CHAOS Industries is redefining modern defense with a multi-product portfolio that gives the ultimate advantage—domain dominance. The company's products are powered by Coherent Distributed Networks (CDN™), empowering warfighters, commercial air operators, and border protection teams to act faster, adapt rapidly, and stay ahead of evolving threats. 

CHAOS Industries was founded in 2022 and has raised a total of $1 billion in funding from leading investors, including 8VC, Accel, and Valor Equity Partners. The company is headquartered in Los Angeles, with offices in Washington, D.C., San Francisco, San Diego, Seattle, and London. For more information, please visit www.chaosinc.com.

About the Team: Mission Engineering at CHAOS turns simulation output into decisions. We run large-scale modeling and simulation campaigns across all warfighting domains and the full kill chain, against named threats, in operationally relevant scenarios, at the speed engineering, operational, and customer teams actually need. Every CHAOS engineering trade, pursuit, and customer engagement is anchored in rigorous, physics-based, tactically relevant, and statistically valid analysis, and we're scaling the function to meet that bar across a growing product portfolio.

About the Role: You will own statistical methodology for the Mission Engineering team at CHAOS. You'll design experimental constructs that extract meaningful signals from broad trade studies and computationally expensive simulation runs, build the analytical pipelines the team relies on, push the methodological state of the art on how we characterize uncertainty, build surrogate models, and communicate quantitative results to decision-makers. You will work shoulder-to-shoulder with engineers and experts in every domain to ensure that simulated, experimental, and tactical results presented by CHAOS are rigorous, reproducible, and actually deliver answers that our teams, customers, and partners need

This is a foundational hire. You will have the freedom to move fast and set the standards for how CHAOS does quantitative analysis from day one.

What You'll Do:

• Design rigorous experimental constructs (DOE, space-filling designs, adaptive sampling, sequential experimentation) for large-scale simulation campaigns, getting maximum signal per simulation hour across operationally relevant trade spaces.
• Apply advanced statistical methods (such as regression modeling, Bayesian inference, surrogate/metamodeling, sensitivity analysis, uncertainty quantification, and beyond) to simulation output to produce decision-quality conclusions.
• Build and own scalable Python-based data pipelines for ingestion, processing, statistical analysis, and visualization of large simulation datasets.
• Develop ML and statistical surrogate models that accelerate analysis, enable real-time trade studies, and feed mission planning applications.
• Set team standards for data management, reproducibility, and statistical rigor (such as code review, methodology validation, and documentation practices).
• Translate operational and engineering questions into well-structured analytical approaches alongside M&S engineers, threat SMEs, and program staff. Push back when the framing is wrong.
• Author technical reports and briefing materials with clear, honest data visualizations; present quantitative results to senior technical and non-technical audiences in language they can act on.
• Mentor peers and cross-functional teams on experimental design, statistical methodology, and reproducible analysis.
• Support programs spanning DoD services, DARPA, intelligence community, and commercial customers.

Required Qualifications:

• Bachelor's degree or higher in Statistics, Data Science, Mathematics, Artificial Intelligence, a related quantitative field, or equivalent demonstrated expertise in modern statistical methodology.
• 7+ years applying advanced statistical and data science methods, ideally supporting defense, intelligence, or advanced technology programs.
• Deep working expertise in experimental design, regression and Bayesian methods, uncertainty quantification, and surrogate modeling, not just textbook familiarity.
• Strong proficiency working in Python, including scientific computing and ML libraries (especially Pandas, Polars, NumPy, SciPy, Scikit-Learn, Statsmodels, PyMC, Matplotlib, Seaborn, CuPy, PyTorch), and exposure to MATLAB or R.
• Demonstrated experience building scalable analytical pipelines for large datasets, including comfort with terabyte-scale data and modern dataframe tooling.
• Exceptional data visualization skills and the ability to develop briefing-quality technical products.
• Strong software development practices: version control, code review, reproducible workflows, and informed use of AI-assisted coding tools.
• Track record of working independently, taking ownership of ambiguous problems, and delivering with minimal oversight.
• Comfortable working with Linux operating systems and writing scalable scripts/software.
• Exceptional written and verbal communication skills, especially in translating quantitative approaches and results for non-technical audiences.
• Eligibility to obtain a Top Secret / Sensitive Compartmented Information (TS/SCI) clearance.

Preferred Qualifications:

• Master's or PhD in Statistics, Data Science, Mathematics, Artificial Intelligence, or a related quantitative field.
• Direct experience applying statistical methods to outputs from military simulations including high fidelity engineering models, war games, and engagement or mission-level combat simulations such as AFSIM, ESAMS, Brawler, or Ansys STK.
• Expertise designing and analyzing large-scale Monte Carlo and DOE-driven simulation campaigns supporting full kill chain or system effectiveness assessment.
• Experience in developing surrogate models, simulations, machine learning, or artificial intelligence models for engineering and operations analysis applications.
• Familiarity with sensor performance analysis (radar, EO/IR, RF, acoustic), weapon effectiveness analysis, or mission-level engagement analysis.
• Experience with HPC environments and distributed computing frameworks (including scalable cloud services and GPU-accelerated computing).
• Leadership experience: mentoring or leading project teams through complex analytical efforts.
• Substantial experience in communicating statistical methods to both technical and non-technical stakeholders and decisionmakers.
• Experience supporting rapid development programs for DoD contractors, combatant commands, research labs, and acquisition communities.
• Active TS/SCI clearance.

Why CHAOS?

• Health Benefits: Medical, dental, and vision benefits 100% paid for by the company
• Additional benefits: 401k (+ 50% company match up to 6% of pay), FSA, HSA, life insurance, and more
• Our Perks: Free daily lunch, ‘No meeting Fridays’, unlimited PTO, casual dress code
• Compensation Components: Competitive base salaries, generous pre-IPO stock option grants, relocation assistance, and (coming soon!) annual bonuses
• Team Growth: 250 employees and counting across 5 global offices

The stated compensation range reflects only the targeted base compensation range and excludes additional earnings such as bonus, equity, and benefits. If your compensation requirements fall outside of the range, we still encourage you to apply. The salary range for this role is an estimate based on a range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. 

Recruiting Agencies: CHAOS Industries does not accept unsolicited resumes or outreach. Unsolicited submissions will not be reviewed or compensated.

#LI-onsite

As a Staff Data Scientist, you will lead innovation in experimentation and causal inference, helping shape the future of decision-making and product innovation at SIE. You will drive innovative research in experimentation methodologies while mentoring other team members. You’ll be responsible for elevating our experimentation strategy, fostering a culture of curiosity and rigor, and helping cross-functional teams deliver player-first experiences through strong evidence-based decisions.

What You’ll Be Doing:

• Drive innovation in experimentation research by shaping measurement frameworks and best practices, and by developing new methodologies that enhance the quality, speed, and scalability of experiments.
• Advance experimentation infrastructure and tooling, incorporating statistical and machine learning methods to refine analytical capabilities.
• Mentor and guide less-senior data scientists, building expertise in experimentation and causal inference while providing technical direction to ensure rigor and impact.
• Partner with product managers and business leaders to identify high-impact experimentation opportunities and align them with PlayStation’s strategic goals.
• Act as a thought leader in experimentation and causal inference, evangelizing best practices and fostering learning across teams.
• Contribute to research and prototyping of novel experimentation techniques that address complex real-world challenges, such as user behavior variability and data limitations.
• Champion a data-driven culture by establishing experimentation standards, ethical practices, and reproducibility
• Represent the team’s insights and innovations across the broader data science and product communities within PlayStation.
• Stay at the forefront of the field by monitoring emerging developments in experimentation, causal inference, and applied machine learning to continuously evolve capabilities.

What We’re Looking For:

• Master’s Degree or equivalent experience in Applied Math, Economics, Statistics, Computer Science, or related field. Ph.D. or equivalent experience preferred.
• Strong familiarity with the gaming industry and contemporary gaming experiences.
• 8+ years of experience in data science, including extensive hands-on work in experimentation, with at least 2+ years in a mentoring or technical leadership capacity.
• Proven track record of leading experimentation innovation and scaling frameworks within a dynamic business environment.
• Proficiency in SQL and statistical programming languages (e.g., R or Python), especially for causal inference, experimental analysis, and scalable modeling.
• Expertise in causal inference techniques and designing both randomized and quasi-experiments.
• Demonstrated ability to collaborate cross-functionally and influence data strategies that inform business and product decisions.
• Excellent communication and storytelling skills, especially in conveying complex concepts to non-technical stakeholders.
• Experience working with modern data engineering and visualization tools (e.g., Airflow, Git, Tableau, MicroStrategy).
• A strong sense of ownership and an inclusive leadership style that encourages collaboration and innovation.

Benefits:

• Discretionary bonus opportunity
• Hybrid Working (within Flexmodes)
• Private Medical Insurance
• Dental Scheme
• 25 days holiday per year
• On Site Gym
• Subsidised Café
• Free soft drinks
• On site bar
• Access to cycle garage and showers

Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks.

Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. 

WHAT YOU’LL DO

THE DAY-TO-DAY

• Lead and Define AI Strategy – Set the vision for applied ML research and AI-driven decision-making across Viant’s products and services.
• Drive High-Impact Research – Conduct advanced research in NLP, RL, LLMs, and deep learning, publishing in top-tier conferences while applying findings to real-world production systems.
• Architect and Deploy ML at Scale – Develop, optimize, and deploy high-throughput, low-latency ML models, collaborating with engineers to bring solutions into production.
• Innovate in Generative AI & Causal ML – Explore novel AI techniques, such as LLMs, reinforcement learning, and causal inference, to enhance targeting, personalization, and attribution models.
• Experimentation and Validation – Design, run, and analyze A/B experiments to test ML-driven strategies, ensuring data-driven decision-making.
• Mentor and Influence – Provide technical leadership for a team of applied scientists and ML engineers, fostering a culture of innovation and excellence.

MUST HAVE

• Experience: 4+ years of experience building and deploying machine learning models at scale.
• Technical Leadership: Demonstrated ability to lead complex, high-ambiguity ML projects from research to production.
• Academic & Industry Recognition: Masters + At least two peer-reviewed publications in deep learning, NLP, or a related AI domain or a PhD in Computer Science, Machine Learning, Statistics, or a related quantitative field.
• Deep Expertise in ML & AI: Strong foundation in deep learning, NLP, generative AI, and causal inference.
• Programming & Frameworks: Proficiency in Python and deep learning frameworks (TensorFlow, PyTorch, LangChain, Llama Index).
• Scalability & Cloud: Experience with distributed computing, cloud ML platforms (AWS, GCP, or Azure), and real-time AI inference.

GREAT TO HAVE

• Industry Impact: Publications at top-tier ML/NLP conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, AAAI).
• Ad Tech Expertise: Experience in digital advertising, real-time bidding, or audience modeling.
• Generative AI Applications: Hands-on experience with LLMs and multimodal AI applications.
• Optimization & Personalization: Strong background in reinforcement learning, dynamic pricing, or recommendation systems.

LIFE AT VIANT

Investing in our employee’s professional growth is important to us, but so is investing in their well-being. That’s why Viant was voted one of the best places to work and some of our favorite employee benefits include fully paid health insurance, paid parental leave and unlimited PTO and more. 

#LI-KW1

We are hiring an Applied Scientist to help advance personalization across the Crunchyroll ecosystem. In this role, you will lead the scientific development of recommendation, ranking, and decisioning solutions that improve how fans discover and engage with anime series/movies, manga, merchandise, games, and other areas in the anime fandom. You will partner closely with Machine Learning Engineers, Product, Engineering, Marketing, and Content stakeholders to make Crunchyroll the ultimate destination for anime experience.

About the role

In the role of Senior Applied Scientist for Recommendation and Personalization, you will report to the Director of Data Science and Machine Learning in our Center for Data and Insights. You will own the research and applied science agenda for personalization, from problem framing and data exploration through model development, evaluation, experimentation, and iteration. This role is ideal for someone who enjoys combining strong scientific rigor with product thinking to improve user discovery, engagement, retention, and long-term fan value.

You will work across multiple user touchpoints, including app and web interfaces, lifecycle and promotional email campaigns, and flywheels that connect video, ecommerce, manga, and adjacent experiences. You will help define what great personalization looks like at Crunchyroll, build the evidence to prove impact, and collaborate with engineering partners to ensure the resulting solutions can be productionized effectively.

This position is based in our Los Angeles office, but we will consider our San Francisco office as a secondary location. We work a hybrid schedule, in-office three days a week: Tuesday, Wednesday, and Thursday. 

Core areas of responsibility

• Lead the research and development of recommendation, ranking, retrieval, and personalization methods tailored to Crunchyroll use cases across streaming, manga, ecommerce, and lifecycle marketing surfaces.
• Frame ambiguous business and product questions into clear scientific problems, hypotheses, success metrics, and experimentation plans.
• Design and run robust offline evaluation frameworks for recommender systems, including relevance, diversity, novelty, coverage, calibration, and long-term value metrics.
• Partner with Product, Analytics, and Engineering to define online experiments, interpret results, and turn learnings into roadmap decisions and model improvements.
• Develop user, content, and contextual understanding through feature design, representation learning, segmentation, and behavioral analysis.
• Prototype and evaluate a range of approaches, including collaborative filtering, content-based methods, sequence modeling, deep learning, bandits, causal or uplift methods, and LLM-enabled recommendation techniques where appropriate.
• Analyze user feedback loops and cross-domain interactions to improve discovery across video, merchandise, manga, and other ecosystem experiences.
• Work closely with Machine Learning Engineers to translate promising research into production-ready solutions on our in-house recommendation platform.
• Communicate scientific findings, model tradeoffs, and business implications clearly to technical and non-technical stakeholders.
• Help establish best practices for experimentation, reproducibility, model governance, and scientific documentation within the personalization and recommendations function.

About you

We get excited about candidates, like you, because you have:

Experience: You bring 5+ years of experience in applied machine learning, recommendation systems, search/ranking, experimentation, or a closely related area, with a track record of driving measurable product impact.

Scientific Depth: You have strong foundations in machine learning, statistics, experimental design, and causal thinking, and you know how to choose the right level of modeling complexity for the problem at hand.

Recommendation Expertise: You have hands-on experience with at least some of the following: collaborative filtering, retrieval and ranking systems, representation learning, sequence / generative models, bandits, graph methods, or personalization for consumer products.

Technical Skills: You are highly proficient in Python and comfortable working with common ML libraries such as PyTorch, TensorFlow, Scikit-learn, XGBoost, or similar tooling. Experience working with SQL, distributed data processing, and cloud-based ML workflows is strongly preferred.

Experimentation Mindset: You know how to design offline and online evaluations, reason carefully about metrics, and connect experimental findings to user and business outcomes.

Cross-Functional Collaboration: You have experience partnering effectively with engineers, product managers, analysts, marketers, and business stakeholders to move from idea to execution.

Communication Skills: You can explain sophisticated modeling decisions and ambiguous findings in a clear, decision-oriented way to diverse audiences.

Educational Background: You hold an MS or PhD in Computer Science, Machine Learning, Statistics, Operations Research, Economics, or a related quantitative discipline, or you bring equivalent applied industry experience.

Nice to have

• Experience personalizing content, commerce, media, entertainment, gaming, or subscription products at scale.
• Familiarity with recommender-system failure modes such as popularity bias, cold start, sparse feedback, and feedback loop effects.
• Experience with multi-objective optimization, constrained ranking, or balancing short-term engagement with long-term user value.
• Exposure to generative AI, representation learning, or LLM applications that support recommendation and personalization workflows.
• Published research, patents, or open-source contributions in recommendation systems, personalization, applied machine learning, or experimentation.

About the team

Our centralized DS/ML team serves stakeholders across Finance, Product, Engineering, Marketing, Creatives, and Content Operations with data-driven and ML/AI-powered solutions. Within that broader organization, the Personalization and Recommendation group is building the next generation capabilities to power tailored fan experiences across every major user interface and lifecycle touchpoint. Today, the team includes engineers focused on operationalizing our recommendation platform with strong engineering excellence. This Applied Scientist role complements that foundation by bringing deeper scientific ownership to modeling strategy, evaluation, and experimentation, while partnering closely with an additional MLE hire to accelerate production impact.

Why this role is exciting

• You will help define personalization strategy across multiple surfaces instead of optimizing a single narrow funnel.
• You will work on problems that span content discovery, user engagement, retention, and cross-domain ecosystem value.
• You will influence both what we build and how we measure success, with strong exposure to partners across the business.
• You will join at a formative moment, with the opportunity to shape team standards, technical direction, and long-term roadmap.

Why you will love working at Crunchyroll

In addition to getting to work with fun, passionate and inspired colleagues, you will also enjoy the following benefits and perks:

#LifeAtCrunchyroll #LI-Hybrid

Research Scientists at Riot combine deep technical expertise across machine learning, artificial intelligence (AI), experimental design, and systems engineering to invent new ways players experience games. As a Staff Research Scientist, you push the boundaries of what’s possible and raise the bar for research quality and its translation into extraordinary gameplay.

The Technology Research team performs applied research to accelerate the pace of building amazing player experiences at Riot Games. As a Staff Research Scientist, you will research and develop world models—learned representations that understand, predict, and simulate game environments. Rather than building general-purpose large language models, you will focus on models that capture the structure and dynamics of Riot's games: how state evolves, how players behave, and how design changes ripple through complex systems. Your work will power scalable simulation for agent training, automated game balancing, synthetic data generation, and new forms of language-conditioned game interaction. You will stay deeply hands-on, turning advances in predictive simulation, latent state representations, and environment modeling into concrete prototypes that game teams can evaluate and build on. You will work closely with game teams to ground your research in real gameplay needs and partner across Technology Research to connect world models with game AI and NLP efforts.

Responsibilities:

• Propose, implement, and evaluate world models that learn latent representations of game state, player behavior, and environment dynamics
• Build predictive simulations that enable agent training, game balance testing, and rapid design iteration without full game server overhead
• Develop methods for synthetic data generation and auto-balancing powered by learned environment models
• Explore language-conditioned approaches that combine large language models with state estimators to enable new forms of game interaction
• Work closely with game teams to understand gameplay needs and design constraints, ensuring research is grounded in real player experiences
• Partner with game AI and NLP researchers to integrate world models into broader AI systems across Technology Research
• Stay current with academic and industry advances in world models, predictive simulation, representation learning, and environment modeling (e.g., MuZero, Gato, Dreamer)
• Communicate progress and learnings clearly to stakeholders, helping teams understand both what works and what doesn’t

Required Qualifications:

• Ph.D. in Machine Learning, AI, Statistics, Math, or related Computer Science/Quantitative field, or equivalent experience (i.e., M.Sc. with 3+ years of relevant experience, or B.Sc. with over 6+ years of relevant experience, etc.)
• 2+ years experience in deep learning or algorithmic foundations of optimization
• Experience with generative models, representation learning, model-based reinforcement learning, or learned simulation
• Proficiency in C, C++, or Python
• Expertise with TensorFlow or PyTorch

Desired Qualifications:

• Experience building or training world models, dynamics models, or latent-space simulators (e.g., Dreamer, MuZero, or similar architectures)
• Familiarity with game engines (e.g., Godot, Unity, or Unreal) for prototyping or data collection
• Distributed computing systems design or large-scale model training infrastructure
• Experience with GCP or AWS
• Demonstrated contributions to public research (e.g., publications, talks, open-source projects)

For this role, you'll find success through craft expertise, a collaborative spirit, and decision-making that prioritizes the delight of players. We will be looking at your past studies, experience, and your personal relationship with games. If you embody player empathy and care about players' experiences, this could be your role!

Our Perks:

Riot focuses on work/life balance, shown by our open paid time off policy and other perks such as flexible work schedules. We offer medical, dental, and life insurance, parental leave for you, your spouse/domestic partner, and children, and a 401k with company match. Check out our benefits pages for more information.

At Riot Games, we put players first. That mission drives every decision in our quest to create games and experiences that make it better to be a player. Whether you’re working directly on a new player-facing experience or you’re supporting the company as a whole, everyone at Riot is part of our mission. And just like in our games, we’re better when we work together. Our goal is to create collaborative teams where you are empowered to bring your unique perspective everyday. If that sounds like the kind of place you want to work, we’re looking forward to your application.

It’s our policy to provide equal employment opportunity for all applicants and members of Riot Games, Inc. Riot Games makes reasonable accommodations for handicapped and disabled Rioters and does not unlawfully discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, handicap, veteran status, marital status, criminal history, or any other category protected by applicable federal and state law. We consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with applicable federal, state and local law, including the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, the San Francisco Fair Chance Ordinance, and the Washington Fair Chance Act.

Per the Los Angeles County Fair Chance Ordinance, the following core duties may create a basis for disqualifying candidates with relevant criminal histories:

• Safeguarding confidential and sensitive Company data
• Communication with others, including Rioters and third parties such as vendors, and/or players, including minors
• Accessing Company assets, secure digital systems, and networks
• Ensuring a safe interactive environment for players and other Rioters

These duties are directly related to essential operations, safety, trust, and compliance obligations within our organization. Please note that job duties may evolve based on business needs and additional responsibilities may be assigned as necessary to maintain operational efficiency and security. 

AE Studio builds products, platforms, and internal ventures that increase agency for all conscious beings. We combine world-class software engineering, AI expertise, and product design to ship ambitious projects that matter.

ABOUT THE ROLE

As a Data Scientist at AE Studio, you’ll work on a mix of client projects and internal research initiatives. You’ll solve real-world problems, help build meaningful products, and contribute to groundbreaking AI alignment research. Your work will involve building data-driven solutions, leveraging machine learning models, and using your creativity to deliver results that matter.

In addition to client projects, you’ll have the opportunity to propose and pursue high-impact research projects, especially those aligned with our mission of increasing agency. Promising projects could even become prioritized skunkworks initiatives.

We want problem-solvers who are adaptable, collaborative, and excited to push boundaries. If this sounds like you, let’s talk.

ABOUT YOU

You thrive on solving challenging problems and bring a mix of technical expertise, creativity, and humor to your work. You enjoy working independently but also love collaborating with a team that shares your passion for making a difference.

Required Skills and Experience

• Fluency in Python..
• Experience with LLM lifecycle: prompt design/engineering, prompting techniques (RAG, few-shot, CoT, etc.), vector databases, multimodality, fine-tuning, and evaluation.
• Proven data science experience: You’ve been a key contributor to impactful projects and know how to deliver results with real-life outcomes.
• Statistical & causal ML fundamentals: expertise in experimental design, uncertainty quantification, and rigorous model evaluation across tabular, time-series, and foundation-model fine-tuning tasks.
• Deep learning experience: Expertise in building/training NLP or computer vision models with PyTorch, TensorFlow, or JAX.
• Agile & AI-powered development: You run lean Kanban/Scrum cycles and leverage AI-powered tools like Cursor to prototype quickly and ship high-impact solutions.
• Growth mindset: You embrace challenges, value progress over perfection, and constantly seek to improve.
• Self-management: You can work independently, take ownership of projects, and deliver without constant oversight.
• Product and UX understanding: You care about delivering a seamless, user-friendly experience.
• Effective communication in English: Clear, concise, and maybe even witty communication is essential.

Bonus Points for

• Self-managed projects: Ideally something that you helped develop from zero and shipped to real users.
• Startup experience: You thrive in dynamic environments and enjoy taking on new challenges.
• Client relationship management: Experience managing clients and delivering excellent results.
• Passion for AI alignment: You care deeply about humanity’s future and want to help navigate the challenges of advancing AI.

WHAT WE OFFER

• Remote-first culture: Work from anywhere, or join us in one of our offices.
• Flexible schedules: We care about outcomes, not micromanagement.
• Competitive pay: Regular performance-based raises and a diversified employee equity program.
• Opportunities for growth: Work on cutting-edge R&D and propose projects that could become our next skunkworks focus.
• Supportive environment: A team that collaborates, mentors, and shares knowledge.
• Perks: Health insurance, free lunches (at the office), weekly knowledge-sharing talks, and an annual team retreat.

Salary range is from $120K to $220K per year for people based in California. 

Not in the range? That's fine, you can still apply, and our team may fit you in a more senior position that we're not actively hiring right now, but we are growing fast and may have other openings soon.

EQUITY

Working at AE means receiving equity in our client projects and in Skunkworks ventures. The equity is priced at $0 when granted for tax reasons, but AE invests millions into these projects. Equity comes from reduced margins on client work and internal funding. You get a real stake in the things you help build.

The longer you stay, the more value you create and the more equity you receive. If you leave on good terms, you can retain 20% of your equity by staying engaged. If you spin out a Skunkworks venture, you retain 100%.

AE Studio builds products, platforms, and internal ventures that increase agency for all conscious beings. We combine world-class software engineering, AI expertise, and product design to ship ambitious projects that matter.

ABOUT THE ROLE

As a Data Scientist at AE Studio, you’ll work on a mix of client projects and internal research initiatives. You’ll solve real-world problems, help build meaningful products, and contribute to groundbreaking AI alignment research. Your work will involve building data-driven solutions, leveraging machine learning models, and using your creativity to deliver results that matter.

In addition to client projects, you’ll have the opportunity to propose and pursue high-impact research projects, especially those aligned with our mission of increasing agency. Promising projects could even become prioritized skunkworks initiatives.

We want problem-solvers who are adaptable, collaborative, and excited to push boundaries. If this sounds like you, let’s talk.

ABOUT YOU

You thrive on solving challenging problems and bring a mix of technical expertise, creativity, and humor to your work. You enjoy working independently but also love collaborating with a team that shares your passion for making a difference.

Required Skills and Experience

• Fluency in Python..
• Experience with LLM lifecycle: prompt design/engineering, prompting techniques (RAG, few-shot, CoT, etc.), vector databases, multimodality, fine-tuning, and evaluation.
• Proven data science experience: You’ve been a key contributor to impactful projects and know how to deliver results with real-life outcomes.
• Statistical & causal ML fundamentals: expertise in experimental design, uncertainty quantification, and rigorous model evaluation across tabular, time-series, and foundation-model fine-tuning tasks.
• Deep learning experience: Expertise in building/training NLP or computer vision models with PyTorch, TensorFlow, or JAX.
• Agile & AI-powered development: You run lean Kanban/Scrum cycles and leverage AI-powered tools like Cursor to prototype quickly and ship high-impact solutions.
• Growth mindset: You embrace challenges, value progress over perfection, and constantly seek to improve.
• Self-management: You can work independently, take ownership of projects, and deliver without constant oversight.
• Product and UX understanding: You care about delivering a seamless, user-friendly experience.
• Effective communication in English: Clear, concise, and maybe even witty communication is essential.

Bonus Points for

• Self-managed projects: Ideally something that you helped develop from zero and shipped to real users.
• Startup experience: You thrive in dynamic environments and enjoy taking on new challenges.
• Client relationship management: Experience managing clients and delivering excellent results.
• Passion for AI alignment: You care deeply about humanity’s future and want to help navigate the challenges of advancing AI.

WHAT WE OFFER

• Remote-first culture: Work from anywhere, or join us in one of our offices.
• Flexible schedules: We care about outcomes, not micromanagement.
• Competitive pay: Regular performance-based raises and a diversified employee equity program.
• Opportunities for growth: Work on cutting-edge R&D and propose projects that could become our next skunkworks focus.
• Supportive environment: A team that collaborates, mentors, and shares knowledge.
• Perks: Weekly knowledge-sharing talks, an annual team retreat, and much more.

EQUITY

Working at AE means receiving equity in our client projects and in Skunkworks ventures. The equity is priced at $0 when granted for tax reasons, but AE invests millions into these projects. Equity comes from reduced margins on client work and internal funding. You get a real stake in the things you help build.

The longer you stay, the more value you create and the more equity you receive. If you leave on good terms, you can retain 20% of your equity by staying engaged. If you spin out a Skunkworks venture, you retain 100%.

AE Studio is an LA-based company focused on increasing human agency, primarily by making the imminent AGI future go well. Our team consists of the best developers, data scientists, researchers, and founders. We do all sorts of projects, always of the quality that makes our clients sing our praises. 

We’ve worked with Samsung, Walmart, Berkshire Hathaway, and other large, important entities you’ve probably heard of.  Our work environment is fantastic for aspiring coders, calculators, and entrepreneurs.  Also, we have neither VC, nor PE, nor other acronyms funding us.  We have a weird business model where we sell our work for a profit and use those profits to pay people (I told you it was weird!). We then reinvest those profits into our promising research on AI alignment and our ambitious internal skunkworks projects. We previously sold one of our skunkworks for some number of millions of dollars.

We have made a name for ourselves in cutting-edge brain computer interface (BCI) R&D, and we are making a name for ourselves in our research and policy efforts on AI alignment. We want to optimize for human agency, if you feel similarly, please apply to support our efforts. Data scientists will have the opportunity between client projects to work on important alignment research, with the opportunity to potentially have your research project prioritized if particularly promising.

ABOUT YOU

• Experience with ML or alignment research
• You care about AI alignment, and are optimistic in humanity’s capacity to problem solve and safely navigate accelerating AI capabilities and have an awesome future
• Eager to use AI and automate everything you do
• Comfortable working in a fast-paced, startup-like environment
• Proven data science experience–primary or equal contributor, multiple smaller projects, management of stake-holders.
• Experience working with / building / training deep learning-based computer vision or NLP models or LLMs
• Lots of experience with Python
• Experience calling AI models’ APIs via REST or client libraries
• Growth mindset. Excited about learning new things and solving difficult problems
• Demonstrated ability to work independently/autonomously
• Track record for breaking down complex problems into manageable chunks for individual or team execution
• Full-time availability–but if you have cool side projects that increase human agency, we totally want you to keep working on it...we’ll even help!
• Ability to communicate effectively and work exclusively in English and communicate complex technical concepts clearly to a non-technical audience

BONUS POINTS FOR

• Experience with self-managed data science projects - show us your cool side hustles, especially if they increase human agency
• Experienced with software engineering best practices/software development background
• Agile experience (worked with Kanban, Scrum, Extreme Programming)
• JavaScript / Node.js experience
• Experience managing clients and client relationships
• Experience in startups
• Being in LA to work in person from our amazing office

Salary range is from $120K to $220K per year for people based in California. 

Not in the range? That's fine, you can still apply, and our team may fit you in a more senior position that we're not actively hiring right now, but we are growing fast and may have other openings soon.

EQUITY

Working at AE means receiving equity in our client projects and in Skunkworks ventures. The equity is priced at $0 when granted for tax reasons, but AE invests millions into these projects. Equity comes from reduced margins on client work and internal funding. You get a real stake in the things you help build.

The longer you stay, the more value you create and the more equity you receive. If you leave on good terms, you can retain 20% of your equity by staying engaged. If you spin out a Skunkworks venture, you retain 100%.

Research Scientists at Riot combine deep technical expertise across machine learning, artificial intelligence (AI), experimental design, and systems engineering to invent new ways players experience games. As a Principal Research Scientist, you operate at the frontier of what’s possible and set the standard for how research is conducted and how it translates into extraordinary gameplay.

As a Principal Research Scientist in Tech Research, you will lead a small, cross-functional team focused on building AI-powered gameplay prototypes. These prototypes are not paper exercises, instead they are playable, opinionated explorations of new game mechanics, agent behaviors, and player experiences enabled by modern AI. You will be responsible for identifying promising research directions, translating them into concrete gameplay experiments, and driving them from early concept through working prototypes that influence game teams. You will be the technical and creative lead on complex, ambiguous problems where success requires strong judgment, rapid iteration, and an ability to balance research rigor with hands-on building. You will set the vision and quality bar, leading by example in various capacities, including writing code, shaping robust systems, and mentoring team members. You will lead AI-driven gameplay exploration who is tasked with rapidly testing new ideas through playable prototypes, rigorous evaluation, and real player insight. Your team will identify emerging research with the potential to meaningfully change gameplay, turn it into concrete gameplay experiments, and work with game teams to transform validated breakthroughs into options Riot can confidently commit to.

Responsibilities:

• Define and lead AI-powered gameplay research directions, translating emerging ML/AI capabilities into concrete, playable game prototypes
• Build, lead, and mentor a small cross-functional team, setting technical direction while remaining deeply hands-on
• Own research and prototyping roadmaps, milestones, and risk management for multi-quarter initiatives
• Work closely with game teams to understand player goals and design constraints, ensuring prototypes are grounded in real gameplay needs
• Rapidly iterate on prototypes, balancing research rigor with playability, performance, and developer usability
• Stay current with academic and industry advances in AI for games, reinforcement learning, generative models, and agent systems
• Communicate vision, progress, and learnings clearly to stakeholders, helping teams understand both what works and what doesn’t

Required Qualifications:

• MS in Computer Science or equivalent with 6+ years research experience or BS in Computer Science or equivalent with 8+ years research experience
• Strong background in applied or foundational research, with experience leading projects through hypothesis-driven experimentation
• 2+ years of experience in machine learning for sequential decision-making, agents, or complex systems (e.g., RL, imitation learning, planning, or hybrid approaches)
• Proficiency in C, C++, or Python
• Demonstrated contributions to public research (e.g., publications, talks, open-source projects)
• Experience designing and implementing complex systems that integrate ML with real-time or interactive environments
• Expertise with PyTorch or TensorFlow
• Experience working in commercial game engines for prototyping or production
• Strong understanding of gameplay systems, game loops, and real-time constraints
• Experience collaborating closely with designers and engineers in a game development context

For this role, you'll find success through craft expertise, a collaborative spirit, and decision-making that prioritizes the delight of players. We will be looking at your past studies, experience, and your personal relationship with games. If you embody player empathy and care about players' experiences, this could be your role!

Our Perks:

Riot focuses on work/life balance, shown by our open paid time off policy and other perks such as flexible work schedules. We offer medical, dental, and life insurance, parental leave for you, your spouse/domestic partner, and children, and a 401k with company match. Check out our benefits pages for more information.

At Riot Games, we put players first. That mission drives every decision in our quest to create games and experiences that make it better to be a player. Whether you’re working directly on a new player-facing experience or you’re supporting the company as a whole, everyone at Riot is part of our mission. And just like in our games, we’re better when we work together. Our goal is to create collaborative teams where you are empowered to bring your unique perspective everyday. If that sounds like the kind of place you want to work, we’re looking forward to your application.

It’s our policy to provide equal employment opportunity for all applicants and members of Riot Games, Inc. Riot Games makes reasonable accommodations for handicapped and disabled Rioters and does not unlawfully discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, handicap, veteran status, marital status, criminal history, or any other category protected by applicable federal and state law. We consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with applicable federal, state and local law, including the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, the San Francisco Fair Chance Ordinance, and the Washington Fair Chance Act.

Per the Los Angeles County Fair Chance Ordinance, the following core duties may create a basis for disqualifying candidates with relevant criminal histories:

• Safeguarding confidential and sensitive Company data
• Communication with others, including Rioters and third parties such as vendors, and/or players, including minors
• Accessing Company assets, secure digital systems, and networks
• Ensuring a safe interactive environment for players and other Rioters

These duties are directly related to essential operations, safety, trust, and compliance obligations within our organization. Please note that job duties may evolve based on business needs and additional responsibilities may be assigned as necessary to maintain operational efficiency and security. 

Hi, we're Oscar. We're hiring a Data Scientist II to join our Data team.

Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves - one that behaves like a doctor in the family.

About the role:

Oscar's data team is focused on pushing our understanding of this complex landscape of health care and insurance business. Insurance companies sit on a trove of data that is both broad and deep, spanning financial claims, clinical medical records, and rich product interaction data from our members. Connecting the dots across these datasets gives us unique insight into how the healthcare system functions and allows us to improve care coordination, better manage risk, build higher-performing provider networks, and create a standout consumer experience in our product.

As a Data Scientist II you will drive data science projects across multiple teams and domains. In this role, you’ll take ownership of analytical and modeling work, contribute to technical direction, and partner closely with business, engineering, product and data stakeholders to deliver impactful solutions.

This is a mid-level role for data scientists who can operate independently, manage ambiguity, and apply advanced analytics or modeling techniques with minimal oversight.

​​You will report into a leader on the Data team (Senior Data Scientist and above). This posting is representative of multiple roles, and final team placement will be determined during the interview process.

Work Location: This position is a hybrid role based in our New York City office, Los Angeles Office, or Tempe Office requiring a hybrid work schedule with 3 days of in-office work per week Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. #LI-Hybrid

Pay Transparency: The base pay for this role is: $131,200 - $172,200 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, company equity grants, and annual performance bonuses.

Responsibilities:

• Research, develop, and maintain data pipelines, statistical models, and advanced analytical solutions
• Own projects end-to-end, including problem definition, implementation, validation, and iteration
• Deliver high-quality analytical and modeling outputs with limited manager oversight
• Collaborate closely with data science peers and cross-functional partners across business units
• Help ensure data science processes and outputs align with broader team strategies and roadmaps
• Provide guidance or informal mentorship to junior data scientists or analysts when needed
• Contribute to improving data science practices, tooling, and documentation

Requirements:

• 3+ years of experience in data science, applied analytics, or a related quantitative field (industry, academia, or both)
• 2+ years of experience using SQL and Python and/or R to query, analyze, and manipulate data
• 2+ years of experience building data models, using more advanced analytics methods, statistical modeling, and/or data processing

Bonus points:

• Master’s degree in a quantitative or technical field
• Knowledge of or previous work experience in health care or health insurance
• Experience mentoring or supporting junior team members
• Experience deploying or supporting models in production environments

Hi, we're Oscar. We're hiring a Data Scientist II to join our Data team.

Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves - one that behaves like a doctor in the family.

About the role:

Oscar's data team is focused on pushing our understanding of this complex landscape of health care and insurance business. Insurance companies sit on a trove of data that is both broad and deep, spanning financial claims, clinical medical records, and rich product interaction data from our members. Connecting the dots across these datasets gives us unique insight into how the healthcare system functions and allows us to improve care coordination, better manage risk, build higher-performing provider networks, and create a standout consumer experience in our product.

As a Data Scientist II you will drive data science projects across multiple teams and domains. In this role, you’ll take ownership of analytical and modeling work, contribute to technical direction, and partner closely with business, engineering, product and data stakeholders to deliver impactful solutions.

This is a mid-level role for data scientists who can operate independently, manage ambiguity, and apply advanced analytics or modeling techniques with minimal oversight.

​​You will report into a leader on the Data team (Senior Data Scientist and above). This posting is representative of multiple roles, and final team placement will be determined during the interview process.

Work Location: This position is a hybrid role based in our New York City office, Los Angeles Office, or Tempe Office requiring a hybrid work schedule with 3 days of in-office work per week Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. #LI-Hybrid

Pay Transparency: The base pay for this role is: $131,200 - $172,200 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, company equity grants, and annual performance bonuses.

Responsibilities:

• Research, develop, and maintain data pipelines, statistical models, and advanced analytical solutions
• Own projects end-to-end, including problem definition, implementation, validation, and iteration
• Deliver high-quality analytical and modeling outputs with limited manager oversight
• Collaborate closely with data science peers and cross-functional partners across business units
• Help ensure data science processes and outputs align with broader team strategies and roadmaps
• Provide guidance or informal mentorship to junior data scientists or analysts when needed
• Contribute to improving data science practices, tooling, and documentation

Requirements:

• 3+ years of experience in data science, applied analytics, or a related quantitative field (industry, academia, or both)
• 2+ years of experience using SQL and Python and/or R to query, analyze, and manipulate data
• 2+ years of experience building data models, using more advanced analytics methods, statistical modeling, and/or data processing

Bonus points:

• Master’s degree in a quantitative or technical field
• Knowledge of or previous work experience in health care or health insurance
• Experience mentoring or supporting junior team members
• Experience deploying or supporting models in production environments

Hi, we're Oscar. We're hiring a Data Scientist II to join our Data team.

Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves - one that behaves like a doctor in the family.

About the role:

Oscar's data team is focused on pushing our understanding of this complex landscape of health care and insurance business. Insurance companies sit on a trove of data that is both broad and deep, spanning financial claims, clinical medical records, and rich product interaction data from our members. Connecting the dots across these datasets gives us unique insight into how the healthcare system functions and allows us to improve care coordination, better manage risk, build higher-performing provider networks, and create a standout consumer experience in our product.

As a Data Scientist II you will drive data science projects across multiple teams and domains. In this role, you’ll take ownership of analytical and modeling work, contribute to technical direction, and partner closely with business, engineering, product and data stakeholders to deliver impactful solutions.

This is a mid-level role for data scientists who can operate independently, manage ambiguity, and apply advanced analytics or modeling techniques with minimal oversight.

​​You will report into a leader on the Data team (Senior Data Scientist and above). This posting is representative of multiple roles, and final team placement will be determined during the interview process.

Work Location: This position is a hybrid role based in our New York City office, Los Angeles Office, or Tempe Office requiring a hybrid work schedule with 3 days of in-office work per week Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. #LI-Hybrid

Pay Transparency: The base pay for this role is: $131,200 - $172,200 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, company equity grants, and annual performance bonuses.

Responsibilities:

• Research, develop, and maintain data pipelines, statistical models, and advanced analytical solutions
• Own projects end-to-end, including problem definition, implementation, validation, and iteration
• Deliver high-quality analytical and modeling outputs with limited manager oversight
• Collaborate closely with data science peers and cross-functional partners across business units
• Help ensure data science processes and outputs align with broader team strategies and roadmaps
• Provide guidance or informal mentorship to junior data scientists or analysts when needed
• Contribute to improving data science practices, tooling, and documentation

Requirements:

• 3+ years of experience in data science, applied analytics, or a related quantitative field (industry, academia, or both)
• 2+ years of experience using SQL and Python and/or R to query, analyze, and manipulate data
• 2+ years of experience building data models, using more advanced analytics methods, statistical modeling, and/or data processing

Bonus points:

• Master’s degree in a quantitative or technical field
• Knowledge of or previous work experience in health care or health insurance
• Experience mentoring or supporting junior team members
• Experience deploying or supporting models in production environments

Xometry is seeking a Principal Data & ML Scientist to join our Generative AI team. The ideal candidate will have a passion for advancing machine learning and generative AI capabilities, particularly for fine-tuning generative and language models, multimodal document understanding, and structured data extraction. This person will leverage their expertise in generative models and data science to develop and optimize innovative AI-driven solutions that enhance Xometry's service offerings.

Responsibilities: 

• Provide technical leadership to the Generative AI team, setting technical direction, defining best practices, and ensuring the team follows industry standards in AI and ML development.
• Lead strategic planning and roadmap development for generative AI initiatives, identifying high-impact projects and aligning them with Xometry’s business objectives.
• Develop and deploy generative AI models and large language models (LLMs) for multimodal document processing, focusing on extracting structured data from technical drawings, purchasing orders, and other complex documents.
• Lead the exploration and development of innovative text and image-based data processing solutions, including training and fine-tuning generative and language models.
• Design and implement efficient workflows for data preparation, cleaning, and augmentation to support the training of generative AI models.
• Utilize cloud platforms (e.g., Amazon Web Services) for large-scale data processing, model training, and deployment.
• Collaborate with cross-functional teams, including engineering and business teams, to align generative AI solutions with business needs and drive impactful applications.
• Mentor and guide team members on advanced machine learning techniques, model architecture design, and problem-solving strategies to elevate the team’s technical capabilities.
• Continuously experiment and iterate on model performance, tuning architectures and parameters to improve accuracy and efficiency in a fast-paced, agile environment.
• Stay updated with the latest research in generative AI, deep learning, and multimodal data processing, incorporating best practices and advancements into model development.

Qualifications:

• A bachelor’s degree is required, but an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is highly preferred.
• 7+ years of experience in data science and machine learning, focusing on generative models, LLMs, or computer vision.
• Expertise in large-scale language and vision models (e.g., Transformers, GPT, VLMs).
• Experience with multimodal data processing (e.g., combining text, image, and 3D data).
• Proficient in Python, including key libraries such as PyTorch, TensorFlow, pandas, and numpy.
• Strong background in probability, statistics, and optimization techniques relevant to generative modeling.
• Familiarity with cloud computing resources and tools for model training and deployment (e.g., AWS SageMaker).
• Familiar with software engineering principles, including version control, reproducibility, and continuous integration.
• Experience in the manufacturing, supply chain, or similar industries is a plus.

The estimated base salary range for new hires into this role is $164,000- $213,000 annually + annual bonus depending on factors such as job-related skills, relevant experience, and location. We also offer a competitive benefits package, including 401(k) match, medical, dental and vision insurance; life and disability insurance; generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave; EAP, other wellbeing resources; and much more.

#LI-Hybrid