithms
Deep understanding of experiment design and documentation
Statistical acumen and experience applying statistical concepts to data science experiments
Deep knowledge of machine learning algorithms, with the ability to choose the optimal algorithm for a given problem

Job Responsibility

Work closely with the Agile team members to bring ML solutions into the product
Benchmark and optimize existing ML solutions performance (e.g, model footprint or latency)
Deliver reports on a sprint cadence
Peer review code and reports written by teammates
Bring good ideas during brainstorming sessions

Fulltime

Principal/Senior Applied Scientist Security Models Training Team - Next-Gen frontier research

The Security Models Training team is expanding to drive the development of a new...

Location

Israel , Tel Aviv, Herzliya

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

M.Sc. / Ph.D. in Computer Science, Information Systems, Electrical or Computer Engineering or Data Science (Ph.D. strongly preferred)
Candidates with M.Sc. / Ph.D. in related fields with proven industry experience or a strong publication record in the areas of LLM, Information Retrieval, Machine Learning, Natural Language Processing, Time Series Forecasting and Deep Learning are considered as well
Proven hands-on experience of at least 5 years (including post-grad work) in building and deploying Machine Learning products
Key areas of expertise include Natural Language Processing and Large Language Models, along with an understanding of concepts such as Privacy and Responsible AI
Candidates are expected to demonstrate a strong history of successfully translating applied research into production-ready solutions, along with a proven track record of delivering projects within large-scale production environments
Proven expertise in the LLM and/or time-series forecasting domain, demonstrating comprehensive knowledge of relevant concepts in the domain
Ideal applicants should be proficient in areas such as LLM’s pre and post training, including CPT, SFT and RL, LLM benchmarking, agentic flows, and model alignment
Hands-on experience in building neural model architectures at the 100M+ scale and the proficiency to adapt them at all abstraction levels down the individual block (e.g. changing the innerworkings of an attention block, introducing new blocks, or changing the routings)
Demonstrated proficiency in problem-solving and data analysis, with substantial expertise in evaluating the performance of large language models (LLMs) and/or time-series forecasting models, developing benchmarks tailored to practical scenarios

Job Responsibility

Technical Leadership & Ownership: set technical direction for major security domain initiatives
lead security model programs spanning pre‑training, task tuning, reinforcement learning, and evaluation
translate cutting‑edge research into production‑ready capabilities
Advanced Model Design – Building and customizing deep learning model architectures (e.g., modifying transformer blocks, attention/memory modules, etc.) at the SLM/LLM scale
making principled architectural tradeoffs to improve reliability, robustness, and security‑specific behavior
Advanced Model Training – Apply deep expertise in pre-training, post-training, and reinforcement learning (RL) for both language and other modalities, including time-series
Design & Evaluate Datasets – Build high-quality datasets and benchmarks
define objective evaluation frameworks and quality gates
run ablation studies to measure impact and optimize data and training effectiveness to support confident product decisions
Develop Data Infrastructure – Create and maintain scalable pipelines for ingestion, preprocessing, filtering, and annotation of large, complex datasets, with attention to privacy, governance, and long‑term reuse across security scenarios

Fulltime

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Research Scientist, Agent Robustness

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