Who We Are

2K is headquartered in Novato, California and is a wholly owned label of Take-Two Interactive Software, Inc. (NASDAQ: TTWO). Founded in 2005, 2K Games is a global video game company, publishing titles developed by some of the most influential game development studios in the world. Our studios responsible for developing 2K’s portfolio of world-class games across multiple platforms, include Visual Concepts, Firaxis, Hangar 13, CatDaddy, Cloud Chamber, 31st Union, HB Studios, and 2K SportsLab. Our portfolio of titles is expanding due to our global strategic plan, building and acquiring exciting studios whose content continues to inspire all of us! 2K publishes titles in today’s most popular gaming genres, including sports, shooters, action, role-playing, strategy, casual, and family entertainment.

Our team of engineers, marketers, artists, writers, data scientists, producers, thinkers and doers, are the professional publishing stewards of 2K’s portfolio currently includes several AAA, sports and entertainment brands, including global powerhouse NBA®️ 2K,  renowned BioShock®️, Borderlands®️, Mafia, Sid Meier’s Civilization®️ and XCOM®️ brands; popular WWE®️ 2K and WWE®️ SuperCard franchises, TopSpin 2K25, as well as the critically and commercially acclaimed PGA TOUR®️ 2K.

At 2K, we pride ourselves on creating an inclusive work environment, which means encouraging our teams to Come as You Are and do your best work! We encourage ALL applicants to explore our global positions, even if they don’t meet every requirement for the role.  If you're interested in the job and think you have what it takes to work at 2K, we encourage you to apply!

 What You Will Do

 2K Games is building a world-class data ecosystem to power real-time analytics, machine learning, and game intelligence across all our franchises. We are looking for a Senior Product Manager, Data Science to drive the vision, strategy, and execution of our data science strategies and products, partnering with game studios and analytics teams to enable enhanced player experiences.

This role requires a blend of strategic development, product management expertise, and technical understanding of data science and machine learning (ML) methodologies. The ideal candidate will seamlessly integrate data-driven strategies with player-centric goals, ensuring AI and analytics improve game design, live operations, and business intelligence.

Strategic Vision & Product Leadership

• Develop and implement the product strategy for 2K’s central data science platform, partnering with Data Scientists across our gaming business units to drive predictive analytics, player personalization, and real-time decision-making;
• Collaborate with the Director of Product, 2K Data to align the data engineering roadmap with customer objectives and player-centric outcomes;
• Define and prioritize a high-impact data science roadmap to lead a team of central data scientists in driving a variety of use cases such as player retention modeling, dynamic content generation, and real-time fraud detection. 

Data Science Platform Development

• Lead the development of reusable and extensible machine learning models, feature engineering pipelines, and ML-driven insights using tools like Databricks, MLflow, and SageMaker;
• Ensure data science initiatives integrate seamlessly with the real-time data infrastructure, supporting streaming analytics, AI-powered LiveOps, and dynamic matchmaking systems;
• Establish and maintain self-service tools that enable game teams to experiment with and deploy AI models independently;
• Support the build and enhancement of the central ML feature store;
• Monitor and optimize model performance in production environments, using MLOps standard methodologies;
• Implement governance frameworks to ensure AI models adhere responsibly to data privacy, security, and compliance standards (e.g., CCPA, GDPR). 

Cross-Functional Collaboration

• Work closely with data scientists across game studios and business units to understand their data science needs and to provide data-driven solutions at the pace they need them;
• Act as a strategic liaison between data scientists and product teams, ensuring model outputs are actionable, reliable, and aligned with business goals;
• Promote a culture of experimentation and rapid iteration, supporting game studios with A/B testing frameworks, predictive analytics, and personalization engines.
• Find opportunities to enhance game design and player engagement through advanced analytics and machine learning.

 What You Need

• 7+ years of experience in product management with a focus on data science, analytics, or ML-driven products
• 5+ years of experience in gaming, technology, or entertainment industries;
• Strong understanding of data science methodologies, such as predictive modeling, natural language processing, and computer vision;
• Experience with data science tools and platforms, such as Python, SQL, Databricks,TensorFlow, and R;
• Customer-focused mentality with focus on the Why and What without getting lost in the What and the How;
• Consistent track record of delivering data science products and features from ideation to production, with measurable business impact;
• Ability to translate complex data insights into clear product strategies and business opportunities;
• Knowledge of real-time analytics platforms, streaming data processing, and feature store management;
• Familiarity with data governance frameworks, model risk management, and MLOps standard processes preferred;
• Advanced degree or equivalent experience in Data Science, Machine Learning, Computer Science, or a related field preferred.

The pay range for this position in California at the start of employment is expected to be between $109,800 and $162,480 per Year. However, base pay offered is based on market location, and may vary further depending on individualized factors for job candidates, such as job-related knowledge, skills, experience, and other objective business considerations. Subject to those same considerations, the total compensation package for this position may also include other elements, including a bonus and/or equity awards and eligibility to participate in our 401(K) plan and Employee Stock Purchase Program. Regular, full-time employees are also eligible for a range of benefits at the Company, including: medical, dental, vision, and basic life insurance coverage; 14 paid holidays per calendar year; paid vacation time per calendar year (ranging from 15 to 25 days) or eligibility to participate in the Company’s discretionary time off program; up to 10 paid sick days per calendar year; paid parental and compassionate leave; wellbeing programs for mental health and other wellness support; family planning support through Maven; commuter benefits; and reimbursements for fitness-related expenses.

As an equal opportunity employer, we are committed to ensuring that qualified individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform their essential job functions, and to receive other benefits and privileges of employment. Please contact us if you need reasonable accommodation.

Please note that 2K Games and its studios never uses instant messaging apps or personal email accounts to contact prospective employees or conduct interviews and when emailing, only use 2K.com accounts. 

#LI-Onsite

The Role 

Our enterprise software team builds the digital backbone that powers K2 Space’s satellite design, manufacturing, and mission operations. We develop tools that connect engineering, production, and mission control into a seamless ecosystem — enabling our hardware to get from concept to orbit faster than ever before. 

As we continue to grow, we’re looking for a Cloud Engineer who shares our vision: someone who doesn’t just maintain cloud infrastructure — but thinks deeply about scalability, security, reliability, and how cloud systems power space-grade engineering and operations. 

Responsibilities 

• Design, build, deploy, and maintain cloud infrastructure supporting mission-critical workloads (IaaS, PaaS, SaaS, FaaS) across production, staging, and development environments. 
• Define and implement infrastructure-as-code (IaC) automation (Terraform, ARM/Bicep, etc.), CI/CD pipelines, configuration management, and other automation tooling to enable rapid, reproducible, and secure deployments. 
• Collaborate with software, mission-ops, and DevOps teams to integrate cloud architecture into our development lifecycle (DevSecOps — from build to launch). 
• Establish and manage identity and access management (IAM), role-based access, encryption, network security, secrets management, and compliance controls. 
• Monitor and maintain the health, performance, and cost-effectiveness of cloud services; implement logging, monitoring, alerting, and capacity planning. 
• Perform security assessments, threat modeling, vulnerability scans, compliance audits; develop mitigation strategies and drive best practices. 
• Create clear documentation of architectures, relevant procedures, security policies, and infrastructure diagrams — and communicate across teams and stakeholders. 
• Stay on top of cloud security threats, emerging technologies, and compliance requirements — and champion proactive improvements in our cloud posture. 

Basic Qualifications 

• Bachelor’s degree in Computer Science, Information Technology, or related field — or equivalent practical experience. 
• 5+ years (senior-level) hands-on experience managing cloud infrastructure (AWS, Azure, GCP or similar), preferably across multiple cloud platforms. 
• Strong proficiency with IaC tools (Terraform, ARM/Bicep, CloudFormation, etc.), CI/CD, configuration management, and scripting (e.g. Python, Bash, PowerShell). 
• Solid understanding of cloud-native services (VMs, containers/Kubernetes, serverless, databases, networking, storage) and ability to design scalable, resilient architectures. 
• Experience with container orchestration systems (Kubernetes, Docker) and modern deployment workflows. 
• Deep knowledge of security best practices: IAM, encryption, network security (firewalls, VNets), secrets management, monitoring, logging, and compliance frameworks. 
• Familiarity with (or willingness to learn) compliance regimes relevant to defense/space sector (e.g., FedRAMP, CMMC, ITAR, government-cloud environments) — especially if working on sensitive or government-facing projects. 
• Excellent problem-solving skills, strong communication (verbal + writing), ability to work in cross-functional teams, and comfort working in a fast-paced, mission-driven startup environment. 

Preferred Qualifications 

• Advanced cloud certifications (e.g. AWS Solutions Architect/DevOps, Azure Administrator/DevOps/Security, Kubernetes certifications) 
• Experience with hybrid clouds / Gov-cloud environments / regulated-space-industry compliance 
• Prior experience supporting aerospace, defense, or highly regulated workloads 
• Familiarity with GitOps workflows, MLOps pipelines, container-security tooling, secrets vaults (e.g. HashiCorp Vault), log aggregators / monitoring systems (e.g. ELK, Splunk), and automated incident response / forensics pipelines. 

Compensation and Benefits: 

• Base salary range for this role is $165,000 - $215,000 + equity in the company 
• Salary will be based on several factors including, but not limited to: knowledge and skills, education, and experience level 
• Comprehensive benefits package including paid time off, medical/dental/vision/ coverage, life insurance, paid parental leave, and many other perks 

Company Information
For more than 20 years, AEG has played a pivotal role in transforming sports and live entertainment. Annually, we host more than 160 million guests, promote more than 10,000 shows and present more than 22,000 events around the world. We are committed to innovation, artistry, and community, and leverage the power of our 300+ venues, leading sports franchises, marquee music brands, integrated entertainment districts, premier ticketing platform and global sponsorship activations, to create memorable moments that give the world reason to cheer.

Our business is interwoven with the human mind and heart, and we strive to build a diverse and inclusive company that reflects the artists, athletes, and fans that we host; reach beyond traditional boundaries to support the communities in which we operate; and minimize our impact on the environment by adopting sustainable practices throughout our business operations.

If you want to be challenged to up your game and make a difference, then join us in giving the world reason to cheer!

JOB DESCRIPTION:

The Sr. Data Analyst will play a pivotal role in maximizing revenue and driving dynamic pricing strategy across ticketing products and fan segments. Using statistical modeling and machine learning, this role will measure price elasticity, forecast revenue, and predict customer demand. The position will collaborate closely with cross-functional teams, including Sales, Service, Marketing, and Operations, to deploy scalable data science tooling, drive decision-making, and optimize sales.

 ESSENTIAL FUNCTIONS:

• Implement and manage dynamic pricing mechanisms to adjust ticket prices in real-time based on factors such as team performance, opponent strength, and event timing. 
• Utilize models and data analysis to identify pricing trends, optimize ticket prices, and forecast revenue potential for various seating categories. 
• Manage the end-to-end data science lifecycle from model design, development, deployment, maintenance, and model updates.  
• Provide expertise, analysis, and guidance for promotional campaigns, ensuring alignment with overall pricing strategies. 
• Effectively collaborate with business partners to communicate findings and understand key pricing problems and define strategic priorities. 
• Partner closely with the Data Engineering team to structure, validate, and optimize data pipelines and data models for analysis and resolve any data discrepancy. 
• Build and maintain SQL-based views across data warehouses, ensuring suitability for reporting, accuracy, performance, and data integrity. 
• Communicate findings and next steps to leadership. 

SPECIFIC JOB KNOWLEDGE, SKILL AND ABILITY:

The Sr. Data Analyst must possess the following knowledge, skills and abilities and be able to explain and demonstrate that he or she can perform the essential functions of the job, with or without reasonable accommodation, using some other combination of skill and abilities:

QUALIFICATION STANDARDS:

Education:

• BA/BS Degree in mathematics, engineering, physics, or related quantitative field

Experience:

• Bachelor’s degree in mathematics, engineering, physics, or related quantitative field 
• 2+ years’ experience as a data scientist, pricing analyst, data analyst, or equivalent 
• Data Science certification required, master’s degree in data science, statistics, computer science, engineering, economics, analytics or a related quantitative field preferred 
• Expertise in SQL, statistical programming (Python) and Spark 
• Experience working with MLOps workflows and platforms, including Databricks, Azure ML, SageMaker or similar tools is preferred.  
• Rigorous attention-to-detail, keen critical thinking skills, and pragmatic problem-solving mindset 
• Strong statistical knowledge and proven experience developing forecasting, demand prediction, and dynamic pricing models, and driving revenue outcomes in a data-driven, agile organization. 
• Strong communication skills and ability to work with all levels of employees; must be able to communicate technical aspects to non-technical team members 
• Ability to work independently to accomplish work objectives, while also thriving in a team environment 
• Experience or interest in sports/live entertainment a plus 

Payscale: $79,000 - $100,000

Bonus: This position is eligible for a bonus under the current bonus plan requirements.

Benefits Full-time: We offer a comprehensive benefits package that includes: medical, dental and vision insurance, paid holidays, vacation and sick time, company paid basic life insurance, voluntary life insurance, parental leave, 401k Plan (with a current employer match of 3%), flexible spending and health savings account options, and wellness offerings.

AEG reserves the right to change or modify the employee’s job description whether orally or in writing, at any time during the employment relationship.  AEG may require an employee to perform duties outside their normal description.

AEG's policy is to hire the most qualified applicants, and we comply with all applicable federal, state and local employment laws in making hiring and employee decisions.  We are an equal opportunity employer and do not discriminate against applicants or employees on the basis of race, color, marital status, disability, religion, age, sex, sexual orientation, national origin, genetic information, veteran status, or any other legally protected status recognized by applicable federal, state or local law.

Employer does not offer work visa sponsorship for this position.

#LI-LAKings #LI-Onsite

Engineering Manager (Assignment: Interoperability & API Engineering)

WelbeHealth PACE helps seniors stay in their homes and communities by providing medical care and community-based services. We believe in going the extra mile and aim to make a genuine difference in our participants’ lives. 

The Engineering Manager is a hands-on technical leader accountable for driving the delivery of production-grade APIs, integrations, and AI/ML–enabled services within the Interoperability & API Engineering team. This role mirrors the technical leadership engineering rigor serving as the technical anchor for a dedicated team while enabling broader organizational scaling. The Engineering Manager will architect solutions, mentor engineers, build proof of concepts (PoCs), enforce engineering excellence, and ensure secure, compliant, scalable, and high-performing systems aligned with healthcare and organizational standards.

This role is different because the Engineering Manager at WelbeHealth:

• Directly shapes secure, compliant, production-grade systems that power care for vulnerable seniors – this role is about being the hands-on technical anchor rather than just managing delivery
• Makes decisions that directly affect healthcare delivery, compliance, and participant outcomes – this role sits at the intersection of healthcare standards (HIPAA, PHI/PII), cross-functional partnerships, and rapid innovation

We care about our team members. That’s why we offer:

• Medical insurance coverage (Medical, Dental, Vision)
• Work/life balance - We mean it! 17 days of personal time off (PTO), 12 holidays observed annually, and 6 sick days
• 401K savings + match
• Comprehensive compensation package including base pay and bonus
• And additional benefits!

On the day-to-day, you will:

Technical Leadership & Hands-On Engineering

• Lead end-to-end architecture, development, and delivery of APIs, microservices, and integration pipelines for internal and external healthcare systems, as well as act as the senior-most engineer for the team: designing components, writing high-quality code, troubleshooting complex issues, and performing rigorous code reviews
• Build scalable, cloud-native solutions using Azure, containerized workloads (Docker/Kubernetes), and modern integration frameworks

AI, Automation & MLOps Integration

• Implement repeatable MLOps patterns for model deployment, monitoring, and lifecycle management
• Build prototype PoCs that validate new technologies, workflows, or AI-enabled automations before scaling to production

Team Leadership, Mentorship, & Execution

• Lead and mentor a team of engineers, fostering a culture of innovation, ownership, and continuous learning, as well as step in as the escalation point for technical blockers, guiding the team toward solutions

Cross-Functional Partnership

• Collaborate with Product, Architecture, Cloud, Security, and other engineering teams to define integration strategies and solution blueprints, as well as translate complex technical designs into clear communication for non-technical stakeholders

Security, Compliance & Healthcare Standards

• Ensure all development aligns with HIPAA, PHI/PII-safe engineering, and healthcare interoperability requirements, as well as apply FHIR, HL7, EDI, and related healthcare interoperability patterns where applicable

Job requirements include:

• Bachelor’s degree in relevant field; master’s degree preferred
• Minimum of eight (8) years in software engineering, with at least three (3) years in a team leader or senior engineering capacity
• Minimum of two (2) years of hands-on experience with AI/ML, Azure AI Foundry, AI Foundry agents, or related AI integration frameworks
• Strong hands-on experience with Python and/or Node.js for API engineering and data integrations; known knowledge on Microsoft Azure tools stack is a must
• Prior experience in healthcare, interoperability, or API-heavy environments is a must
• Proficiency in REST/GraphQL API design, microservices patterns, authentication/authorization (OAuth2, JWT, Entra ID), and event-driven architectures
• Familiarity with MLOps tools (Azure ML, MLflow, Databricks) and container ecosystems
• Experience with interoperability standards such as FHIR, HL7, EDI, or clinical integration workflows is highly preferred

We are seeking an Engineering Manager that ideally has successful leadership abilities, hands on with AI/ML, Azure AI foundry with prior working experience in the healthcare domain. If you’re ready to join a team that values both its participants and team members, we’d love to hear from you!

Engineering managers at Riot are technical leaders first — they stay close to the craft, make grounded architectural decisions, and earn credibility through the quality of their technical judgment. They are also deeply invested in people: building diverse teams, growing individual careers, and creating environments where engineers do the best work of their lives. The best Riot engineering managers hold both of these responsibilities without trading one for the other.

AI Foundations (AIF) designs and operates Riot's production execution layer for models, agents, and AI-native workflows. The organization has three teams: ML Platform (model hosting, inference, lifecycle tooling), ML Bots (game-agent runtime and training), and Production AI (AI developer workflows, tooling, and vendor management), plus a small leadership staff. Together, these teams serve every game studio and central team at Riot that wants to use AI. As the Senior Manager, ML Engineering for AI Foundations, you will lead the group's engineering managers and a set of senior ICs, owning the organization's mid-term (~1 year) technical and capability roadmap. You will be accountable for coherent engineering practice across the three sub-teams, for the group's combined delivery against strategic commitments, and for building the kind of engineering culture that attracts and retains strong ML talent. This is a servant-leadership role on a team full of servant leaders. You succeed when frontline managers have the context they need to lead, senior ICs have room to focus, and teams across Riot can adopt AI with confidence. You will partner with peer leaders in game studios and central teams to understand their AI adoption challenges and feed those patterns back into the platforms and tools your teams build. You will report to the Director of AI Foundations.

Responsibilities

• Own the group's mid-term (~1 year) capability roadmap and 1+ year technical strategy; balance investment across custom platforms and tool adoption based on where Riot gets the most value.
• Track adoption and impact metrics; re-prioritize based on usage data and partner feedback.
• Ensure coherent technical direction across sub-teams; connect local tech strategy to Riot's broader AI direction. Contribute to architecture discussions, code when it helps, and support design cross-team decisions.
• Set a high bar for craft, operational rigor, and continuous learning; codify and share best practices for production ML (serving, MLOps, observability, responsible AI) so lessons from one team benefit all.
• Establish shared operational practices including cross-team on-call; maintain high ML system and model quality; ensure adherence to Responsible AI standards including fairness, explainability, and safety.
• Manage MLE team leads and senior ICs; coach managers to maintain a high performance bar and build growth plans.
• Develop ML engineering leaders; mentor ICs into management or senior technical roles; drive promotions at the Staff and Principal levels.
• Align staffing against AIF priorities, development goals, and career paths; own headcount requests (FTE and contractor). Partner with the talent team; set staffing priorities for technical roles in AIF; work with hiring managers around Riot to improve hiring practices for AI-related roles.
• Work with AIF leadership to establish operational and tooling budgets, including training, travel, and conference investment.
• Build alignment with game studios, central tech teams, and vendor partners; identify and de-risk dependencies. Manage AI vendor relationships (evaluation, integration, ongoing partnership) in coordination with AIF leadership.
• Make the transition from Tech Research to production repeatable, with clear handoff practices so promising research reaches players and Rioters.
• Advocate for AI-native workflows within AIF and across Riot; ensure stakeholders know what AIF is building, why, and how to engage. Make grounded build-vs.-adopt recommendations.
• Encourage teams to share what they learn — write-ups, demos, reusable components — so others across Riot can adopt AI more easily.

Qualifications

• BS in Computer Science, Machine Learning, or related field (or equivalent experience); 10+ years of industry experience including experience as a Senior ML Engineer or higher.
• 4+ years of management experience, including managing managers or team leads. Track record of building engineering culture by enabling the people around you.
• Evidence of shipping production ML systems that other teams depend on, with real operational weight. Working knowledge of model serving, CI/CD for ML, observability, and cost tradeoffs even if you're not writing code daily.
• Experience translating technical vision into a roadmap your teams executed against, with evidence of course-correcting when priorities shifted.
• Strong collaboration across ML, platform, product, and game development teams; track record of alignment across org boundaries. Experience making AI accessible to teams without deep ML expertise

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. 

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

By bringing together next-gen technology and the finest live data available, Genius Sports is enabling a new era of sports for fans worldwide, delivering experiences that are more immersive, interactive and personalized than ever before. Learn more at geniussports.com. 

The Role - Staff Engineer - Infrastructure Platform 

We are seeking a Staff Engineer to help lead critical initiatives of our core infrastructure platform. Genius Sports is currently in the process of aligning its various tech teams and acquisitions under one unified technical strategy. The infrastructure platform is the ground level of this change. The goal is to enable engineering teams to build, deploy, and operate Genius Sport’s massive product catalog in a consistent and cohesive manner. 

In this role, you’ll work with other InfraPlat leads to define and drive technical vision and implementation for a variety of projects. Some of these initiatives include multi-account/region Kubernetes clusters, MLOps, standardized deployments, and the company-wide authentication platform. In addition, you will engage with stakeholders from product engineering teams to scope requests, identify shared pain points within the org, and prioritize initiatives. 

What You’ll Bring

• 8+ years of experience building and operating infrastructure or devops platforms. 
• Experience architecting complex infrastructure with strict uptime and latency requirements across multiple regions.  
• Ability to navigate significant ambiguity and make sound technical decisions that hold up over time.
• Experience building applications and automations to eliminate toil for engineering teams. 
• Strong communication skills that enable you to drive platform adoption forwards for new teams.  
• Track record of making pragmatic tradeoff decisions across architecture, implementation, technical debt, and customer requests.
• Passion for mentorship and upleveling the team around you to maximize their full potential.

It’ll Be a Bonus if You Have 

• Experience managing hybrid edge infrastructure environments. 
• Experience with Rust in production. 
• History of open source contribution.
• Full stack software development experience with web applications or data pipelines.

The salary for this role is based on an annualized range of $230,000 - $260,000 USD. This role will also be eligible to take part in Genius Sports Group's benefits plan.

We enjoy an ‘office-first’ culture and maximize opportunities to collaborate, connect and learn together. Our hybrid working models differ depending on your role and location. Occasional travel may be required.

As well as a competitive salary and range of benefits, we’re committed to supporting employee wellbeing and helping you grow your skills, experience and career. Learn more about how rewarding life at Genius can be at Reward | Genius Sports.

One team, being brave, driving change 

We strive to create an inclusive working environment, where everyone feels a sense of belonging and the ability to make a difference. Learn more about our values and culture at Culture | Genius Sports.

Let us know when you apply if you need any assistance during the recruiting process due to a disability.

Engineering managers at Riot are technical leaders first—they stay close to the craft, make grounded architectural decisions, and earn credibility through the quality of their technical judgment and its impact on Riot’s ability to deliver for players. They are deeply invested in people: building diverse teams, growing individual careers, and creating environments where engineers can do the best work of their lives. The best Riot engineering managers hold both of these responsibilities without trading one for the other.

Anti-Cheat is Riot’s first defense against cheaters that don’t want to play fair. As a cross-discipline team of former cheaters, kernel developers, machine learning engineers, data analysts, and software engineers, they make products like Vanguard to detect and ban the bad guys across all of Riot’s competitive titles and platforms, staying vigilant to whatever shape they’ll take in response.  From beaming bots to scorching scripters, anti-cheat enables Riot’s game teams to take on competitive genres and design rewarding systems that would otherwise be too vulnerable to fraudsters and cheaters. As a Sr. Manager of Machine Learning Engineering on Anti-Cheat, you will lead a group of teams, including Data Analytics, Data Engineering, and ML Engineering, unified in a quest to both operationally support day-to-day anti-cheat operations and cook the ML-powered weaponry that will ultimately upgrade them. You will own the entire group’s roadmap, ensuring a coherent technical approach to modelling, warehousing, and engineering across all of anti-cheat, while also fostering strong alignment with partnering games and organizations.  Your responsibilities will include converting product priorities into tangible technical strategies, optimizing data team compositions to achieve these goals, and deeply contributing to all projects involved on a profoundly technical level.  Your success will be measured through both the statistical and the perceived fairness of Riot’s competitive ladders. You will report to the Director of Anti-Cheat.

Responsibilities

• Use all of anti-cheat’s resources to help design, build, and maintain AI/ML pipelines from end-to-end, creating an iterative, ever-evolving series of classifiers, capable of adapting in perpetuity as attackers learn from its actions.
• Leverage Riot’s centralized ML infrastructure where possible, upgrade it where necessary, and ensure that any realized technical capabilities can be capitalized on by other teams and products.
• Innovate in the anomaly detection space by creating proven, trusted player outcomes from novel and even theoretical modelling approaches.
• Drive AI/ML pipeline development and deployment standards across teams, coordinating with data engineering on shared MLOps capabilities.
• Manage individual contributors and team-level managers of a variety of shapes: Data Engineers, Data Analysts, ML Engineers while also helping shepherd the unique “Anti-Cheat Analyst” craft that amalgamates detections, reconnaissance, and player support.
• Evaluate overall team composition, identifying gaps in skills, seniority, and capacity that could impact roadmap delivery; take a proactive role in resource allocation and strategic development of team capabilities.
• Clearly articulate and demonstrate good ML engineering practices; recognize when to lean in and help directly when necessary.
• Ensure the group stays current with AI/ML developments and has high contextual awareness of company and industry direction; separate signal from noise in service of product and technical strategy.

Required Qualifications

• BS in Computer Science, Machine Learning, or related field (or equivalent experience).
• 10+ years of industry experience, including experience as a Senior ML Engineer or higher.
• 4+ years of management experience, including experience managing managers or team leads.
• Evidence that teams you’ve led have shipped ML systems that other teams or products depend on.  Not just prototypes, but production systems with real operational weight.
• Experience translating a long-term technical vision into a roadmap that your teams successfully executed against, with evidence of course-correcting when priorities shifted.
• Working knowledge of production ML systems.  You can engage credibly on model serving, CI/CD for ML, observability, and cost tradeoffs, even if you’re not writing the code daily (but you can also write the code daily).
• Comfort representing ML capabilities in cross-disciplinary forums and translating technical tradeoffs for product, design, and leadership audiences.
• History of working at the boundary between research and production, where interesting problems require both scientific rigor and engineering pragmatism.

Desired Qualifications

• Experience building iterative machine classifiers for behavioral anomalies in competitive video games.
• Hands-on experience in threat detection for risk, fraud, insurance, security, sports, or gaming spaces.
• Passion for player experience, games, or creative technology.

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 Engineers bring deep knowledge of specific technical areas but also value the chance to work in many broader domains. As a Staff Software Engineer, you’ll also dive into projects that focus on team cohesiveness and cross-team goals. You’ll lead without authority and provide other engineers with a clear illustration of extraordinary engineering. In this role, you will be enabling productionized machine learning across all of Riot, at a global scale. You’ll be applying modern MLOps practices: streamlining deployment, simplifying operations, and creating reliable infrastructure that empowers data scientists, ML engineers, and product teams to deliver value quickly and confidently.

As a Staff Machine Learning Engineer, you’ll design and implement methods for model deployment, monitoring, and lifecycle management. You’ll work on enabling all kinds of AI/ML by creating critical infrastructure; think model orchestration, feature stores, vector DBs, and everything in between. Your contributions will make ML & AI easier to adopt and operate across Riot, helping game and platform teams deliver high-impact machine learning solutions more efficiently. You will report to the Engineering Manager with Riot's Game Technology Group.

Responsibilities:

• Implement and support ML inference infrastructure for real-time and batch serving, including deployment pipelines and CPU/GPU-aware orchestration
• Contribute to CI/CD workflows for ML artifacts, helping enable rapid iteration and safe promotion from development to production
• Implement platform observability features such as monitoring, drift detection, resource utilization, and latency tracking
• Support ML deployment best practices, including multi-version models, blue/green rollouts, shadow deployments, and safe rollback strategies
• Be thoughtful on developer UX and incorporate an iterative approach to improving
• Help lead long-term platform architecture, providing input into design decisions and contributing to team discussions
• Contribute upstream to shared infra initiatives and build feedback loops and collaboration models with other Riot platform teams
• Collaborate with researchers and game teams to understand product needs and build generalizable, reusable solutions

Required Qualifications: 

• 6+ years of experience in software engineering, with time spent on ML/AI, platform or infrastructure teams
• Experience maintaining cloud-agnostic inference platforms (e.g. KServe) or running open source frameworks (Feast, Milvus, etc.) in a production environment
• Experience with one or more inference serving frameworks (e.g., NVIDIA Triton, TorchServe, BentoML, Seldon Core etc)
• Familiarity with GPU orchestration, performance tuning, and cost-aware scheduling
• Exposure to CI/CD workflows, infrastructure-as-code (e.g., Terraform), and artifact management
• Maintained or led development of services within a service-oriented architecture

Desired Qualifications:

• Proficiency in Python and experience with package management tools (e.g., Conda, Poetry)
• Exposure to AB testing and experimentation frameworks, especially in online model evaluation
• Familiarity with machine learning workflows (e.g., training, validation, deployment, monitoring) and experience working with data scientists
• Passion for player experience, game systems, or creative technology development

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. 

CSQ127R318

As a Big Data Solutions Architect (Resident Solutions Architect) in our Professional Services team you will work with clients on short to medium term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

• You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of  professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps 
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time
• Databricks Certification

This role follows a hybrid schedule, with three days per week onsite in our Culver City or San Francisco office.

The opportunity

We're hiring a Senior Cloud Infrastructure Engineer to join the Cloud Infrastructure & Platform (CIN) team at Altruist. This is a high-impact, senior individual contributor role responsible for architecting, building, and operating the AWS-based infrastructure that powers our broker-dealer and clearing platform. You will own critical infrastructure domains end-to-end and drive technical decisions that affect the reliability, security, and scalability of systems handling real financial transactions.

As the industry evolves rapidly with generative AI and agentic workflows, we need engineers who combine deep AWS and Kubernetes expertise with the vision and initiative to define how AI/ML tools and patterns can transform infrastructure operations, developer productivity, and platform resilience. This role carries significant technical influence — you will shape infrastructure strategy, lead complex cross-functional initiatives, and raise the bar for engineering practices across the organization.

What sets this role apart

This is not a ticket-driven infrastructure role. At the Senior-to-Staff level, we expect you to:

• Own domains, not just tasks. You will be the technical authority for critical infrastructure areas (e.g., EKS platform, observability strategy, DR architecture, or AI infrastructure) and drive their roadmap.
• Define technical direction. Author architectural decision records (ADRs), propose infrastructure standards, and influence engineering-wide technology choices through design reviews and RFCs.
• Lead without a title. Drive cross-team initiatives, align stakeholders, unblock other engineers, and represent infrastructure perspectives in leadership discussions and planning.
• Multiply the team. Elevate the entire CIN team through mentorship, code reviews, knowledge sharing, and building reusable frameworks and golden paths that scale beyond your individual output.
• Bridge infrastructure and business. Translate complex technical trade-offs into clear recommendations for engineering leadership, product teams, and compliance stakeholders.

Your impact

• Cloud Infrastructure Architecture & Platform Engineering
  • Architect, deploy, and operate production AWS infrastructure supporting high-availability financial services workloads (EKS, MSK, RDS/Aurora PostgreSQL, OpenSearch, ElastiCache, S3, CloudFront, and more).
  • Own and evolve the Infrastructure as Code (IaC) strategy using Terraform — define module standards, enforce code review practices, and drive adoption of reusable patterns across teams.
  • Lead Kubernetes (EKS) platform strategy, including cluster upgrades, node group architecture, Helm chart governance, service mesh evolution, and workload autoscaling policies.
  • Design and drive CI/CD platform improvements (GitHub Actions, ArgoCD, or similar) to enable safe, fast, and self-service deployments for application engineering teams.
  • Architect and validate disaster recovery (DR) strategies, including cross-region failover designs, backup automation, and leading DR simulation exercises.
  • Lead infrastructure design reviews and architectural discussions; ensure solutions meet scalability, security, and compliance requirements before implementation.
• Reliability, Observability & Operational Excellence
  • Define and drive the observability strategy across the platform (Datadog, Prometheus, Grafana, CloudWatch, OpenSearch) — including SLO/SLI frameworks, alerting standards, and distributed tracing.
  • Serve as a senior on-call escalation point; lead root-cause analysis on critical production incidents and drive systemic improvements through blameless post-mortems.
  • Own monthly resource saturation reviews and capacity planning processes; proactively identify scaling needs and present findings to engineering leadership.
  • Drive cloud cost optimization strategy: FinOps practices, Reserved Instances/Savings Plans analysis, vendor spend governance, and accountability frameworks across teams.
• Security, Compliance & Networking
  • Define and enforce security architecture standards across AWS environments: IAM policy governance, VPC design patterns, encryption strategies, secrets management (Vault, AWS Secrets Manager), and vulnerability remediation workflows.
  • Partner with Security, Compliance, and Audit teams to ensure infrastructure meets FINRA, SEC, SOC 2, and other regulatory requirements — and proactively identify gaps before they become findings.
  • Own networking architecture decisions including VPC topology, Transit Gateway strategy, VPN configurations, load balancer patterns (ALB/NLB), CDN optimization (Fastly/CloudFront), and DNS management.
• AI/ML Infrastructure & Developer Productivity
  • Define the strategy for evaluating, integrating, and governing AI-powered developer tools (e.g., Cursor AI, GitHub Copilot, CodeRabbit) across the engineering organization — including usage analytics, cost optimization, security review, and policy frameworks.
  • Architect infrastructure for AI/ML workloads: GPU-enabled compute, SageMaker endpoints, Bedrock integration, vector databases, and data pipeline orchestration.
  • Lead the adoption of AI-driven automation for infrastructure operations — intelligent alerting, anomaly detection, auto-remediation, and AIOps patterns — moving from exploration to production integration.
  • Build and champion internal platforms and golden paths that leverage generative AI to improve developer experience, reduce operational toil, and accelerate delivery velocity.
• Technical Leadership & Collaboration
  • Act as a trusted technical advisor to the Director of Engineering and engineering leadership on infrastructure strategy, trade-offs, and investment priorities.
  • Lead cross-functional initiatives spanning application engineering, data, security, and DevSecOps teams — driving alignment on complex multi-team infrastructure projects.
  • Represent the CIN team in architecture review boards, incident response leadership, and engineering-wide planning sessions.
  • Author and maintain comprehensive technical documentation, runbooks, ADRs, and operational procedures that serve as organizational knowledge assets.
  • Mentor senior and mid-level engineers; conduct thorough design and code reviews; actively contribute to hiring and onboarding processes for the CIN team.

What you bring

• 5+ years of hands-on experience in cloud infrastructure engineering, with deep, production-proven expertise in AWS.
• Track record of owning and driving infrastructure initiatives end-to-end — from design and architecture through implementation, rollout, and operational excellence.
• Expert-level proficiency with Terraform, including module design, state management strategies, and establishing IaC standards for engineering teams.
• Extensive production experience operating Kubernetes (EKS strongly preferred) at scale — cluster lifecycle management, multi-tenancy patterns, Helm governance, and GitOps workflows.
• Strong Linux systems engineering skills and advanced scripting proficiency (Python, Bash, or Go).
• Deep expertise in CI/CD platforms (GitHub Actions, ArgoCD, Jenkins) with experience designing deployment strategies for multi-service architectures.
• Expert-level understanding of cloud networking (VPC architecture, Transit Gateway, peering, DNS, load balancing) and security (IAM, KMS, WAF, GuardDuty, Secrets Manager).
• Proven experience designing and operating observability platforms (Datadog, Prometheus/Grafana, CloudWatch, OpenSearch/ELK) at organizational scale.
• Strong experience with database infrastructure and data layer architecture (Aurora PostgreSQL, RDS, ElastiCache/Redis, OpenSearch, DynamoDB).
• Demonstrated ability to lead disaster recovery planning, execute DR simulations, and design HA architecture patterns for mission-critical systems.
• Excellent technical communication skills — ability to write clear ADRs, present to leadership, and translate infrastructure complexity for non-technical stakeholders.
• Proven track record of mentoring engineers and elevating team capabilities through knowledge sharing, design reviews, and tooling improvements.

Bonus points

• 7+ years of infrastructure or platform engineering experience, including 3+ years operating at a senior or staff level.
• Experience in financial services, fintech, broker-dealer, or other heavily regulated industries with FINRA/SEC compliance requirements.
• AWS certifications at the Professional or Specialty level: Solutions Architect Professional, DevOps Engineer Professional, Security Specialty, or Machine Learning Specialty.
• Experience with event streaming platforms at scale (Amazon MSK / Apache Kafka) including cluster operations, partition strategy, and consumer group management.
• Hands-on experience with API gateway management and platform design (Kong, AWS API Gateway).
• Demonstrated experience with AI/ML infrastructure: provisioning GPU compute, SageMaker/Bedrock integration, vector databases, MLOps pipelines, or AIOps automation in production.
• Experience defining and executing organizational rollout strategies for AI developer tools, including governance frameworks, usage analytics, and cost management.
• Proficiency with policy-as-code frameworks (OPA/Rego, Sentinel, Kyverno) for infrastructure governance and compliance automation.
• FinOps certification or demonstrated experience leading cloud cost optimization programs at scale.
• Experience authoring RFCs, ADRs, or technical strategy documents that influenced engineering-wide decisions.
• Contributions to open-source projects, conference talks, or published technical writing.

This role follows a hybrid schedule, with three days per week onsite in our San Francisco FiDi office.

The opportunity

We're hiring a Senior Cloud Infrastructure Engineer to join the Cloud Infrastructure & Platform (CIN) team at Altruist. This is a high-impact, senior individual contributor role responsible for architecting, building, and operating the AWS-based infrastructure that powers our broker-dealer and clearing platform. You will own critical infrastructure domains end-to-end and drive technical decisions that affect the reliability, security, and scalability of systems handling real financial transactions.

As the industry evolves rapidly with generative AI and agentic workflows, we need engineers who combine deep AWS and Kubernetes expertise with the vision and initiative to define how AI/ML tools and patterns can transform infrastructure operations, developer productivity, and platform resilience. This role carries significant technical influence — you will shape infrastructure strategy, lead complex cross-functional initiatives, and raise the bar for engineering practices across the organization.

What sets this role apart

This is not a ticket-driven infrastructure role. At the Senior-to-Staff level, we expect you to:

• Own domains, not just tasks. You will be the technical authority for critical infrastructure areas (e.g., EKS platform, observability strategy, DR architecture, or AI infrastructure) and drive their roadmap.
• Define technical direction. Author architectural decision records (ADRs), propose infrastructure standards, and influence engineering-wide technology choices through design reviews and RFCs.
• Lead without a title. Drive cross-team initiatives, align stakeholders, unblock other engineers, and represent infrastructure perspectives in leadership discussions and planning.
• Multiply the team. Elevate the entire CIN team through mentorship, code reviews, knowledge sharing, and building reusable frameworks and golden paths that scale beyond your individual output.
• Bridge infrastructure and business. Translate complex technical trade-offs into clear recommendations for engineering leadership, product teams, and compliance stakeholders.

Your impact

• Cloud Infrastructure Architecture & Platform Engineering
  • Architect, deploy, and operate production AWS infrastructure supporting high-availability financial services workloads (EKS, MSK, RDS/Aurora PostgreSQL, OpenSearch, ElastiCache, S3, CloudFront, and more).
  • Own and evolve the Infrastructure as Code (IaC) strategy using Terraform — define module standards, enforce code review practices, and drive adoption of reusable patterns across teams.
  • Lead Kubernetes (EKS) platform strategy, including cluster upgrades, node group architecture, Helm chart governance, service mesh evolution, and workload autoscaling policies.
  • Design and drive CI/CD platform improvements (GitHub Actions, ArgoCD, or similar) to enable safe, fast, and self-service deployments for application engineering teams.
  • Architect and validate disaster recovery (DR) strategies, including cross-region failover designs, backup automation, and leading DR simulation exercises.
  • Lead infrastructure design reviews and architectural discussions; ensure solutions meet scalability, security, and compliance requirements before implementation.
• Reliability, Observability & Operational Excellence
  • Define and drive the observability strategy across the platform (Datadog, Prometheus, Grafana, CloudWatch, OpenSearch) — including SLO/SLI frameworks, alerting standards, and distributed tracing.
  • Serve as a senior on-call escalation point; lead root-cause analysis on critical production incidents and drive systemic improvements through blameless post-mortems.
  • Own monthly resource saturation reviews and capacity planning processes; proactively identify scaling needs and present findings to engineering leadership.
  • Drive cloud cost optimization strategy: FinOps practices, Reserved Instances/Savings Plans analysis, vendor spend governance, and accountability frameworks across teams.
• Security, Compliance & Networking
  • Define and enforce security architecture standards across AWS environments: IAM policy governance, VPC design patterns, encryption strategies, secrets management (Vault, AWS Secrets Manager), and vulnerability remediation workflows.
  • Partner with Security, Compliance, and Audit teams to ensure infrastructure meets FINRA, SEC, SOC 2, and other regulatory requirements — and proactively identify gaps before they become findings.
  • Own networking architecture decisions including VPC topology, Transit Gateway strategy, VPN configurations, load balancer patterns (ALB/NLB), CDN optimization (Fastly/CloudFront), and DNS management.
• AI/ML Infrastructure & Developer Productivity
  • Define the strategy for evaluating, integrating, and governing AI-powered developer tools (e.g., Cursor AI, GitHub Copilot, CodeRabbit) across the engineering organization — including usage analytics, cost optimization, security review, and policy frameworks.
  • Architect infrastructure for AI/ML workloads: GPU-enabled compute, SageMaker endpoints, Bedrock integration, vector databases, and data pipeline orchestration.
  • Lead the adoption of AI-driven automation for infrastructure operations — intelligent alerting, anomaly detection, auto-remediation, and AIOps patterns — moving from exploration to production integration.
  • Build and champion internal platforms and golden paths that leverage generative AI to improve developer experience, reduce operational toil, and accelerate delivery velocity.
• Technical Leadership & Collaboration
  • Act as a trusted technical advisor to the Director of Engineering and engineering leadership on infrastructure strategy, trade-offs, and investment priorities.
  • Lead cross-functional initiatives spanning application engineering, data, security, and DevSecOps teams — driving alignment on complex multi-team infrastructure projects.
  • Represent the CIN team in architecture review boards, incident response leadership, and engineering-wide planning sessions.
  • Author and maintain comprehensive technical documentation, runbooks, ADRs, and operational procedures that serve as organizational knowledge assets.
  • Mentor senior and mid-level engineers; conduct thorough design and code reviews; actively contribute to hiring and onboarding processes for the CIN team.

What you bring

• 5+ years of hands-on experience in cloud infrastructure engineering, with deep, production-proven expertise in AWS.
• Track record of owning and driving infrastructure initiatives end-to-end — from design and architecture through implementation, rollout, and operational excellence.
• Expert-level proficiency with Terraform, including module design, state management strategies, and establishing IaC standards for engineering teams.
• Extensive production experience operating Kubernetes (EKS strongly preferred) at scale — cluster lifecycle management, multi-tenancy patterns, Helm governance, and GitOps workflows.
• Strong Linux systems engineering skills and advanced scripting proficiency (Python, Bash, or Go).
• Deep expertise in CI/CD platforms (GitHub Actions, ArgoCD, Jenkins) with experience designing deployment strategies for multi-service architectures.
• Expert-level understanding of cloud networking (VPC architecture, Transit Gateway, peering, DNS, load balancing) and security (IAM, KMS, WAF, GuardDuty, Secrets Manager).
• Proven experience designing and operating observability platforms (Datadog, Prometheus/Grafana, CloudWatch, OpenSearch/ELK) at organizational scale.
• Strong experience with database infrastructure and data layer architecture (Aurora PostgreSQL, RDS, ElastiCache/Redis, OpenSearch, DynamoDB).
• Demonstrated ability to lead disaster recovery planning, execute DR simulations, and design HA architecture patterns for mission-critical systems.
• Excellent technical communication skills — ability to write clear ADRs, present to leadership, and translate infrastructure complexity for non-technical stakeholders.
• Proven track record of mentoring engineers and elevating team capabilities through knowledge sharing, design reviews, and tooling improvements.

Bonus points

• 7+ years of infrastructure or platform engineering experience, including 3+ years operating at a senior or staff level.
• Experience in financial services, fintech, broker-dealer, or other heavily regulated industries with FINRA/SEC compliance requirements.
• AWS certifications at the Professional or Specialty level: Solutions Architect Professional, DevOps Engineer Professional, Security Specialty, or Machine Learning Specialty.
• Experience with event streaming platforms at scale (Amazon MSK / Apache Kafka) including cluster operations, partition strategy, and consumer group management.
• Hands-on experience with API gateway management and platform design (Kong, AWS API Gateway).
• Demonstrated experience with AI/ML infrastructure: provisioning GPU compute, SageMaker/Bedrock integration, vector databases, MLOps pipelines, or AIOps automation in production.
• Experience defining and executing organizational rollout strategies for AI developer tools, including governance frameworks, usage analytics, and cost management.
• Proficiency with policy-as-code frameworks (OPA/Rego, Sentinel, Kyverno) for infrastructure governance and compliance automation.
• FinOps certification or demonstrated experience leading cloud cost optimization programs at scale.
• Experience authoring RFCs, ADRs, or technical strategy documents that influenced engineering-wide decisions.
• Contributions to open-source projects, conference talks, or published technical writing.

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.