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: On the Mission Engineering team at CHAOS, you will design, develop, execute, analyze, and validate models and simulations to deliver operational analysis and system performance assessment across defense, national security, and commercial programs. You will have freedom to move rapidly and use your expertise to apply rigorous statistical methods to analyze simulation outcomes, quantify system effectiveness, and communicate actionable insights to technical teams, leadership, and customers. Your work will directly inform critical decisions around sensor performance, mission planning, weapon effectiveness, and platform capability evaluation.

This is a foundational hire. You will shape how CHAOS does mission analysis from day one, and you will have the freedom to move fast.

What You'll Do:

• Scope, plan, and execute modeling and simulation efforts and studies aligned to program objectives, managing your competing priorities and timelines effectively.
• Develop, configure, and execute analysis using mission-level models and simulations such as AFSIM, ESAMS, Brawler, Ansys STK, and/or physics-based models to evaluate system and platform performance in operationally relevant scenarios.
• Build and refine models of sensors, communications systems, aircraft (including unmanned), weapons, and spacecraft within mission-level simulation frameworks.
• Architect, implement, and validate models of both blue and red systems, sensors, communications, weapons, aircraft, spacecraft, and ground/maritime platforms, within mission- and engagement-level simulation frameworks.
• Define and apply rigorous statistical methodologies to simulation results to quantify measures of effectiveness and performance to produce relevant and defensible findings for internal and external stakeholders.
• Develop and maintain Python-based analysis tools and pipelines for data processing, statistical analysis, and visualization.
• Implement technical methodology, simulation best practices, and customer engagement.
• Document methodology, assumptions, and findings in technical reports and briefing materials, including data visualizations, and present results to both technical and non-technical audiences.
• Partner with engineering, product, growth, and customer teams to translate operational questions into well-structured analytical approaches and shape new business pursuits. Push back when the framing is wrong.

Minimum Requirements:

• Bachelor's degree or higher in Computer Science, Aerospace/Software/Computer Engineering, Data Science, Statistics, Mathematics, Operations Research, Physics, or a related field.
• 5+ years of experience supporting defense, intelligence, or advanced technology programs through industry or government employment.
• Demonstrated track record leading mission-level operations analysis studies and delivering decision-quality results to senior engineering and customer stakeholders.
• Extensive direct experience with combat simulations such as AFSIM, ESAMS, Brawler, Ansys STK, or equivalent, including ownership of rigorous methodology, not just execution.
• Significant experience developing analytical tools and applying rigorous statistical methods to interpret and present results.
• Strong proficiency in Python and MATLAB, including standard scientific computing libraries (such as Pandas, Polars, NumPy, SciPy, Scikit-Learn, Matplotlib, Seaborn, CuPy, or PyTorch).
• Exceptional data visualization skills and comfort developing CONOPS/OV-1 visuals and briefing packages.
• Proficiency with software development practices including version control and leveraging/validating outputs of AI-assisted coding tools.
• Demonstrated ability to lead analytical efforts and deliver products with minimal oversight, including leading projects and studies.
• Comfortable working on Linux-based systems and writing scalable scripts and software.
• Exceptional written and verbal communication skills, including experience briefing flag/general officer or SES-level audiences.
• Eligibility to obtain a Top Secret / Sensitive Compartmented Information (TS/SCI) clearance 

Preferred Requirements:

• Active TS/SCI clearance.
• Recognized expertise analyzing the full kill chain (find, fix, track, target, engage, assess) across multiple domains, including air-to-air, air-to-surface, surface-to-air, space, and electronic warfare engagements.
• Deep expertise in sensor performance analysis (especially radar) and in developing and validating models of sensors, communications, weapons, aircraft, spacecraft, or ground/maritime systems in mission-level simulation environments such as AFSIM or Ansys STK.
• Experience leading study teams or technical working groups across organizations, including model accreditation, V&V efforts, or threat-informed scenario development.
• Experience designing and analyzing large-scale Monte Carlo and DOE-driven simulation campaigns supporting system effectiveness or kill chain assessment.
• Exposure to Distributed Interactive Simulation (DIS) networking and visualization tools such as MAK VR-Forces, SIMDIS, or similar.
• Experience supporting rapid development programs across DoD services, DARPA, ONR, AFRL, COCOMs, the acquisition community, or commercial advanced technology programs.
• Experience supporting capture and positioning activities (RFI/RFP responses, white papers, technical exchanges) and shaping new business pursuits.

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

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

Riot engineers bring deep knowledge of specific technical areas but also value the opportunity to work in a variety of broader domains.  We work with both new and current technology, creating innovative solutions to solve complex, large-scale challenges and deliver player value.  As a Principal Software Engineer, you’ll lead the development of key features and model high standards of engineering excellence. 

As a Principal Software Engineer on Riot’s AI Enablement team, you are a technical force multiplier. You will embed directly with any team at Riot to accelerate their adoption of modern AI development (e.g., generative AI, LLMs, reinforcement learning). Operating as part of an elite, highly mobile strike team, you will build production-ready AI integrations, develop robust developer tools, and level up partner engineers through side-by-side collaboration. Once a team is empowered and systems are successfully handed off, you will deploy to the next challenge. You will be at the forefront of cutting-edge AI in the game industry, bridging the gap between new technologies and live environments to shape how Riot develops products and games. You will be accountable to Riot’s Head of AI Product.

Responsibilities:

• Implement and Integrate: Lead the technical execution of integrating modern AI practices into existing engines, tools, and pipelines.
• Embed and Accelerate: Deploy onto partner teams across Riot to break down complex AI implementation problems, establish technical direction, and deliver scalable, highly performant solutions.
• Mentorship and Handoff: Train and coach embedded team engineers through pair programming, technical reviews, and hands-on collaboration. Ensure a seamless transition of code ownership before deploying to your next assignment.
• Evangelize Best Practices: Share engineering best practices, security guardrails, and performance standards for AI usage across Riot’s development ecosystem.
• Build Foundations: Identify when industry-standard tools are insufficient and develop new foundations, middleware, or APIs to connect AI research with practical development.
• Manage Ambiguity: Actively navigate highly complex, uncharted technical spaces, communicating trade-offs and building consensus among engineering and product leadership.

Required Qualifications:

• BS in Computer Science (or equivalent experience) with 8-12 years of software engineering experience.
• Extensive experience with systems integration, technical leadership, and early-stage software development.
• Deep programming proficiency in C++ and at least one other language (e.g., Python, C#).
• Shipped at least one AAA game or large-scale, high-concurrency live service product.
• Proven track record of managing high ambiguity, setting technical strategy, and leading multi-month/year initiatives.
• Practical experience utilizing, integrating, or building modern AI tools, APIs, or infrastructure.

Desired Qualifications:

• Experience extending or developing within Unreal Engine (C++).
• Familiarity with ML frameworks (e.g., PyTorch, TensorFlow) or LLM orchestration.
• Background working on shared engine technology, central tools, or platform engineering teams.
• Familiarity with the Runeterra and VALORANT IPs.

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. 

Riot Data Scientists combine their wide technical expertise across data processing, automation, machine learning ("ML"), artificial intelligence ("AI"), and experimental design to inform decisions and develop data-powered products.

As a Principal Machine Learning Engineer on the Publishing Platform Data team, you will define and drive the modeling architecture that powers personalization, matchmaking, and social experiences across Riot’s player ecosystem. You’ll partner closely with Product, Data Engineering, and Software Engineering to transform large-scale social graph, matchmaking, and behavioral data into adaptive, fair, and player-centric AI systems. Your work shapes how players connect, discover communities, and experience matchmaking that feels meaningful and equitable.

Responsibilities:

• Define and lead the modeling architecture for personalization, matchmaking, social graph recommendations, and player/community discovery.
• ‘Architect multi-model systems combining skill, preference, trust, and safety signals for fair and meaningful matchmaking
• Develop models for skill inference, player behavior prediction, trust & safety signals, and multi-objective optimization across fairness, latency, and experience quality.
• Build and optimize real-time inference systems for personalized content, store offers, matchmaking, and player interactions at global scale.
• Drive adoption of advanced modeling approaches including contextual bandits, reinforcement learning, graph ML, and session-aware personalization.
• Partner with Data Engineering and Product to shape data schemas, feature pipelines, telemetry standards, and model observability across the ML lifecycle.
• Define Responsible AI standards and implement fairness audits, bias mitigation, transparency, and safety mechanisms for matchmaking and social systems.
• Lead post-launch evaluations of algorithmic impact on player sentiment, community health, and ecosystem stability.
• Set organization-wide standards for model optimization (latency, throughput, memory), multi-model orchestration, and drift detection.
• Mentor senior ML engineers and data scientists, influencing system design, experimentation strategy, and modeling craft across organizations.
• Represent the ML discipline in cross-functional design reviews, driving alignment on technical decisions, data contracts, and long-term strategy

Required Qualifications:

• 10+ years in ML/Applied AI; 3+ years in principal/staff-level technical leadership.
• Experience with large-scale, real-time ML systems (recommendations, personalization, matchmaking).
• Expertise in graph ML, RL, and representation learning.
• Proficiency in PyTorch, TensorFlow, JAX, and modern data/serving tools (Ray, Kafka, Flink, Redis).
• Strong grounding in A/B testing, experiment design, and experience metrics.
• Track record of setting ML strategy and standards across teams.

Desired Qualifications:

• Professional background in gaming, player modeling, or social ecosystems.
• Experience with trust & safety, toxicity detection, or community health models.
• Familiarity with Vertex AI, SageMaker, or internal large-scale inference systems.
• Experience integrating ML systems with live-service game backends.

For this role, you'll find success through craft expertise and a collaborative spirit that prioritizes the delight of players. We will look at your past studies and experience, but for this role, we also look for dedicated people with a personal relationship with games. If you embody player empathy and care about players' experiences, this is the role for you!

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. 

About the Role:

The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding, and ads optimization that shape the future of streaming.

We are seeking a Director of Machine Learning Engineering and Infrastructure to lead a hybrid team bridging advanced ML engineering with world-class infrastructure design. In this role, you will own the strategic direction and execution for scaling our machine learning capabilities while ensuring our distributed systems and infrastructure can support innovation at massive scale. You will combine technical depth with leadership excellence to guide teams that deliver both foundational ML systems and high-performance distributed services.

What You'll Do: 

• Lead and manage high-performing teams across ML engineering and ML infrastructure, fostering a culture of innovation, collaboration, and growth.
• Define and execute the strategic roadmap for ML systems, including recommendation, personalization, and ads optimization.
• Oversee the design, development, and deployment of scalable ML pipelines: data ingestion, feature engineering, model training, evaluation, and serving.
• Architect distributed systems to support ML workloads at scale, ensuring reliability, observability, and operational excellence.
• Partner closely with Product, Engineering, and Content teams to align on business goals and deliver impactful ML-driven experiences.
• Support best practices in experimentation, evaluation, and ML system monitoring.
• Ensure cost efficiency, scalability, and performance in ML infrastructure investments.

Your Background:

• 10+ years of industry experience spanning machine learning engineering and distributed systems.
• 3+ years of leadership and management experience, with a proven ability to build and lead strong technical teams.
• MSc or Ph.D. in Computer Science, Machine Learning, or related field, or equivalent practical experience.
• Proven expertise in building and deploying end-to-end ML systems at scale, including recommendation and personalization systems.
• Strong background in distributed systems architecture, including low-latency services, streaming platforms, and large-scale serving.
• Hands-on experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and ML infrastructure technologies.
• Track record of delivering high-quality, scalable, and fault-tolerant systems.
• Excellent communication skills and ability to influence product and technical strategy.
• Proven experience deploying large-scale serving systems on AWS and demonstrated expertise in leveraging Databricks for large-scale data processing and ML workflows

About the Role:

The Machine Learning team at Tubi drives the innovation behind personalized user experiences.  With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding and ads optimization that shape the future of streaming.

We are seeking a highly skilled Machine Learning Engineer to contribute to transformative projects in video personalization. In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy. As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross-functional teams to develop and optimize machine learning-driven solutions.

What You'll Do:

• Lead the design, development, and implementation of advanced recommendation systems and algorithms for a global audience
• Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas
• Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment
• Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences.
• Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement

Your Background:

• 8+ years of industry experience building production Machine Learning systems
• MSc or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field
• Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks
• Proficiency in building and deploying full-stack machine learning pipelines: data extraction, data mining, model training, feature development, testing, and deployment.
• Solid understanding of statistical concepts such as hypothesis testing, regression analysis, and performance evaluation metrics for machine learning.
• Ability to deep dive into individual components and systems, as well as understand the overall architecture of machine learning solutions.

#LI-Hybrid #LI-SC1

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

About the role

In the role of senior machine learning engineer, you will report to the director of data science and machine learning in the Center for Data and Insights, working from Los Angeles or San Francisco area in California.

In this Machine Learning Engineer role focused on Algorithm Development and End-to-End Production at our VOD streaming company, you will lead the creation and deployment of scalable ML models to detect account sharing fraud, drawing from user behavior data like geolocation, concurrent sessions, and device profiles. This position is essential for collaborating with data scientists, product analysts, and data engineers,  translating research prototypes into production systems that enhance detection accuracy while minimizing user disruption, aligning with proven strategies from streaming giants to boost subscriber growth.

We work a hybrid schedule, in-office three days a week; Tuesday, Wednesday, Thursday. 

Core Areas of Responsibility

• Design and implement machine learning algorithms, including anomaly detection models, to identify unauthorized account sharing in real-time.
• Develop end-to-end ML pipelines for data preprocessing, model training, evaluation, and deployment using cloud platforms.
• Optimize models for performance, scalability, and efficiency to handle high-volume streaming data.
• Integrate ML solutions with existing systems via APIs and establish monitoring for model drift and retraining.
• Collaborate on A/B testing and iteration to refine algorithms based on feedback and evolving evasion tactics.

About You

• Experience: You bring 5+ years of hands-on experience in ML engineering, with a track record in fraud or anomaly detection systems, ideally in online, consumer facing products and services.
• Technical Skills: Expert in Python and frameworks like TensorFlow, PyTorch, or XGBoost, with proficiency in MLOps tools such as MLflow, Docker, and cloud services like AWS SageMaker, Databricks MLFlow, etc. Experience with cloud computing infra and tooling such as AWS/GCP.
• Cross-Functional Collaborations: Experienced in working with data scientists, engineers, and product teams to deploy models that support business goals like revenue optimization.
• Communication Skills: Strong ability to document technical processes and explain algorithm decisions to diverse stakeholders for seamless integration.
• Education Background: Possess a master's degree in computer science, machine learning, or a related quantitative field, with certifications in cloud ML being a plus.
• Communication Skills: Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

Educational Background: Graduate degree (MS or PhD) in Computer Science, Statistics, or a related field.

About the Team

Our team is composed of passionate Machine Learning Engineers and Data Scientists who have already made a significant impact across our product offerings, content strategy, and user engagement metrics. As we expand our scope, our team is poised to become the cornerstone of innovation and growth across various business verticals within the company. We are dedicated to leveraging advanced machine learning techniques to continue transforming how users interact with and enjoy our offering of video contents and all other services.

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

About the role

In the role of Senior Machine Learning Engineer for Recommendation and Personalization, you will report to the Director of Data Science and Machine Learning in the Center for Data and Insights, working from Los Angeles or San Francisco area in California. You will lead the research, development, and test of advanced models, and work together with product and engineering partners to deliver tailored experiences for our fans across the anime ecosystem, including anime video recommendations, digital manga suggestions, merchandise personalization, anime-themed gaming, music, and more. This position will collaborate closely with scientists, engineers, product owners, to prototype innovative algorithms, evaluate their impact, and integrate them into production systems that drive user engagement, retention, discovery, and satisfaction.

We work a hybrid schedule, in-office three days a week; Tuesday, Wednesday, Thursday. This position can be based in our Los Angeles or San Francisco offices.

Core Areas of Responsibility

• Research, design, and implement machine learning algorithms for recommendation systems, including collaborative filtering, content-based models, and deep learning, and generative recommendation approaches to personalize content discoveries.
• Co-develop end-to-end ML pipelines for data ingestion, feature engineering, model training, evaluation, and deployment using scalable cloud platforms with engineers.
• Optimize models for accuracy, latency, and scalability to handle massive user interaction data from streaming and multi-platform, multi-domain experiences across the fandom.
• Integrate personalization solutions with other services, and implement monitoring for model performance, bias detection, and automated retraining.
• Collaborate on A/B testing, experimentation, and iterative improvements to refine recommendations based on user feedback and evolving content trends.

About You

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

Experience: You bring 8+ years of hands-on experience in applied machine learning, with a proven track record in building recommendation systems or personalization engines, ideally in media, entertainment, or e-commerce platforms.

Technical Skills: Expert in Python and frameworks like TensorFlow, PyTorch, or Scikit-learn, with proficiency in MLOps tools such as MLflow, Docker, and cloud services like AWS SageMaker, Databricks, or similar. Experience with big data tools (e.g., Spark) and cloud infrastructure (e.g., AWS/GCP) for handling large-scale datasets.

Cross-Functional Collaborations: Experienced in partnering with data scientists and analysts, engineers, and product teams to deploy models that align with business objectives like increasing user retention and content consumption.

Communication Skills: Strong ability to document research findings, explain algorithmic choices, and present results to diverse stakeholders for effective adoption.

Educational Background: Graduate degree (MS or PhD) in Computer Science, Machine Learning, Statistics, or a related quantitative field, with publications or contributions in recommendation systems being a plus.

About the Team

Our team is composed of passionate Machine Learning Engineers and Data Scientists who have already made a significant impact across our product offerings, content strategy, and user engagement metrics. As we expand our scope, our team is poised to become the cornerstone of innovation and growth across various business verticals within the company. We are dedicated to leveraging advanced machine learning techniques to continue transforming how users interact with and enjoy our offering of video contents and all other services.

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

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

About the role

In the role of Data Scientist, you will report to the Director of Machine Learning and Data Science. We are considering applicants for the location(s) of Los Angeles, CA or San Francisco.

We are seeking a Data Scientist with skills and experience in using User Behavior Analytics and Modeling to kick start our effort to detect and deter account sharing by leveraging platform-collected data such as login patterns, device usage, IP addresses, and viewing behaviors. This position focuses on uncovering insights from large datasets to inform machine learning models that identify anomalous sharing activities, ultimately supporting revenue growth and subscriber retention strategies inspired by industry leaders like Netflix and Disney+.

Core Areas of Responsibility

• Conduct exploratory data analysis on user session logs to establish baselines for normal and anomalous behaviors.
• Develop predictive models using statistical and machine learning techniques to forecast and segment user sharing patterns.
• Design and conduct experiments to validate the model accuracy and operations effectiveness.
• Collaborate with cross-functional teams to define data requirements and create frameworks for ongoing behavioral monitoring.
• Build visualizations and reports to communicate insights on user engagement and potential sharing risks to stakeholders.
• Ensure data privacy compliance while optimizing data pipelines for efficient operations.

About You

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

• Experience: You have 5+ years in data science roles focused on behavioral analytics, preferably in tech or streaming industries, with proven success in user behavior modeling, anomaly and fraud detection, and related applications.
• Technical Skills: Proficient in Python for data analysis and modeling, SQL for database querying, and tools like Tableau or matplotlib for visualization, with experience in machine learning libraries such as xgboost, scikit-learn, and pytorch for modeling.
• Cross-Functional Collaborations: Skilled at partnering with engineering, product, and legal teams to align analytics with business objectives and integrate findings into product features.
• Communication Skills: Adept at presenting complex behavioral insights in clear, actionable formats to non-technical audiences through reports and visualizations.

Education Background: Hold a master's degree in data science, statistics, computer science, or a related field, with coursework in behavioral economics or psychology being advantageous.

About the Team

You will join an interdisciplinary team of Data Scientists, Machine Learning Engineers, and AI Engineers, united by a passion for leveraging data and ML/AI to create transformative solutions. Our team delivers both consumer-facing product features that enhance the streaming experience for millions of users and stakeholder-oriented solutions that empower internal teams with actionable insights. From building personalized recommendation systems to developing innovative tools like our stakeholder-facing chatbot, we combine cutting-edge machine learning, robust data pipelines, and advanced AI to drive impact across the organization. Collaboration, creativity, and a commitment to excellence define our team’s culture as we work together to push the boundaries of what’s possible in streaming and data-driven decision-making.

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: 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 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%.

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. 

THE OPPORTUNITY

Silvus is seeking a Machine Learning Engineer who will report to the R&D Director, Machine Learning on the R&D team.  The successful individual in this role will focus on applying machine learning and data-driven techniques to improve the performance, efficiency, and adaptability of Silvus’ advanced MIMO radios and wireless networking systems.  This individual will work closely with experts in wireless communications, DSP, networking, and embedded systems to develop ML-driven features that solve real-world problems in dynamic and challenging RF environments.

This position is based at Silvus Technologies’ headquarters in the heart of vibrant West Los Angeles, CA, and is on a hybrid schedule.  A minimum of 3 days onsite per week is expected. On-site days are Mondays, Wednesdays, and Thursdays.

The following is a list of at least some of the current essential job functions of the position. Management may assign or reassign duties and responsibilities at any time at its discretion.

ROLE AND RESPONSIBILITIES

• Research, design, and implement machine learning algorithms to enhance performance in wireless communication systems (e.g., link adaptation, interference mitigation, anomaly detection, spectrum sensing).
• Analyze real-world radio frequency datasets to extract insights and develop predictive models.
• Develop software prototypes and integrate ML algorithms with Silvus’ radio firmware and networking stack.
• Collaborate with cross-functional teams to define machine learning use cases and evaluate the impact of deployed models.
• Contribute to the design of data pipelines and infrastructure for training, testing, and validating models.
• Participate in performance benchmarking and iterative improvement cycles.
• Stay current with the latest Machine Learning research for wireless and embedded systems.
• Perform other related duties of which the above are representative.

REQUIRED QUALIFICATIONS

• S. or Ph.D. in Electrical Engineering, Computer Science, or a related field.
• Minimum of 3 years of experience in machine learning, with demonstrated application to real-world problems; 1 year of machine learning experience with a PhD.
• Strong foundation in supervised and unsupervised learning, signal processing, and statistical modeling.
• Experience with Python ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn, etc.).
• Familiarity with wireless communication concepts (e.g., PHY/MAC layers, MIMO, OFDM, spectrum access, SDRs).
• Proficiency in MATLAB or C/C++ for signal processing algorithm development.
• Security Clearance: Active U.S. Government SECRET clearance or the ability to obtain one within 15 months of hire.
• Must be a U.S. Citizen due to clients under U.S. government contracts.
• All employment is contingent upon the successful clearance of a background check and drug test.

PREFERRED KNOWLEDGE, SKILLS, AND ABILITIES

• Demonstrated experience with radio frequency signal classification, anomaly detection, or spectrum monitoring.
• Familiarity with embedded machine learning, real-time systems, or deploying machine learning on edge devices.
• Background in adaptive modulation, beamforming, or cognitive radio techniques.
• Experience working with wireless standards such as 3GPP, IEEE 802.11/15, or military waveforms.
• Experience with GPU acceleration or model optimization for constrained environments.
• Excellent communication and collaboration skills.

WORKING CONDITIONS AND PHYSICAL REQUIREMENTS

• Office environment.
• Outdoor environment for demos.
• Occasional exposure to heat, cold, and allergens while performing tests or demonstrations in the field.
• While performing the duties of this job, the employee is required to do the following:
  • Lift equipment up to 20 lbs. for the set-up of demonstrations and testing.
  • Perform bending and reaching movements to place items on lower and higher shelves.

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

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.

Role Overview:

As a Modeling & Simulation Engineer: Operations Analysis at CHAOS, you will design, develop, execute, analyze, and validate models and simulations to deliver operational analysis and system performance assessment across defense, national security, and commercial programs. You will have freedom to move rapidly and use your expertise to apply rigorous statistical methods to analyze simulation outcomes, quantify system effectiveness, and communicate actionable insights to technical teams, leadership, and customers. Your work will directly inform critical decisions around sensor performance, mission planning, weapon effectiveness, and platform capability evaluation.

This is an exciting opportunity to be among the first members of a rapidly growing team of professionals dedicated to delivering highly impactful technologies to the defense, national security, and critical industry sectors.

Responsibilities:

• Scope, plan, and execute modeling and simulation efforts and studies aligned to program objectives, managing your competing priorities and timelines effectively.
• Develop, configure, and execute analysis using mission-level models and simulations such as AFSIM, ESAMS, Brawler, Ansys STK, and/or physics-based models to evaluate system and platform performance in operationally relevant scenarios.
• Apply statistical analysis techniques to simulation output data to quantify key performance metrics, identify trends, and characterize system effectiveness.
• Build, refine, and analyze models of sensors, communications systems, aircraft (including unmanned), weapons, and spacecraft within high-fidelity, engagement-level, and mission-level simulation frameworks.
• Develop and maintain Python-based analysis tools and pipelines for data processing, statistical analysis, and visualization.
• Document methodology, assumptions, and findings in technical reports and briefing materials, including data visualizations, and present results to both technical and non-technical audiences.
• Collaborate with engineering, business development, and customer teams to translate operational questions into well-structured analytical approaches.
• Maintain software development best practices including version control and reproducible analysis workflows.
• Support programs spanning DoD services, DARPA, intelligence community, and commercial customers.

Minimum Requirements:

• Bachelor's degree or higher in Computer Science, Aerospace/Software/Computer Engineering, Data Science, Statistics, Mathematics, Operations Research, Physics, or a related field.
• 5+ years of experience supporting defense, intelligence, or advanced technology programs through industry or government employment.
• Significant experience developing analytical tools and applying rigorous statistical methods to interpret and present results.
• Strong proficiency in Python and MATLAB, including standard scientific computing and visualization libraries (such as Pandas, Polars, NumPy, SciPy, Scikit-Learn, Matplotlib, Seaborn, CuPy, or PyTorch).
• Exceptional data visualization skills and comfort with developing CONOPS/OV-1 visuals and briefing packages.
• Proficiency with software development practices including version control and leveraging/validating outputs of AI-assisted coding tools.
• Prior experience in developing/working with rigid body/6 Degrees of Freedom physics simulations.
• Demonstrated ability to work independently and deliver analytical products with minimal oversight.
• Comfortable working on Linux-based systems and writing scripts and software for scalability.
• Eligibility to obtain a Top Secret / Sensitive Compartmented Information (TS/SCI) clearance.

Preferred Requirements:

• Demonstrated experience performing operations analysis studies using combat simulations (such as AFSIM, ESAMS, Brawler, and/or physics-based models), including interpreting results with statistical rigor and briefing key stakeholders.
• Extensive experience in radar sensor performance analysis, including quantification of key metrics and performance parameters, and conducting mission-level analysis of air-to-air, air-to-surface, surface-to-air, and electronic warfare engagements.
• Expertise in developing and validating models of sensors (especially radar), communications, aircraft (including unmanned aerial systems), weapons (especially missiles), or spacecraft in mission-level simulation environments such as AFSIM or Ansys STK.
• Exposure to Distributed Interactive Simulation (DIS) networking and visualization tools such as MAK VR-Forces, SIMDIS, or similar.
• Exposure to PX4 Guidance, Navigation & Control, and software-in-the-loop simulation with platforms such as X-Plane, Gazebo, or NVIDIA Omniverse.
• Experience supporting U.S. Department of Defense branches and related research labs such as DARPA, ONR, AFRL, or others, and commercial advanced technology programs.
• 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

The Data Science team, a part of the broader StubHub Data organization, is looking for an experienced, senior-level Data Science Manager to lead a growing team (currently 6, ranging from entry level DS to Staff+) that covers a wide range of data science disciplines.

StubHub is the largest secondary ticketing marketplace in the world, generating massive amounts of consumer data that are leveraged to tackle many unique and interesting predictive and inference problems across user acquisition, product recommendations, pricing optimization, ticket fulfillment mitigation, and business forecasting. As a Data Science Manager, you will need to work closely with business leaders and convert their long-term strategic goals into tangible machine learning projects executed by your team at a day-to-day level. Understanding when to provide oversight from a technical perspective, while being able to grow individuals, will be paramount in your team's long-term success.

You will also be responsible for the technical and personal growth of your team members, developing talent density through focused mentorship, strategic career development, and execution excellence. There will be a need to plan team structure and growth as we invest more in ML, especially to understand the best ways to build and apply generative AI solutions within our product.

You will be joining at a critical time for the Data Science practice and the company – while the value of this discipline has been established and there’s a high-performing team in place, we are far from steady state. Key areas of investment from a vision and team planning perspective include establishing new pockets of deep technical expertise (e.g., causal inference, graph ML), advocating for best-in-class ML tooling/platform, and widening the reach of data science company-wide. As a senior leader on this team, you will be responsible for shaping and realizing that vision.

Location: Hybrid (3 days in office/2 days remote) – New York, NY or Century City, CA 

What You'll Do

• Technical project scoping and planning
• Partner with cross-functional stakeholders across the business, executives, and data team
• Technical review and architecture oversight
• Recruitment and end-to-end talent growth development: Performance reviews, promotion recommendations, 360 feedback, etc
• Surface infrastructure needs and onboard solutions

What You've Done

• 8 - 10 years of relevant machine learning/data science in a fast-paced, high growth environment
• 8 - 10 years of experience managing high performant data science team.
• Strong programming and analytical ability with expertise in SQL and Python (TensorFlow, scipy, scikit-learn, PyTorch, statsmodels)
• Experience with modern workflow orchestration used in machine learning, e.g.,Metaflow, ZenFlow, Airflow
  
  
• Nice to Haves:
  • Worked at a consumer tech company
  • Experience with GenAI/LLM/Agentic workflows in a production setting
  • Hands-on experience with graph-based machine learning and recommendation systems

What We Offer

• Accelerated Growth Environment: An environment designed for swift skill and knowledge enhancement, where you have the autonomy to lead experiments and tests on a massive scale.
• Top Tier Compensation Package: Competitive base, equity, and upside that tracks with your impact.
• Flexible Time Off: Enjoy unlimited Flex Time Off, giving you the flexibility to manage your schedule and take time to recharge as needed.
• Comprehensive Benefits Package: Prioritize your well-being with a comprehensive benefits package, featuring 401k, and premium Health, Vision, and Dental Insurance options.

The Data Science team, a part of the broader StubHub Data organization, is looking for an experienced, senior-level Data Science Manager to lead a growing team (currently 6, ranging from entry level DS to Staff+) that covers a wide range of data science disciplines.

StubHub is the largest secondary ticketing marketplace in the world, generating massive amounts of consumer data that are leveraged to tackle many unique and interesting predictive and inference problems across user acquisition, product recommendations, pricing optimization, ticket fulfillment mitigation, and business forecasting. As a Data Science Manager, you will need to work closely with business leaders and convert their long-term strategic goals into tangible machine learning projects executed by your team at a day-to-day level. Understanding when to provide oversight from a technical perspective, while being able to grow individuals, will be paramount in your team's long-term success.

You will also be responsible for the technical and personal growth of your team members, developing talent density through focused mentorship, strategic career development, and execution excellence. There will be a need for planning of team structure and growth as we put more investment into ML, especially understanding the best ways of building and applying generative AI solutions within our product.

You will be joining at a critical time for the Data Science practice and the company – while the value of this discipline has been established and there’s a high performing team in place, we are far from steady state. Key areas of investment from a vision and team planning perspective include establishing new pockets of deep technical expertise (e.g. causal inference, graph ML), advocating for best-in-class ML tooling/platform, and widening the reach of data science company-wide. As a senior leader of this team, you will be in charge of shaping and materializing that vision.

Location: Hybrid (3 days in office/2 days remote) – New York, NY or Century City, CA 

What You'll Do

• Technical project scoping and planning
• Partner with cross-functional stakeholders across the business, executives, and data team
• Technical review and architecture oversight
• Recruitment and end-to-end talent growth development: Performance reviews, promotion recommendations, 360 feedback, etc
• Surface infrastructure needs and onboard solutions

What You've Done

• 8 - 10 years of relevant machine learning/data science in a fast-paced, high growth environment
• 8 - 10 years of experience managing high performant data science team.
• Strong programming and analytical ability with expertise in SQL and Python (TensorFlow, scipy, scikit-learn, PyTorch, statsmodels)
• Experience with modern workflow orchestration used in machine learning, e.g.,Metaflow, ZenFlow, Airflow
  
  
• Nice to Haves
  • Worked at a consumer tech company
  • Experience with GenAI/LLM/Agentic workflows in a production setting
  • Hands-on experience with graph based machine learning and recommendation systems

What We Offer

• Accelerated Growth Environment: An environment designed for swift skill and knowledge enhancement, where you have the autonomy to lead experiments and tests on a massive scale.
• Top Tier Compensation Package: Competitive base, equity, and upside that tracks with your impact.
• Flexible Time Off: Enjoy unlimited Flex Time Off, giving you the flexibility to manage your schedule and take time to recharge as needed.
• Comprehensive Benefits Package: Prioritize your well-being with a comprehensive benefits package, featuring 401k, and premium Health, Vision, and Dental Insurance options.

We are seeking a seasoned Technical Leader to build and scale the foundational compute infrastructure that powers our state-of-the-art AI models—from multimodal training data pipelines to high-throughput, low-latency video generation.

Responsibilities

You will be the core engineer responsible for building the robust, efficient, and scalable platform that enables our research and production teams to rapidly iterate on HeyGen's generative video models. Your contributions will directly impact model performance, developer productivity, and the final quality of every AI-generated video.

• Optimize GPU Utilization: Design and implement mechanisms to aggressively optimize GPU and cluster utilization across thousands of devices for inference, training, data processing and large-scale deployment of our state-of-art video generation models.

• Develop Large-Scale AI Job Framework: Build highly scalable, reliable frameworks for launching and managing massive, heterogeneous compute jobs, including multi-modal high-volume data ingestion/processing, distributed model training, and continuous evaluation/benchmarking.

• Enhance Observability: Develop world-class observability, tracing, and visualization tools for our compute cluster to ensure reliability, diagnose performance bottlenecks (e.g., memory, bandwidth, communication).

• Accelerate Pipelines: Collaborate closely with AI researchers and AI engineers to integrate innovative acceleration techniques (e.g., custom CUDA kernels, distributed training libraries) into production-ready, scalable training and inference pipelines.

• Infrastructure Management: Champion the adoption and optimization of modern cloud and container technologies (Kubernetes, Ray) for elastic, cost-efficient scaling of our distributed systems.

Minimum Requirements

We are looking for a highly motivated engineer with deep experience operating and optimizing AI infrastructure at scale.

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

• 5+ years of full-time industry experience in large-scale MLOps, AI infrastructure, or HPC systems.

• Experience with data frameworks and standards like Ray, Apache Spark, LanceDB

• Strong proficiency in Python and a high-performance language such as C++  for developing core infrastructure components.

• Deep understanding and hands-on experience with modern orchestration and distributed computing frameworks such as Kubernetes and Ray.

• Experience with core ML frameworks such as PyTorch, TensorFlow, or JAX.

Preferred Qualifications

• Master's or PhD in Computer Science or a related technical field.

• Demonstrated Tech Lead experience, driving projects from conceptual design through to production deployment across cross-functional teams.

• Prior experience building infrastructure specifically for Generative AI models (e.g., diffusion models, GANs, or large language models) where cost and latency are critical.

• Proven background in building and operating large-scale data infrastructure (e.g., Ray, Apache Spark) to manage petabytes of multi-modal data (video, audio, text).

• Expertise in GPU acceleration and deep familiarity with low-level compute programming, including CUDA, NCCL, or similar technologies for efficient inter-GPU communication.

What HeyGen Offers

• Competitive salary and benefits package.
• Dynamic and inclusive work environment.
• Opportunities for professional growth and advancement.
• Collaborative culture that values innovation and creativity.
• Access to the latest technologies and tools.

HeyGen is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

We are seeking a seasoned Software Engineer to build and scale the foundational compute infrastructure that powers our state-of-the-art AI models—from multimodal training data pipelines to high-throughput, low-latency video generation.

Responsibilities

You will be the core engineer responsible for building the robust, efficient, and scalable platform that enables our research and production teams to rapidly iterate on HeyGen's generative video models. Your contributions will directly impact model performance, developer productivity, and the final quality of every AI-generated video.

• Optimize GPU Utilization: Design and implement mechanisms to aggressively optimize GPU and cluster utilization across thousands of devices for inference, training, data processing and large-scale deployment of our state-of-art video generation models.

• Develop Large-Scale AI Job Framework: Build highly scalable, reliable frameworks for launching and managing massive, heterogeneous compute jobs, including multi-modal high-volume data ingestion/processing, distributed model training, and continuous evaluation/benchmarking.

• Enhance Observability: Develop world-class observability, tracing, and visualization tools for our compute cluster to ensure reliability, diagnose performance bottlenecks (e.g., memory, bandwidth, communication).

• Accelerate Pipelines: Collaborate closely with AI researchers and AI engineers to integrate innovative acceleration techniques (e.g., custom CUDA kernels, distributed training libraries) into production-ready, scalable training and inference pipelines.

• Infrastructure Management: Champion the adoption and optimization of modern cloud and container technologies (Kubernetes, Ray) for elastic, cost-efficient scaling of our distributed systems.

Minimum Requirements

We are looking for a highly motivated engineer with deep experience operating and optimizing AI infrastructure at scale.

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

• 5+ years of full-time industry experience in large-scale MLOps, AI infrastructure, or HPC systems.

• Experience with data frameworks and standards like Ray, Apache Spark, LanceDB

• Strong proficiency in Python and a high-performance language such as C++  for developing core infrastructure components.

• Deep understanding and hands-on experience with modern orchestration and distributed computing frameworks such as Kubernetes and Ray.

• Experience with core ML frameworks such as PyTorch, TensorFlow, or JAX.

Preferred Qualifications

• Master's or PhD in Computer Science or a related technical field.

• Demonstrated Tech Lead experience, driving projects from conceptual design through to production deployment across cross-functional teams.

• Prior experience building infrastructure specifically for Generative AI models (e.g., diffusion models, GANs, or large language models) where cost and latency are critical.

• Proven background in building and operating large-scale data infrastructure (e.g., Ray, Apache Spark) to manage petabytes of multi-modal data (video, audio, text).

• Expertise in GPU acceleration and deep familiarity with low-level compute programming, including CUDA, NCCL, or similar technologies for efficient inter-GPU communication.

What HeyGen Offers

• Competitive salary and benefits package.
• Dynamic and inclusive work environment.
• Opportunities for professional growth and advancement.
• Collaborative culture that values innovation and creativity.
• Access to the latest technologies and tools.

HeyGen is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Position Summary:

At HeyGen, we are at the forefront of developing applications powered by our cutting-edge AI research. As a Data Infrastructure Engineer, you will lead the development of fundamental data systems and infrastructure. These systems are essential for powering our innovative applications, including Avatar IV, Photo Avatar, Instant Avatar, Interactive Avatar, and Video Translation. Your role will be crucial in enhancing the efficiency and scalability of these systems, which are vital to HeyGen's success.

Key Responsibilities:

• Design, build, and maintain the data infrastructure and systems needed to support our AI applications. Examples include
• Large scale data acquisition
• Multi-modal data processing framework and applications
• Storage and computation efficiency
• AI model evaluation and productionization infrastructure
• Collaborate with data scientists and machine learning engineers to understand their computational and data needs and provide efficient solutions.
• Stay up-to-date with the latest industry trends in data infrastructure technologies and advocate for best practices and continuous improvement.
• Assist in budget planning and management of cloud resources and other infrastructure expenses.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
• Proven experience in managing infrastructure for large-scale AI or machine learning projects
• Excellent problem-solving skills and the ability to work independently or as part of a team.
• Proficiency in Python
• Experience optimizing computational workflows
• Familiarity with AI and machine learning frameworks like TensorFlow or PyTorch.

Preferred Qualifications:

• Experience with GPU computing
• Experience with distributed data processing system
• Experience building large scale batch inference system
• Prior experience in a startup or fast-paced tech environment.

What HeyGen Offers

• Competitive salary and benefits package.
• Dynamic and inclusive work environment.
• Opportunities for professional growth and advancement.
• Collaborative culture that values innovation and creativity.
• Access to the latest technologies and tools.

HeyGen is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Driving Product Innovation with Advanced Computer Vision Technology

HeyGen is a dynamic startup at the forefront of revolutionizing video content with state-of-the-art artificial intelligence technology. With a robust track record of growth and a proven business model, we are rapidly carving out a leadership position in the AI-powered video creation industry. We are in search of passionate Research Scientists with a specialization in Computer Vision to propel our mission forward. If you are eager to deploy your advanced skills to disrupt and redefine the video creation and interaction experience, your next big opportunity awaits with us.

Key Responsibilities:

• Applied Innovation and Product Development: Harness your knowledge of generative models, including GANs, Diffusion models, and other multi-modal models, to propel our video creation tools forward. Your role involves translating state-of-the-art research into innovative features that directly enhance our user experience and set our products apart.

• Real-World Solutions: Channel your research capabilities to develop scalable solutions that have a significant impact on our platform, making the video creation process more intuitive, powerful, and accessible to our users.

• Collaborative Engineering and Growth: Engage with a diverse team where collaborative efforts lead to extraordinary outcomes. Embrace an environment that promotes learning, mentorship, and teamwork, furthering both personal development and the advancement of our technology.

Qualifications:

• A Master's or PhD in Computer Science, Engineering, or a related field
• 1-3 years of experience in machine learning and computer vision, demonstrating practical application of generative models and a passion for product-centric innovation.
• Proficiency in Python, with openness to other programming languages and tools as required by project demands.
• Experience with deep learning frameworks such as PyTorch, and a capacity for quickly mastering new technologies.
• A collaborative spirit with a proven track record in a team-based research or development setting.
• A lifelong learner with outstanding problem-solving skills and the ability to communicate effectively in a diverse team environment.

What HeyGen Offers:

• Competitive Salary and Benefits: We offer a salary commensurate with your experience and a comprehensive benefits package that addresses a variety of needs.
• Innovative and Inclusive Work Environment: Our workplace is designed to inspire innovation through collaboration, respect, and mutual support.
• Opportunities for Advancement: We are committed to your professional development, offering extensive opportunities for learning, mentorship, and career growth.
• Dedication to Diversity: HeyGen is an equal opportunity employer, championing a diverse and inclusive team that ensures equal access to opportunities for all members.