The Senior Machine Learning Engineer will join our ML team.  This team is responsible for building, maintaining, and monitoring the production ML models and offline experimentation frameworks that are at the core of Signifyd’s product. This includes the core fraud detection model that decides the majority of our traffic, alongside our model training and evaluation infrastructure. We work closely with Platform Engineering teams to contribute novel modeling methods, advanced feature engineering, and robust statistical practices.

Our Culture

We value tenacity, curiosity, and a hunger for learning. Our adversaries are highly motivated fraudsters looking to exploit any gap. We seek equally motivated individuals who are passionate about keeping our customers safe while pulling the field of adversarial machine learning forward.

The Role

As a Senior Machine Learning Engineer, you will be a driver of technical execution within the ML team. You won’t just build models—you’ll own the end-to-end lifecycle of high-impact ML projects, from offline experimentation to deployment to production. You will be responsible for improving model performance, refining our experimentation processes, and ensuring our fraud detection systems are robust, scalable, and scientifically sound.

Responsibilities:

• Expand ML Capabilities – Identify, prototype, and integrate new ML technologies and infrastructure to enhance fraud detection effectiveness and scalability.
• Enable High-Velocity Experimentation – Own the design and implementation of ML pipeline components that accelerate our innovation
• Collaborate Across Functions – Partner with Product, Engineering, and Risk teams to translate business requirements into technical solutions and ensure ML initiatives align with customer needs.
• Raise the Bar – Foster a culture of technical excellence by championing best practices in testing, documentation, model monitoring, and development.

Requirements:

• Education: A degree in Computer Science, Statistics, or a comparable quantitative field.
• Experience: 4-6+ years of post-undergrad work experience in a production-grade ML environment.
• Technical Depth: Strong foundation in machine learning theory, statistical evaluation, and experience with supervised/unsupervised learning at scale.
• Execution Focus: Proven track record of taking ML projects from research/prototype to high-scale production environments.
• Communication: Ability to communicate technical findings clearly to both technical peers and non-technical stakeholders.
• Tech Stack: Proficiency in Python, SQL, key ML libraries, and Spark
• Mindset: A strong outcome-oriented mindset—you care about the "why" behind the models and the business impact they create.
• Attention to detail is critical in fraud prevention. To demonstrate this, please start your response to the first application question with the word 'Stochastic'

Nice to have:

• Previous experience in fraud, fintech, payments, or e-commerce.
• Passion for writing well-tested production-grade code
• A Master’s Degree or PhD.

Why Join Us?

• Make an Impact – Your work will directly shape the future of fraud prevention, protecting billions of payments.
• Lead & Grow – Drive high-visibility initiatives and develop leadership skills in a fast-paced, high-growth environment.
• Innovate at Scale – Work with cutting-edge ML technologies and experiment freely to push the boundaries of what’s possible.
• Collaborative Culture – Join a team that values curiosity, ownership, and continuous learning.

#LI-Remote

Benefits in our US offices:

• Discretionary Time Off Policy (Unlimited!)
• 401K Match
• Stock Options
• Annual Performance Bonus or Commissions
• Paid Parental Leave (12 weeks)
• On-Demand Therapy for all employees & their dependents
• Dedicated learning budget through Learnerbly
• Health Insurance
• Dental Insurance
• Vision Insurance
• Flexible Spending Account (FSA)
• Short Term and Long Term Disability Insurance
• Life Insurance
• Company Social Events
• Signifyd Swag

Compensation: 

In the United States, each work location is assigned a specific pay zone, which determines the salary range for a given position. The starting base salary for the selected candidate will be based on a variety of factors, including job-related skills, experience, qualifications, geographic location, and current market conditions.

Base Salary Ranges by Pay Zone:

• Tier 1 (NYC/SF Bay Area/Seattle):  $160,000 - $190,000 annually
• Tier 2 (DC Metro/Austin/Chicago/Denver/Boston/Los Angeles/San Diego):$150,000 - $180,000 annually
• Tier 3 (US - All Other): $140,000 - $170,000 annually

Equity: This role is eligible for a stock option grant of 4,000 stock options, based on the position level and internal compensation guidelines. 

Bonus: This role is eligible for an annual performance bonus of up to 10% of base salary.

We want to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.

Scale’s Generative AI business unit is currently seeing historic levels of growth. As a Strategic Projects Lead (SPL), you will  leading initiatives that will drive $XXM+ in new revenue for the business. This is a demanding role, and as an SPL, you should be prepared to wear many hats such as Operator, Product Manager and customer-facing Engagement Manager. The ideal SPL should have a strong entrepreneurial mindset, be comfortable getting into the weeds, and be excited about intense, impactful work that leads to an accelerated career progression.

You will:

• Lead cross-functional projects with diverse stakeholders (Engineering + Ops + Go-to-Market)
• Partner with product and engineering teams to enhance products to fulfill needs of strategic customers and initiatives
• Own the execution of our data labeling operations for strategic projects
• Give regular progress updates to Scale’s executive team
• Work on some of the most impactful problems at the company

Ideally, you’d have:

• Strong technical background (a degree in computer science is ideal, and at minimum the role requires the ability to do data analytics using SQL or Python).
• 2+ years of experience leading a team, developing product or operational processes, or as a SWE. 
• Strong problem solving capabilities (experience working on operational challenges or as a consultant is a plus). 
• Entrepreneurial experience and mindset - you are excited about building things from scratch

About the team + role

We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards.

The Platforms Data Science team sits at the intersection of customer experience and trust, building the intelligence that powers how Robinhood supports its customers. The team develops systems that safeguards customers and the platform while making every interaction smarter: from the in-app AI assistant that helps customers research, trade, and manage their portfolios, to the AI-powered support chatbot that resolves issues autonomously, to the machine learning systems that detect and prevent fraud and abuse in real time. These systems rely on evaluation frameworks and guardrails that maintain reliability and safety across the platform. You will work with product engineering, product management, and ML infrastructure teams to deliver production-ready AI systems at scale. Join a team where your work directly shapes how customers interact with Robinhood!

As a Data Scientist, Agentic (CX), you will lead machine learning development across the customer experience stack. This includes models and prompts that power multi-agent orchestration, evaluation pipelines that measure model quality at scale, and personalization systems that determine when and how to engage customers. You will partner closely with product and engineering to improve reasoning, expand tool usage, and strengthen feedback loops between live systems and offline evaluation. The role offers ownership from experimentation through deployment, with opportunities to apply advanced AI techniques in a regulated environment!                                

This role is based in our Menlo Park, CA and New York, NY offices, with in-person attendance expected at least 3 days per week.

At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams. 

What you’ll do

• Build and deploy machine learning models for customer support systems, including intent classification, escalation detection, clarification, summarization, and multi-agent orchestration
• Design evaluation frameworks using LLM-based review methods, human feedback loops, and automated quality metrics to identify regressions before customer impact
• Develop propensity, segmentation, and personalization models that support proactive outreach and tailored AI experiences
• Translate advances in agent architectures into production systems, partnering with engineering on prompt design, retrieval systems, tool use, memory, and orchestration
• Develop systems that maintain response quality and reliability at scale while working with product, engineering, legal, and compliance partners

What you bring

• You have strong Python and SQL skills, with experience building and evaluating machine learning systems end to end
• You have experience with agent-based AI systems, including reasoning loops, tool use, memory, retrieval-augmented generation, and orchestration
• You have experience designing experiments and applying causal inference methods, including A/B testing and measurement design
• You are comfortable working through ambiguous problems and collaborating with partners across product and engineering

Preferred Qualifications

• Experience building and evaluating agent-based systems for production use
• Experience developing recommendation, ranking, or personalization systems at scale
• Experience working on AI products in regulated industries such as financial services.

What we offer

• Challenging, high-impact work to grow your career.
• Performance-driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching.
• Best-in-class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents.
• Lifestyle wallet — a highly flexible benefits spending account for wellness, learning, and more.
• Employer-paid life & disability insurance, fertility benefits, and mental health benefits.
• Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!
• Exceptional office experience with catered meals, events, and comfortable workspaces.

About the Company   

At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.   
A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight.   
Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.    

Meet The Team:    

Torc is marching towards its AV 3.0 strategy. Simulation and Data Generation are key elements towards autonomous trucking. The team builds the sensor simulation based on Neural Rendering and Generative models for Torc’s data-driven simulator. High-quality data from novel scenarios close the domain data gap, solving one of the biggest challenges for safe autonomous driving.  The team works on state-of-the-art approaches for Neural Rendering and data generation for camera, LiDAR, and Radar sensor data, that contributes to the Torc’s data workflow for training and validation across the complete AV stack.   

What You’ll Do:    

• Implement the latest research advances in Neural Rendering and generative models 
• Translate cutting edge solution in the domain of autonomous driving for high-quality Camera, LiDAR and Radar sensor simulations 
• Support implementing a neural rendering framework that allows to scale perception simulation and AV 3.0 training 
• Integrate the framework in a cloud environment and automate the pipeline to allow scaling for the target verification and validation of our autonomous trucks  
• Own development projects in the team – From research, design, to implementation, testing and deployment 
• Design, implement, test and deploy shippable production quality software starting from early prototypes using disciplined software development processes.
• Work in the cloud machine learning ecosystem alongside other machine learning services existing in the company.
• Proactively assess current capabilities to identify areas for improvement proposing solutions that align with core strategy and operation. 
• Demonstrate project management skills, serving as project lead guiding less experienced team members in multiple facets of project execution, coaching and mentoring as needed.   

What You’ll Need to Succeed:    

• Proficiency in Python and deep learning frameworks such as PyTorch. 
• PhD or equivalent work experience of 6+ years in relevant fields (CS, Robotics, Electrical Engineering) with industry experience in shipping production software. 
• Proven expertise in Neural Rendering (Neural Radiance Fields and 3D Gaussian Splatting) and generative models (Diffusion Models, Flow Matching). 
• Background in Computer Graphics, 3D Reconstruction, or 3D Computer Vision. 
• Considered highly skilled and proficient in discipline; conducts complex, important work under minimal supervision and with wide latitude for independent judgment.   
• Experience with VDI and cloud based machine learning development environments.
• Expected to drive alignment across team interfaces to the rest of the organization.  
• Designs, maintains and owns team technical solutions and drives consensus.   
• Mentors and guides engineers within the group.    

Bonus Points!  

• Experience with autonomous driving or robotics perception in production environments. 
• Proficiency with CUDA programming for efficient rendering of large-scale scenes 
• Publications in top-tier CV/AI/Graphics conferences (CVPR/ECCV/ICCV, NeurIPS/ICLR/ICML, SIGGRAPH) or journals 
• Experience with MLOps and infrastructure tools (Ray) 
• Familiarity with 3D labeling, calibration, and sensor simulation pipelines.  
• Handling of Autonomous Driving Sensors – Multiple timestamp, multiple sensor data from cameras, lidars, and radars  

Perks of Being a Full-time Torc’r   
Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:     

• A competitive compensation package that includes a bonus component and stock options 
• 100% paid medical, dental, and vision premiums for full-time employees  
• 401K plan with a 6% employer match  
• Flexibility in schedule and generous paid vacation (available immediately after start date) 
• AD+D and Life Insurance   

At Torc, we’re committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc’rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities.  
Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply.  

Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. 

US Base Pay Range:

$160,800 - $212,300

Job ID: R-102432

Data Analytics Engineer — Boulder, Colorado

Full-time | Boulder, CO | No visa sponsorship available

The US Analytics team is building the data foundations that power SumUp's US operations. We design reliable data models, keep our infrastructure clean, and turn complex datasets into insights the business can act on. You'll join at a point where there's real work to own — from shaping how data is structured to improving the tools and dashboards that teams rely on every day. If you're someone who's been close to data in an analytical role and is ready to go deeper into how it's built and maintained, this is a meaningful next step.

👉 Take a look at our Boulder office

What you'll do

• Build, maintain, and document DBT models in a Snowflake environment, keeping data clean, reliable, and well-structured
• Develop and maintain Tableau dashboards and data sources that stakeholders across the business trust and use independently
• Rotate through day-to-day data operations support — handling ad hoc requests, troubleshooting reporting issues, and diagnosing pipeline problems
• Contribute to modernizing our data infrastructure, helping business stakeholders self-serve through AI-assisted tooling
• Own stakeholder relationships independently — gathering requirements, setting clear expectations, and communicating confidently with technical and non-technical audiences alike

You'll be great for this role if…

• Strong experience building or structuring datasets — not just querying them based on others work
• Solid SQL skills and hands-on experience with Snowflake and DBT Core
• Proven ability to build Tableau dashboards that stakeholders genuinely rely on
• Strong communicator who can own stakeholder conversations, gather requirements, manage expectations, and push back when a request isn't clearly defined
• High attention to data quality and the confidence to work through problems independently before escalating
• Familiarity with AI-assisted data tools such as GitHub Copilot or Cursor
• Familiarity with Salesforce

Bonus points for:

• Experience with self-serve or semantic data layers
• Contributions to an AI agent knowledge base or prompt engineering work
• Understanding of the limitations of LLMs when applied to data problems
• Previous experience in a fast paced, team environment

Why you should join SumUp

• 🌍 Opportunity to work with SumUppers globally on large-scale fintech products used by millions of businesses worldwide, from our Boulder office. This involves an office-first setup
• 🚀 Enrollment onto our Virtual Stock Option program: you will own a stake in SumUp's future success
• 📚 A dedicated annual learning budget of $2,000 for your individual development, which can be used to attend conferences and/or advance your career through further education
• 🏖 Generous time off: 22 days of paid vacation, plus an extra day each year up to 28 days, public holidays, and special leaves
• 🏥 Health and life coverage: group medical coverage, plus life insurance
• 💼 Financial security: 401(k) retirement scheme with SumUp matching funds
• 🌴 Break4me: 1-month sabbatical after 3 years of service
• 🌈 Commitment to Diversity and Inclusion: be part of a workplace that values and promotes diversity, fostering an inclusive environment where everyone's perspectives are respected and embraced

Compensation:

• $95,000–$115,000 base salary
• Final compensation will be based on the candidate's experience and location

About SumUp

Be empowered to do more that matters.

At SumUp, we're on a mission to empower small businesses across the globe by providing simple and affordable tools that allow them to thrive. Today, over 4 million businesses in 37 markets rely on SumUp as their financial partner to manage payments, finance and customer relationships.

Our commitment to small businesses is reflected in our diverse team of over 4,000 SumUppers from over 90 nationalities, united by global collaboration and an innovative mindset. Our core values lay the foundation for who we are and what we stand for, shaping our work culture and driving our success. We foster inclusivity and a continuous learning culture, providing a safe space for personal and professional growth. Our differences make us unique and strong as we strive to create an environment where everyone belongs and feels supported, no matter how they identify.

SumUp is proud to be an Equal Employment Opportunity employer, actively seeking and embracing diversity in our workforce. We don't make hiring or employment decisions based on race, colour, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age or any other basis protected by applicable laws or prohibited by company policy. Our commitment extends beyond recruitment to creating a safe and respectful workplace where harassment of any form is strictly prohibited. Discover more about our culture and opportunities on our careers website, and follow our journey on LinkedIn, Instagram, and TikTok.

WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com.

THE ROLE

Zeta Global is looking for a seasoned, external client-engaging Senior Manager, Data Science & Analytics (individual contributor role) for its ZX Activation division.  They will be responsible for prescribing a performance-oriented marketing and analytics strategy to achieve optimal performance in the client’s customer acquisition efforts.  

This position will partner with cross-functional teams including but not limited to Sales, Client Success, Operations, Engineering, and Data Cloud. You will support strategic growth initiatives by delivering actionable insights to helping clients acquire new customers.  You will benefit from a globally distributed Analytics team that provides essential support across data QA, reporting, and tool creation, allowing you to prioritize high-impact strategy work. 

RESPONSIBILITIES

• Strategic Leadership 
  • Define and drive a clear analytics vision aligned to client engagement, media performance, and marketing measurement priorities. 
  • Champion a data-driven culture by embedding analytics into strategic planning, campaign optimization, and decision-making processes. 
  • Lead the development and execution of measurement frameworks tailored to each client’s objectives, ensuring alignment with business goals. 
• Data & Analytics 
  • Translate data into actionable insights by identifying performance drivers, resolving anomalies, and crafting compelling narratives that demonstrate media impact. 
  • Establish and maintain robust testing frameworks that are statistically valid and operationally scalable. 
  • Drive confidence and alignment by delivering actionable insights rooted in analytics, business strategy, and persuasive communication. 
  • Provide business feedback as a key stakeholder in the development of standardized dashboards and advanced analytics to measure the effectiveness of campaigns. 
  • Leverage predictive and prescriptive analytics to identify trends, opportunities, and risks related to client behavior and retention. 
• Marketing Measurement 
  • Utilize advanced analytics to quantify marketing impact and ROI, and partner cross-functionally to diagnose and address performance irregularities. 
  • Implement robust A/B and multivariate testing and experimentation protocols to optimize campaigns and maximize impact. 

REQUIREMENTS

• Master’s degree in Analytics, Management Science, MIS or similar quantitative disciplines. 
• 8+ years of experience in Analytics, marketing measurement, campaign optimizations, with a strong focus on email marketing. 
• Expertise in advanced analytics tools and Business Intelligence tools. 
• Proven experience designing and scaling experiments in a digital environment. 
• Exceptional analytical and problem-solving skills with the ability to translate complex data into actionable insights. 
• Excellent communication and presentation skills, with the ability to influence senior stakeholders and clients. 

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee Equity
• Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!!

SALARY RANGE

The salary range for this role is $125,000 - $145,000 depending on location and experience. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation, gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging, so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate, support and advocate for one another. Learn more about our commitment to diversity, equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

#LI-ND1

#LI-remote

See yourself at Twilio

Join the team as Twilio’s next L3, Machine Learning Engineer, Trust Intelligence Platform.

About the job

Join Twilio’s rapidly-growing AI & Data Platform team as an  Machine Learning Engineer. You will design, build, and operate the cloud-native data and ML infrastructure that powers every customer interaction, enabling Twilio’s product teams and customers to move from raw events to real-time intelligence. This is a hands-on, builder-focused role that offers clear technical ownership, mentoring, and growth inside a company defining the future of communications with AI.

Responsibilities

In this role, you’ll:

• Architect, implement, and maintain scalable data pipelines and feature stores for batch and real-time workloads.
• Build reproducible ML training, evaluation, and inference workflows using modern orchestration and MLOps tooling.
• Integrate event streams from Twilio products (e.g., Messaging, Voice, Segment) into unified, analytics-ready datasets.
• Monitor, test, and improve data quality, model performance, latency, and cost.
• Partner with product, data science, and security teams to ship resilient, compliant services.
• Automate deployment with CI/CD, infrastructure-as-code, and container orchestration best practices.
• Produce clear documentation, dashboards, and runbooks; share knowledge through code reviews and brown-bag sessions.
• Embrace Twilio’s “We are Builders” values by taking ownership of problems and driving them to completion.

Qualifications 

Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!

*Required:

• B.S. in Computer Science, Data Engineering, Electrical Engineering, Mathematics, or related field—or equivalent practical experience.
• 3–5 years building and operating data or ML systems in production.
• Proficient in Python and SQL; comfortable with software engineering fundamentals (testing, version control, code reviews).
• Hands-on experience with ETL/ELT orchestration tools (e.g., Airflow, Dagster) and cloud data warehouses (Snowflake, BigQuery, or Redshift).
• Familiarity with ML lifecycle tooling such as MLflow, SageMaker, Vertex AI, or similar.
• Working knowledge of Docker and Kubernetes and at least one major cloud platform (AWS, GCP, or Azure).
• Understanding of data modeling, distributed computing concepts, and streaming frameworks (Spark, Flink, or Kafka Streams).
• Strong analytical thinking, communication skills, and a demonstrated sense of ownership, curiosity, and continuous learning.

Desired:

• Experience with Twilio Segment, Kafka/Kinesis, or other high-throughput event buses.
• Exposure to infrastructure-as-code (Terraform, Pulumi) and GitHub-based CI/CD pipelines.
• Practical knowledge of generative AI workflows, foundation-model fine-tuning, or vector databases.
• Contributions to open-source data/ML projects or published technical presentations/blogs.
• Domain experience in communications, marketing automation, or customer engagement analytics.

Location

This role will be remote, but is not eligible to be hired in CA, CT, NJ, NY, PA, WA.

Travel 

We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.

What We Offer

Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.

Compensation

*Please note this role is open to candidates outside of California, Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Washington D.C., and Washington State. The information below is provided for candidates hired in those locations only.

The estimated pay ranges for this role are as follows:

• Based in Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Vermont or Washington D.C. : $138,700 - $173,400.
• Based in New York, New Jersey, Washington State, or California (outside of the San Francisco Bay area): $146,800 - $183,600.
• Based in the San Francisco Bay area, California: $163,100 - 203,900.
• This role may be eligible to participate in Twilio’s equity plan and corporate bonus plan. All roles are eligible for the following benefits: health care insurance, 401(k) retirement account, paid sick time, paid personal time off, paid parental leave.

The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location.. 

Applications for this role are intended to be accepted until May 20, 2026 but may change based on business needs. 

ABOUT THE TEAM

The Maneuver Dominance team at Anduril develops operationally relevant, multi-asset autonomy. We are focused on making large groups of autonomous systems work effectively together, with a particular emphasis on larger, more capable unmanned aerial vehicles. Our team specializes in integrating advanced perception and autonomy algorithms into complex aerial platforms, pushing the boundaries of what's possible in autonomous flight and mission execution. We develop cutting-edge Computer Vision and Autonomy algorithms to solve some of the hardest problems facing our customers, particularly in challenging and dynamic environments where robust perception is critical.

ABOUT THE JOB

We are seeking an experienced Computer Vision Engineer with a strong background in robotics to join our rapidly growing team in Costa Mesa, CA. In this role, you will be at the forefront of developing advanced perception systems for complex autonomous aerial platforms. Your expertise in computer vision algorithms, combined with your understanding of robotics principles, will be crucial in solving a wide variety of challenges involving visual perception, SLAM, motion planning, controls, and state estimation.

This role requires not only technical expertise in computer vision and robotics but also the ability to make pragmatic engineering tradeoffs, considering the unique constraints of aerial platforms. Your work will directly contribute to the seamless integration of Anduril's products, achieving critical outcomes in autonomous operations. This position demands strong systems-level knowledge and experience, as you'll be working on the intersection of computer vision, robotics, and autonomous systems. If you are passionate about pushing the boundaries of computer vision in robotics, possess a "Whatever It Takes" mindset, and can execute in an expedient, scalable, and pragmatic way while keeping the mission top-of-mind and making sound engineering decisions, then this role is for you.

WHAT YOU'LL DO

• Work at the intersection of 3D perception and computer vision, developing robust algorithms that power real-time decision-making for autonomous aerial systems.
• Develop and implement advanced structure from motion and SLAM algorithms to create accurate 3D models from multiple camera inputs in real-time.
• Integrate perception outputs with path planning algorithms to enable autonomous navigation in complex, unstructured environments
• Design experiments, data collection efforts, and curate training/evaluation sets to develop insights for both internal purposes and customers.
• Collaborate closely with robotics, software, and hardware teams to integrate perception algorithms into autonomous aerial systems.
• Work with vendors and government stakeholders to advance the state-of-the-art in perception and world modeling for autonomous aerial systems.

REQUIRED QUALIFICATIONS

• BS in Robotics, Computer Science, Mechatronics, Electrical Engineering, Mechanical Engineering, or related field.
• Strong knowledge of 3D computer vision concepts, including multi-view geometry, camera models, photogrammetry, and 3D reconstruction techniques.
• Fluency in standard domain libraries (numpy, opencv, pytorch, etc).
• Proven understanding of data structures, algorithms, concurrency, and code optimization.
• 6+ years of professional industry experience working with C++ or Rust programming languages.
• Experience deploying software to end customers, internal or external.
• Must be willing to travel 25%.
• Eligible to obtain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS

• MS or PhD in Robotics, Computer Science, Mechatronics, Electrical Engineering, Mechanical Engineering, or related field.
• Experience with perception systems for aerial robotics or other highly dynamic platforms.
• Experience with real-world sensor integrations, including LiDAR, RGB-D cameras, stereo cameras, or TOF cameras.
• Knowledge of path planning algorithms and their integration with perception systems in dynamic environments.
• Experience with GPU / CUDA programming for accelerated computer vision processing.

ABOUT THE TEAM

The Maneuver Dominance team at Anduril develops operationally relevant, multi-asset autonomy. We are focused on making large groups of autonomous systems work effectively together, with a particular emphasis on larger, more capable unmanned aerial vehicles. Our team specializes in integrating advanced perception and autonomy algorithms into complex aerial platforms, pushing the boundaries of what's possible in autonomous flight and mission execution. We develop cutting-edge Computer Vision and Autonomy algorithms to solve some of the hardest problems facing our customers, particularly in challenging and dynamic environments where robust perception is critical.

ABOUT THE JOB

We are seeking an experienced Computer Vision Engineer with a strong background in robotics to join our rapidly growing team in Costa Mesa, CA. In this role, you will be at the forefront of developing advanced perception systems for complex autonomous aerial platforms. Your expertise in computer vision algorithms, combined with your understanding of robotics principles, will be crucial in solving a wide variety of challenges involving visual perception, SLAM, motion planning, controls, and state estimation.

This role requires not only technical expertise in computer vision and robotics but also the ability to make pragmatic engineering tradeoffs, considering the unique constraints of aerial platforms. Your work will directly contribute to the seamless integration of Anduril's products, achieving critical outcomes in autonomous operations. This position demands strong systems-level knowledge and experience, as you'll be working on the intersection of computer vision, robotics, and autonomous systems. If you are passionate about pushing the boundaries of computer vision in robotics, possess a "Whatever It Takes" mindset, and can execute in an expedient, scalable, and pragmatic way while keeping the mission top-of-mind and making sound engineering decisions, then this role is for you.

WHAT YOU'LL DO

• Work at the intersection of 3D perception and computer vision, developing robust algorithms that power real-time decision-making for autonomous aerial systems.
• Develop and implement advanced structure from motion and SLAM algorithms to create accurate 3D models from multiple camera inputs in real-time.
• Integrate perception outputs with path planning algorithms to enable autonomous navigation in complex, unstructured environments
• Design experiments, data collection efforts, and curate training/evaluation sets to develop insights for both internal purposes and customers.
• Collaborate closely with robotics, software, and hardware teams to integrate perception algorithms into autonomous aerial systems.
• Work with vendors and government stakeholders to advance the state-of-the-art in perception and world modeling for autonomous aerial systems.

REQUIRED QUALIFICATIONS

• BS in Robotics, Computer Science, Mechatronics, Electrical Engineering, Mechanical Engineering, or related field.
• Strong knowledge of 3D computer vision concepts, including multi-view geometry, camera models, photogrammetry, and 3D reconstruction techniques.
• Fluency in standard domain libraries (numpy, opencv, pytorch, etc).
• Proven understanding of data structures, algorithms, concurrency, and code optimization.
• 4+ years of professional industry experience working with C++ or Rust programming languages.
• Experience deploying software to end customers, internal or external.
• Must be willing to travel 25%.
• Eligible to obtain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS

• MS or PhD in Robotics, Computer Science, Mechatronics, Electrical Engineering, Mechanical Engineering, or related field.
• Experience with perception systems for aerial robotics or other highly dynamic platforms.
• Experience with real-world sensor integrations, including LiDAR, RGB-D cameras, stereo cameras, or TOF cameras.
• Knowledge of path planning algorithms and their integration with perception systems in dynamic environments.
• Experience with GPU / CUDA programming for accelerated computer vision processing.

The Notifications Relevance Team focuses on delivering the right content to the right user at the right time through push, email, and in-app notifications. Our systems and algorithms operate on the world's largest corpus of human conversation, connecting Redditors with what matters - whether it’s recommending similar posts and subreddits, surfacing conversations they’ll care about, or introducing communities they didn’t know they needed.

We are looking for an Engineering Manager to lead our Notifications Relevance team, shaping the future of Notifications at Reddit. In this role, you will lead a team of machine learning engineers dedicated to advancing our current Notifications Relevance systems. This is a high-impact team driving DAU growth and long-term user retention by connecting users to what matters most to them.

If applying ML / AI in production to improve the relevance of Reddit Notifications excites you, then you’ve found the right place.

What You’ll Do

• Lead the team that architects and designs notifications relevance at Reddit.
• Guide team on holistic, adaptive systems covering budgeting optimization, candidate retrieval, and ranking. 
• Work with ML engineers to design, implement, and optimize machine-learning models that drive personalization and user re-engagement.
• Participate in the full development cycle: design, develop, QA, experiment, analyze, and deploy.
• Build and maintain a diverse team that can collaborate across disciplines to find technical solutions to complex challenges.
• Serve as a thought partner to product and upper management to ensure your team’s plans align with company goals.
• Communicate your team’s work and set expectations with cross-functional stakeholders.
• Help your engineers identify career goals and create development plans to achieve them.
• Constantly seek opportunities to push your engineers & managers outside their comfort zone and turn followers into leaders.

You Have:

• 2+ years of experience building and managing engineering teams.
• 5+ years of experience as a Machine Learning Engineer or Software Engineer working on large-scale machine learning systems.
• Deep understanding of building and deploying large-scale recommender systems (retrieval + ranking) in production.
• Hands-on experience working with deep learning models, sequential features and real-time systems.
• Experience with distributed training and inference using tools like Ray, PyTorch Distributed, or similar.
• Familiarity with reinforcement learning or multi-objective optimization in recommendation systems.
• Entrepreneurial and self-directed, innovative, results-oriented, biased towards action in fast-paced environments.
• Able to communicate and discuss complex topics with technical and non-technical audiences.
• Able to tackle ambiguous and undefined problems

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

#LI-remote, #LI-JS5

Reddit's Ads Data Science team is seeking a highly motivated Principal Data Scientist to drive the strategic application of advanced quantitative methods across our advertising platform to advance the intelligence powering the advertiser experience on Reddit. 

In this pivotal leadership role, you will be responsible for defining and implementing the next generation of foundational data science solutions, leveraging expertise in statistics, econometrics, machine learning and/or other quantitative methods to optimize Reddit's Ads marketplace. You will partner closely with Analytics Engineering to ensure our underlying data systems are continuously upleveled to support advanced analysis and modeling at scale. You will be a strategic partner, collaborating closely with Product, Engineering, and Business leaders to establish the long-term vision for measurement, prediction, and optimization. 

As a thought leader, you will champion scientific rigor, causal inference, and economic modeling, while providing deep mentorship to the broader team. If you are passionate about applying foundational quantitative science to solve complex, high-impact business problems, join us in shaping the future of Reddit ads.

What you’ll do

• Define the future of Ads Data Science: Own the design and long-term evolution of our core Ads Data Science solutions and infrastructure, building for the next several years of continued scale, revenue growth, and relevance.
• Strategic leadership & scientific roadmap: Identify fundamental gaps and opportunities in our current systems (including platform, auction, targeting, and full-funnel relevance models). Lead the strategic design and scientific roadmap for new solutions to significantly improve Advertiser ROI, User experience, and Reddit revenue.
• Drive end-to-end impact: Take end-to-end ownership of complex problem domains such as full funnel acceleration, advertiser lifetime value (LTV), and developing advanced predictive and causal frameworks that power Reddit’s strategic investments.
• Establish scientific standards: Define and codify best practices for large-scale statistical modeling, economic analysis, causal inference, offline model evaluation, and A/B experimentation to ensure scientific rigor and trust across the Ads data science and engineering teams.
• Technical deep dive & authority: Be the undisputed domain authority for data scientists, engineers, and product managers on complex problems involving large-scale behavioral data, foundational models for strategic insights, and the economics of marketplace dynamics.
• Translate ambiguity into outcomes: Influence the design and definition of core business and performance metrics, robust measurement methodologies, and collaborate deeply with cross-org XFNs to align on strategic goals and translate insights into tangible action.
• Influence and uplevel the organization: Lead technically minded peers and mentor senior data scientists, influencing technical and statistical direction across the entire product and engineering organization, and championing innovation in ad systems through advanced quantitative techniques.

Requirements

• Demonstrated expertise in at least one of the following: ads marketplace understanding, auctioning/bidding, ads creative & format evaluation, measurement & experimentation at scale
• Master's or Ph.D. in Economics, Statistics, Computer Science, Operations Research, or a related quantitative discipline
• For M.S. holders: 12+ years of industry experience in applied science, data science, or machine learning engineering roles
• For Ph.D. holders: 8+ years of relevant experience applied science, data science, or machine learning engineering roles
• Advanced proficiency in statistical programming (Python or R) and SQL
• Experience with statistical analysis, economic modeling, foundational machine learning and/or optimization techniques
• Strong understanding of experimental design, causal inference, or A/B testing methodologies
• Exceptional problem-solving and communication skills, with a track record of influencing product and engineering partners
• Experience working in fast-paced, ambiguous environments with cross-functional teams
• Proven experience in influencing large (500+ engineers/data scientists) organizations on technical direction, statistical rigor, and machine learning best practice

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave  

The Developer Platform team is building the future of Reddit: a future where third-party developers, moderators and everyday redditors can invent and ship brand-new apps, games and tools that create entirely new ways for communities to play, connect and get things done at reddit. We power everything from interactive custom posts and daily games to mod tooling and data products, giving builds the primitives they need to create entirely new kinds of  experiences on Reddit. 

Within Developer Platform, our Growth team focuses on helping redditors discover the right apps and games at the right time through ranking, notifications, and cross‑surface entry points, directly moving the needle on engagement and DAU for Dev Platform experiences. You’ll work end‑to‑end with a highly collaborative, cross‑functional group of engineers, PMs, designers, and data scientists who value impact, personal growth, openness, and kindness, and who ship quickly while holding a high bar for reliability and performance across Reddit’s web, mobile, and backend stack.

How You'll Have Impact

We are looking for a Staff Machine Learning Engineer to build the ranking and personalization systems that connect redditors with their next favorite game or app on Reddit. You will work closely with Product, Backend, Data Science, and Core Ranking/ML Platform teams to design and ship best-in-class ranking, retrieval, and experimentation systems that power discovery and re-engagement for Dev Platform experiences across feeds, surfaces, and notifications.

You will own problems end-to-end—from framing objectives and defining signals, to training and deploying models, to designing experiments and reading results—not just tuning existing knobs on mature systems. You’ll help define the ranking strategy for Developer Platform, stand up new ML models and feedback loops where none exist today, and turn noisy behavioral data into clear wins for users, creators, and developers.

This is a high-impact, 0→1 role where your work will directly shape how interactive apps and games show up on one of the largest sites in the world. You’ll set technical direction for Dev Platform ranking, raise the bar on relevance and system reliability, and mentor other engineers as we scale a team of builders who value impact, personal growth, openness, and kindness.

Languages: Go, Python, C++ or any object oriented programming language

Libraries: Baseplate, GraphQL

Databases: Redis, Postgres, Memcached 

Tools: Kubernetes, AWS

Tools: Kubernetes, Docker, AWS, GCP

What You’ll Do

• Design and ship next-generation ranking and personalization models that power discovery of Dev Platform apps and games across Reddit surfaces.
• Partner with ML, DS, and product to define signals, APIs, and feedback loops for building, deploying, and iterating on ranking models.
• Explore and productionize new retrieval, ranking, and experimentation approaches that unlock new Dev Platform experiences.
• Champion model quality, reproducibility, and experimentation best practices — including offline evaluation, A/B testing, and monitoring for model health and degradation
• Mentor engineers and lead technical discussions, shaping the long-term ranking and personalization modeling strategy for Dev Platform.

Who You Might Be

• 8+ years of experience building and deploying ML models in production, particularly in ranking or personalization modeling, large-scale representation learning, or recommender systems.
• Proven track record working on cross-functional product teams (PM, Design, DS, Eng) where you owned end-user outcomes, not just models or infra, and shipped features that moved core product metrics.
• Strong domain knowledge in modern ranking and personalization techniques: user/item embeddings, multi-task learning, sequential modeling, or similar approaches applied at scale.
• Experience designing and implementing performant, stable, and efficient ML or ranking systems (recommendation, ads, search, feed, or similar high-throughput decision systems).
• Strong organizational skills with the ability to prioritize, sequence, and de-risk work, keeping complex projects on schedule with a high attention to detail.
• BS in Computer Science or a related technical field, or equivalent practical experience.
• Comfortable with software engineering best practices: testing, code reviews, technical design docs, and clear documentation for other teams that depend on your systems.
• Entrepreneurial mindset: you are self-directed, comfortable in ambiguity, and biased toward action in fast-paced environments. You like 0→1 building, iteration, and learning from experiments and failures.
• Excellent communication skills: you collaborate effectively in a remote, cross-functional team, and can explain complex ML and ranking concepts to both technical and non-technical stakeholders.

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave  

#LI-remote

Your Impact at LILA

As a Machine Learning Scientist focused on Scientific Reasoning, you will help pioneer the next generation of AI systems capable of reasoning like a scientist. You’ll design novel frameworks that push the boundaries of LLM-based reasoning methods — while also implementing scalable frameworks that integrate with Lila’s platforms. This role bridges deep theoretical thinking with practical ML engineering, enabling breakthroughs in how scientific hypotheses are generated, tested, deployed and optimized.

What You'll Be Building

• Design and formalize frameworks for scientific reasoning with LLMs, including structured prompting, reasoning chains, and test-time compute.
• Explore and implement methods for in-context learning, self-reflection, and adaptive reasoning in scientific discovery workflows.
• Build scalable model prototypes that can be deployed to solve frontier scientific problems.
• Collaborate with scientists and engineers to encode domain knowledge into reasoning systems that integrate symbolic and statistical approaches.

What You’ll Need to Succeed

• PhD (preferred) or equivalent research/industry experience in Computer Science, Machine Learning, AI, Engineering, Materials Science or related fields.
• Strong programming skills in Python with deep expertise in LLM frameworks (PyTorch, HuggingFace Transformers, LangChain, LlamaIndex, and related toolkits).
• Expertise in LLM reasoning methods: in-context learning, test-time compute, chain-of-thought, or tool-augmented reasoning.
• Ability to balance theoretical research with practical ML engineering to deliver scalable solutions.

Bonus Points For

• Research experience in causal reasoning, symbolic AI, or probabilistic programming.
• Contributions to open-source LLM reasoning frameworks.
• Familiarity with scientific discovery pipelines in chemistry, biology, or materials science.
• Experience with multimodal reasoning (e.g., combining text, image, and experimental data).
• Publications in top ML/AI conferences (NeurIPS, ICML, ICLR, ACL).

Your Impact at LILA

Lila is building a platform where AI and automation co-evolve to solve the hardest problems in medicine. Within Life Science AI (LSAI), ML engineers build and operate the systems that turn generative models and reasoning frameworks into production capabilities powering automated scientific discovery across Lila's life science domains.

We are seeking a Principal ML Engineer to design, build, and scale the ML infrastructure behind models spanning biological sequence design, molecular structure prediction, antibody engineering, and multimodal scientific reasoning. You will own critical systems end to end, from training pipelines and distributed compute to model deployment and integration into Lila's closed-loop discovery engine.

This is a high-impact IC role for someone who operates at the intersection of ML systems engineering and life science applications. You will shape the technical direction for how ML models are trained, evaluated, and deployed at scale, collaborate closely with AI scientists and experimental researchers to close the computational-experimental loop, and drive Lila's ML infrastructure toward the next generation of capabilities.

What You'll Be Building

• Design, build, and optimize large-scale training pipelines for generative models on biological and chemical data, including distributed training across GPU clusters
• Own production ML systems end to end: model deployment, serving infrastructure, monitoring, and reliability for models used in Lila's scientific workflows
• Architect ML infrastructure that supports rapid iteration across sequence design, structure prediction, and multimodal scientific reasoning workloads
• Drive the engineering side of Lila's "Lab-in-the-Loop" lifecycle: build pipeline models, integrate experimental feedback loops, and ensure model outputs are actionable for downstream scientific workflows
• Define and advance ML engineering standards, tooling, and best practices across the AI organization
• Collaborate with AI scientists to translate research prototypes into robust, scalable production systems, bridging the research-to-deployment gap

What You’ll Need to Succeed

• Master's degree or higher in Computer Science, Machine Learning, or a related quantitative field (or Bachelor's with equivalent professional experience)
• 10+ years of hands-on experience building and operating production ML systems at scale
• Deep expertise in distributed training infrastructure, including experience with large-scale GPU clusters (AWS, GCP, or on-prem)
• Strong software engineering fundamentals: system design, production-grade code, CI/CD, observability, and reliability practices
• Proficiency in ML frameworks (PyTorch, JAX, or TensorFlow) with experience optimizing training and inference performance
• Demonstrated ability to drive technical direction for ML infrastructure independently, from architecture through implementation
• Track record of cross-functional collaboration with research scientists, translating between ML methodology and engineering execution

Bonus Points For

• Experience building training or inference infrastructure for generative models applied to biological sequences, molecular structures, or scientific data
• Experience with agentic frameworks, active learning loops, or closed-loop experimental workflows
• Contributions to open-source ML tools, frameworks, or infrastructure projects
• Familiarity with at least one life science domain (molecular biology, genomics, protein engineering, or nucleic acid design)
• Experience with model evaluation frameworks for scientific applications where ground truth is sparse or delayed

Your Impact at LILA

Join us in shaping the future of science! We are seeking a software engineer with a background in life sciences to join our data science team, where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. This role spans web services and data engineering, with a strong emphasis on Python development for scientific applications. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!

What You'll Be Building

• Participate in the entire software development life cycle, focusing on designing, implementing, and maintaining software services.
• Develop reusable code and libraries to improve efficiency and scalability.
• Align development with strategic goals, ensuring software supports broader organizational needs.
• Manage git repositories, team Jira board and Notion Hub, promote best practices, assist lab scientists with use of new tools, and foster a collaborative development culture.
• Work directly with scientists to identify gaps and unmet needs, develop tailored software solutions for data management, LIMS functionality, and data automation
• Support infrastructure as code and design efficient deployment strategies.
• Write clear, concise documentation for both engineers and end users.

What You’ll Need to Succeed

• Minimum of 2 years of experience writing software in a commercial setting.
• High-level proficiency in Python.
• Strong understanding of git best practices.
• Acute listening skills and patience to deeply understand user challenges.
• Experience implementing scalable software solutions.
• Excellent problem-solving skills and team-first mentality.
• Strong communication skills to effectively collaborate with team members and stakeholders.
• Energetic self-starter and independent thinker, with strong attention to detail.
• Eager to work with highly skilled and dynamic teams in a fast-paced, entrepreneurial, and technical setting.

Bonus Points For

• Background in biological sciences
• Familiarity with data science and ML libraries (pandas, numpy, scipy).
• Knowledge of modern developer tools (pydantic, pyright, uv).
• Understanding of Kubernetes, ArgoCD, and GitHub Actions.
• Familiarity with AWS fundamentals (e.g., RDS, EC2, S3, EKS).

Your Impact at LILA

Lila is building a platform where AI and automation co-evolve to solve the hardest problems in medicine. Within Life Science AI (LSAI), software engineers build the systems that connect generative models, scientific data, and experimental workflows into reliable, production-grade pipelines powering Lila's protein design and engineering campaigns.

We're hiring a Staff ML Engineer, Life Sciences AI to lead software infrastructure development for our protein design and engineering pipelines. This is a senior IC role focused on the engineering systems that surround and support our ML stack — pipeline orchestration, data flow between computational and experimental systems, integration of new tools and methods, and the developer experience that lets LSAI move fast on commercial partnership deliverables.

What You'll Be Building

• Architect and build software infrastructure powering Lila's protein design and engineering pipelines: orchestration, data flow, APIs, and integration with experimental systems.
• Own the engineering side of LSAI's "Lab-in-the-Loop" lifecycle — connecting computational outputs to experimental inputs and feeding results back into design workflows.
• Onboard new tools and methods developed by AI scientists and ML engineers into production-ready systems used in commercial partnership campaigns.
• Partner cross-functionally with ML researchers, scientists, and platform engineers to translate research code into reliable, scalable systems.
• Set engineering standards for LSAI software — design reviews, CI/CD, testing, observability, reproducibility — and mentor senior engineers as the team grows.
• Diagnose and resolve reliability, performance, and scaling bottlenecks in production pipelines supporting partnership deliverables.

What You’ll Need to Succeed

• Master's degree or higher in Computer Science, Machine Learning, or a related quantitative field (or Bachelor's with equivalent professional experience).
• 8+ years of professional software engineering experience in Python (or comparable systems languages).
• Proven experience designing, building, and operating scalable production systems — APIs, data pipelines, orchestration, and cloud infrastructure.
• Strong software engineering fundamentals: system design, production-grade code, CI/CD, observability, and reliability practices.
• Experience building or operating scientific or ML-adjacent infrastructure — workflow orchestration, experiment tracking, and reproducible pipelines.
• Hands-on experience with containerization, orchestration platforms, and infrastructure-as-code on a major cloud provider.
• Track record of leading technical direction across multiple systems and partnering deeply with research scientists or ML engineers to translate scientific needs into production engineering.

Bonus Points For

• Experience building infrastructure for protein design and engineering, antibody engineering, or other molecular ML applications.
• Familiarity with biological data formats and bioinformatics tooling.
• Experience integrating ML training/inference systems with broader product or scientific platforms.
• Open-source contributions to scientific computing or data infrastructure projects.

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

Metropolis is seeking a Senior AI Engineer to join our Applied AI organization, a team purpose-built to rebuild how the company operates from an AI-first perspective. You will be the builder at the heart of this transformation, designing and shipping AI-powered tools and automation pipelines that replace manual, repetitive work across finance, operations, revenue, and beyond. This is a hands-on engineering role with enormous scope: you will own systems end-to-end, from the LLM prompt layer through to production deployment, working side-by-side with Process Analysts who understand the business deeply. If you want to see your work directly change how a company functions — not someday, but now — this is the role.

What you'll do

• Design, build, and ship AI-powered automation tools and internal applications that transform manual business processes into AI-first workflows
• Architect and maintain LLM-based systems, including prompt pipelines, agentic workflows, tool-calling integrations, and retrieval-augmented generation (RAG) setups
• Build and maintain data pipelines that connect source systems (Snowflake, internal APIs, SaaS tools) to AI workflows, ensuring data quality and reliability
• Partner with Process Analysts to understand how business functions work today, translate requirements into engineering specifications, and iterate based on real user feedback
• Own production reliability for the systems you build — monitoring, alerting, and iterating on AI outputs to maintain quality over time
• Evaluate and integrate emerging AI tooling (models, frameworks, APIs) to ensure Metropolis is always leveraging the best available capabilities
• Contribute to internal standards for AI development: prompt management, evaluation frameworks, model selection, and system architecture

What we're looking for

• 6+ years of software engineering experience, with 2+ years of hands-on experience designing, building, and deploying LLM-based or AI-powered applications in production
• Strong Python skills — you write clean, maintainable code and are comfortable building APIs, data pipelines, and backend services
• Practical experience with LLM APIs (OpenAI, Anthropic, or similar), prompt engineering, and agentic patterns (function calling, multi-step reasoning, tool use)
• Familiarity with data engineering fundamentals: SQL, data transformation, working with cloud data warehouses (Snowflake preferred)
• Experience with workflow orchestration tools (e.g., Airflow, Prefect, or similar) and cloud infrastructure (AWS preferred)
• A strong instinct for product quality — you care about whether the tools you build are actually useful, not just technically functional
• Ability to work autonomously in a fast-moving environment, manage competing priorities, and ship iteratively rather than waiting for perfection

While not required, these are a plus:

• Experience with vector databases, embeddings, or semantic search is a plus

Our Stack

• Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited)
• Datastores: MySQL, PostgreSQL, Snowflake
• Cloud: AWS
• Version control: Git & GitHub
• AI Tooling: Copilot on GitHub and Claude Code
• Observability: Datadog

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $170,000.00 USD to $200,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis' total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more. #LI-CM1 #LI-Onsite

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

Metropolis is seeking a Senior AI Engineer to join our Applied AI organization, a team purpose-built to rebuild how the company operates from an AI-first perspective. You will be the builder at the heart of this transformation, designing and shipping AI-powered tools and automation pipelines that replace manual, repetitive work across finance, operations, revenue, and beyond. This is a hands-on engineering role with enormous scope: you will own systems end-to-end, from the LLM prompt layer through to production deployment, working side-by-side with Process Analysts who understand the business deeply. If you want to see your work directly change how a company functions — not someday, but now — this is the role.

What you'll do

• Design, build, and ship AI-powered automation tools and internal applications that transform manual business processes into AI-first workflows
• Architect and maintain LLM-based systems, including prompt pipelines, agentic workflows, tool-calling integrations, and retrieval-augmented generation (RAG) setups
• Build and maintain data pipelines that connect source systems (Snowflake, internal APIs, SaaS tools) to AI workflows, ensuring data quality and reliability
• Partner with Process Analysts to understand how business functions work today, translate requirements into engineering specifications, and iterate based on real user feedback
• Own production reliability for the systems you build — monitoring, alerting, and iterating on AI outputs to maintain quality over time
• Evaluate and integrate emerging AI tooling (models, frameworks, APIs) to ensure Metropolis is always leveraging the best available capabilities
• Contribute to internal standards for AI development: prompt management, evaluation frameworks, model selection, and system architecture

What we're looking for

• 6+ years of software engineering experience, with 2+ years of hands-on experience designing, building, and deploying LLM-based or AI-powered applications in production
• Strong Python skills — you write clean, maintainable code and are comfortable building APIs, data pipelines, and backend services
• Practical experience with LLM APIs (OpenAI, Anthropic, or similar), prompt engineering, and agentic patterns (function calling, multi-step reasoning, tool use)
• Familiarity with data engineering fundamentals: SQL, data transformation, working with cloud data warehouses (Snowflake preferred)
• Experience with workflow orchestration tools (e.g., Airflow, Prefect, or similar) and cloud infrastructure (AWS preferred)
• A strong instinct for product quality — you care about whether the tools you build are actually useful, not just technically functional
• Ability to work autonomously in a fast-moving environment, manage competing priorities, and ship iteratively rather than waiting for perfection

While not required, these are a plus:

• Experience with vector databases, embeddings, or semantic search is a plus

Our Stack

• Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited)
• Datastores: MySQL, PostgreSQL, Snowflake
• Cloud: AWS
• Version control: Git & GitHub
• AI Tooling: Copilot on GitHub and Claude Code
• Observability: Datadog

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $170,000.00 USD to $200,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis' total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more. #LI-CM1 #LI-Onsite

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

Metropolis is seeking a Senior AI Engineer to join our Applied AI organization, a team purpose-built to rebuild how the company operates from an AI-first perspective. You will be the builder at the heart of this transformation, designing and shipping AI-powered tools and automation pipelines that replace manual, repetitive work across finance, operations, revenue, and beyond. This is a hands-on engineering role with enormous scope: you will own systems end-to-end, from the LLM prompt layer through to production deployment, working side-by-side with Process Analysts who understand the business deeply. If you want to see your work directly change how a company functions — not someday, but now — this is the role.

What you'll do

• Design, build, and ship AI-powered automation tools and internal applications that transform manual business processes into AI-first workflows
• Architect and maintain LLM-based systems, including prompt pipelines, agentic workflows, tool-calling integrations, and retrieval-augmented generation (RAG) setups
• Build and maintain data pipelines that connect source systems (Snowflake, internal APIs, SaaS tools) to AI workflows, ensuring data quality and reliability
• Partner with Process Analysts to understand how business functions work today, translate requirements into engineering specifications, and iterate based on real user feedback
• Own production reliability for the systems you build — monitoring, alerting, and iterating on AI outputs to maintain quality over time
• Evaluate and integrate emerging AI tooling (models, frameworks, APIs) to ensure Metropolis is always leveraging the best available capabilities
• Contribute to internal standards for AI development: prompt management, evaluation frameworks, model selection, and system architecture

What we're looking for

• 6+ years of software engineering experience, with 2+ years of hands-on experience designing, building, and deploying LLM-based or AI-powered applications in production
• Strong Python skills — you write clean, maintainable code and are comfortable building APIs, data pipelines, and backend services
• Practical experience with LLM APIs (OpenAI, Anthropic, or similar), prompt engineering, and agentic patterns (function calling, multi-step reasoning, tool use)
• Familiarity with data engineering fundamentals: SQL, data transformation, working with cloud data warehouses (Snowflake preferred)
• Experience with workflow orchestration tools (e.g., Airflow, Prefect, or similar) and cloud infrastructure (AWS preferred)
• A strong instinct for product quality — you care about whether the tools you build are actually useful, not just technically functional
• Ability to work autonomously in a fast-moving environment, manage competing priorities, and ship iteratively rather than waiting for perfection

While not required, these are a plus:

• Experience with vector databases, embeddings, or semantic search is a plus

Our Stack

• Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited)
• Datastores: MySQL, PostgreSQL, Snowflake
• Cloud: AWS
• Version control: Git & GitHub
• AI Tooling: Copilot on GitHub and Claude Code
• Observability: Datadog

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $170,000.00 USD to $200,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis' total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more. #LI-CM1 #LI-Onsite

Duetto is at an inflection point — moving from heuristic-based approaches to a fully ML-powered intelligence layer that drives forecasting, pricing, and decisioning across thousands of hotel properties worldwide. As VP of Data Science, you'll set the vision for that transition, build the team and practice to execute it, and deliver the agentic workflows that help hotel operators run a genuinely better business. This is a rare opportunity to define the intelligence strategy for the market-leading platform in hospitality technology, reporting directly to the Chief Product Officer with board-level visibility.

What Makes Us Different?

Duetto is the hospitality industry's leading revenue management platform, founded in 2012 by former Wynn Resorts executives who knew the industry needed better technology. We built the world's first Revenue & Profit Operating System — a suite of tools (GameChanger, ScoreBoard, BlockBuster, Advance and more) that goes beyond room pricing to give hotels, resorts and casinos a complete picture of their revenue and profitability. Trusted by clients ranging from independent boutique hotels to global chains, we've been named the #1 Revenue Management Software by HotelTechAwards four years running and the #1 Best Place to Work in Hotel Tech in 2025. Backed by GrowthCurve Capital since 2024, we're accelerating our investment in AI — and we're genuinely passionate about the industry we serve. We build products we're proud of, for customers we care about.

What You'll Be Doing

• You'll build and lead the intelligence engine behind Duetto's Revenue & Profit Operating System — setting a multi-year data science strategy that balances high-uncertainty research with pragmatic delivery, and establishing a rigorous science practice across Data Science Product Management, Analytics, ML Platform, and R&D.
• You'll lead the vision for Duetto's evolution toward agentic workflows — providing the technical blueprint for moving from fragmented, manual decisions to unified, intelligent automation that helps hotel operators make better commercial, financial, and operational decisions at scale.
• You'll own the model lifecycle end-to-end in a high-scale SaaS environment: deploying advanced forecasting, pricing optimisation, and causal models into production with measurable customer adoption, while managing the strategic trade-offs between model performance, system latency, and operational cost.
• You'll build the business case for data science investment, allocate departmental budget effectively, and influence peers in Engineering and Product to ensure data science capabilities are integrated into intuitive UX and scalable platform patterns.
• You'll preside over a rigorous research culture that prioritises reproducibility, global-scale evaluation, and decision-grade product analytics — and establish Responsible AI guardrails that ensure all models meet high standards for auditability, transparency, and data governance.
• You'll hire, develop, and continuously raise the bar for a high-performing organisation across multiple sub-functions, and communicate vision and execution progress to the wider organisation, the executive leadership team, and the board of directors.

What We're Looking For

You may be a good fit if you have:

• 12+ years of professional experience, including 5+ years of data science and product leadership operating production-grade data science organisations
• A track record of delivering business outcomes from innovative, data science-driven product development in high-scale SaaS environments
• Proven expertise managing the model lifecycle with specific focus on latency, cost, and data quality constraints
• Deep technical judgment in causal methods, forecasting, pricing optimisation, and experimentation in real-world commercial settings
• Experience building or partnering on ML Platforms and MLOps — monitoring, deployment modes, and CI/CD for ML
• Exceptional leadership skills with a demonstrated track record of hiring, developing, and high-grading technical talent across multiple sub-functions

Strong candidates may also have:

• An advanced degree in computer science, operations research, or a related analytical field
• Experience scaling ML across many tenants with heterogeneous data behaviour — hierarchical or per-entity modelling at scale
• Specialized knowledge of hospitality technology, specifically revenue management
• Experience operating in privacy or security-constrained environments, or regulated decision-intelligence systems

Why Duetto?

• A genuinely consequential mandate. You'll be defining the intelligence strategy for the market-leading platform in hospitality revenue management — the models you build inform pricing decisions for global hotel brands processing millions of rate decisions daily.
• The transition is already underway. Duetto is actively moving from heuristic to ML-powered decisioning — you're not starting from zero, you're accelerating a transformation that the organisation is already committed to.
• Agentic AI, for real. The vision here is unified, intelligent automation that replaces fragmented manual decisions — you'll be building toward genuinely agentic workflows in a domain where the data is rich and the commercial impact is clear.
• Board-level visibility. This role communicates directly to the executive leadership team and board of directors — the scope and influence are genuine, not ceremonial.
• A platform worth building on. Java/Spring Boot, AWS SageMaker, MLflow, and a globally distributed engineering organisation that takes technical excellence seriously — the foundation is solid and the ambition is high.

The Details

• Location: Remote (US)
• Department: Product
• Reports to: Chief Product Officer

Duetto is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by applicable law.

Sound like you?

You don't need a hospitality background to apply. If you're a senior data science leader with deep technical judgment, a track record of building high-performing teams, and the vision to define what ML-powered decisioning looks like at scale — we'd love to hear from you.

#LI-REMOTE

Pinterest is the world's leading visual search and discovery platform, serving over 500 million monthly active users globally on their journey from inspiration to action. As we scale and unify our foundational AI models across every recommendation surface, rigorously measuring the system-level impact of these advances is essential to our ability to ship with confidence and compound gains over time.

We are looking for a Senior Data Scientist to serve as the measurement backbone for Pinterest's foundational model initiatives within the Advanced Technology Group (ATG). In this role, you will design the evaluation frameworks, experimentation strategies, and system-level metrics that quantify how improvements to our largest and most complex models translate into real user and business outcomes. You will work in a highly collaborative and cross-functional environment, partnering with ML Engineers, Applied Scientists, Product Managers, and ML Platform engineers. 

You are expected to develop a deep understanding of Pinterest's recommendation ecosystem, from representation learning to retrieval, ranking, reinforcement learning, and beyond, and bring the analytical rigor necessary to decompose, attribute, and communicate the impact of foundational model changes across this interconnected system. The results of your work will directly influence model investment decisions, launch criteria, and the pace of innovation across ATG and Pinterest.

What You'll Do:

• Design and execute system-level measurement frameworks for foundational model improvements spanning offline evaluation benchmarks, online A/B experiments, and longitudinal impact tracking across surfaces.
• Define, and own the success metrics that quantify foundational model value.
• Build causal inference methodologies to isolate the incremental impact of individual model components within a complex, multi-model production system where changes co-occur and interact.
• Work cross-functionally to build relationships, proactively communicate key findings, and collaborate closely with ML Engineers, Applied Scientists, Homefeed and Surface teams to ensure measurement rigor is embedded in every model launch.
• Relentlessly focus on impact, whether through sharpening investment decisions with data, raising the bar for launch criteria, accelerating experimentation velocity, or surfacing hidden inefficiencies in the model ecosystem.

What We're Looking For:

• 5+ years of experience analyzing data in a fast-paced, data-driven environment with proven ability to apply scientific methods to solve real-world problems on web-scale data.
• Strong interest and hands-on experience in one or more of: ML system evaluation, recommender system measurement, A/B experimentation at scale, causal inference
• Deep familiarity with large-scale recommendation or ranking systems and their evaluation including an understanding of how representation learning, retrieval, ranking, and re-ranking stages interact and compound in production.
• Experience designing and executing A/B experiments for complex ML systems,  including multi-surface holdouts, metric decomposition, long-run effect estimation, and interference/spillover mitigation.
• Strong quantitative programming (Python) and data manipulation skills (SQL/Spark); experience with ML pipelines, feature stores, and large-scale experimentation platforms.
• Ability to work independently, drive ambiguous projects end-to-end, and operate with high ownership in a fast-moving research-to-production environment.
• Excellent written and verbal communication skills, with the ability to translate complex system-level findings into clear narratives for technical and non-technical partners including leadership-level investment recommendations.
• A team player eager to partner across teams to turn measurement insights into better models and faster launches.
• Bachelor’s/Master’s degree in a relevant field such as Computer Science, or equivalent experience.

Relocation Statement:

• We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
• This role will need to be in the office for in-person collaboration 1-2 times/quarter every 6-months] and therefore can be situated anywhere in the country.
• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

#LI-NM4

We are looking for a Machine Learning Engineer to join our team, with a specialized focus on Knowledge Graphs and LLMs. You will drive the development of AI products for our clients and participate in the development of a top-notch AI. At Factored we are building a company that we all hold as our own, every single one of us. We need your skills to help take this rocketship to new heights and help create new opportunities for us.  In return, you will be rewarded with an amazing team that supports you, rich culture, shared success and the flexibility to work– from the comfort of your home.

Functional Responsibilities:

• Design and implement knowledge graph architectures using property graph (Neo4j)or RDF-based models.
• Transform structured and semi-structured data into optimized graph structures and query them using Cypher or SPARQL.
• Integrate knowledge graphs with LLMs using Retrieval-Augmented Generation (RAG) architectures to deliver actionable insights.
• Build robust APIs (FastAPI) and application services to implement relationship strength analysis and network traversal logic.

Qualifications:

• 5+ years of hands-on experience developing and deploying machine learning models in production environments.
• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related fields
• Hands-on experience with knowledge graph technologies, specifically property graph (Neo4j) or RDF frameworks.
• Proficiency in querying systems using Cypher and/or SPARQL.
• Hands-on experience with AWS Neptune, GraphDB, or Memgraph for building production-grade Knowledge Graphs
• Strong skills in ontology design and modeling complex entity relationships.
• Expert-level Python development skills for building enterprise-grade applications.
• Experience building Retrieval-Augmented Generation (GraphRAG) and AI-driven recommendation systems.
• Strong knowledge of embeddings, vector databases, and semantic search techniques.
• Hands-on experience with major cloud platforms such as AWS, Azure, or GCP.
• Experience working with FastAPI/Flask 
• Ability to integrate relational databases and diverse external data sources into a unified graph.
• Excellent verbal and written communication skills in English.

The Team

Biohub's data organization is responsible for producing biologically informative, petabyte-scale, AI-ready datasets for frontier models of cell biology. Our work spans genomics, imaging, and proteomics, and we're building the data systems that will enable a new generation of biological AI. The team consists of data engineering, data science, and technical program management. We operate with a flat structure that emphasizes strong IC ownership. We're solving hard problems at the intersection of scientific strategy, large-scale data infrastructure, and foundation model training.

The Opportunity

In April 2026, Biohub launched the Virtual Biology Initiative—a $500 million, five-year commitment to galvanize a global effort to build predictive models of the human cell. This initiative will bring together leading institutions to generate the multi-modal biological data, at unprecedented scale, that will power the next generation of AI models for biology while producing datasets of unprecedented size.

Our data science team defines the algorithms and processing approaches that turn raw biological measurements into rich representations models can actually learn from. That includes designing data formats and representations optimized for AI use cases, building cost-aware processing pipelines that balance expressiveness with efficiency, developing scalable QC and validation frameworks across modalities, creating agent-augmented curation tools for metadata extraction and ontology mapping, and building the cross-modal entity resolution and semantic infrastructure that ties it all together. 

Both the scale and domain are active research areas. How do you tokenize a cell image? How do you represent a perturbation experiment? How do you combine transcriptomics with imaging in a way that preserves biological meaning? These questions don't have established answers. We need scientific leaders who can work at this frontier: people who understand biological measurement deeply, think creatively about data representations, sampling, and tokenization strategies, and can translate that thinking into data representations that enable novel training architectures.

You'll work directly with scientists, computational biologists, data engineers, and AI researchers to define model input and biological evaluations. You will operate with broad scope and high autonomy, influencing roadmap decisions across teams while mentoring senior individual contributors. Success in this role means creating and implementing data systems that are not only large, but adaptive, interpretable, and scientifically grounded—accelerating progress toward robust biological frontier models and ultimately advancing human health.

What You'll Do

• Set technical vision and strategy for the design of data representations and tokenization strategies across biological data types—including imaging, sequencing, and multimodal data—that enable novel model architectures
• Develop, deploy and validate approaches for combining heterogeneous data modalities into unified training frameworks, designing for robustness to noise, bias, and batch effects
• Evaluate model performance, identifying which biological signals are captured or lost and iterating to improve
• Partner deeply with ML engineers and AI researchers to co-design datasets and optimize model training, evaluation, and generalization
• Lead cross-functional initiatives spanning data engineering, infrastructure, science, and product, aligning technical execution with long-term scientific goals
• Identify and drive new data acquisition and generation opportunities, from consortium partnerships to internal experimental pipelines
• Serve as a technical mentor and leader, raising the bar for data science and ML rigor across the organization

What You'll Bring

• 12+ years of experience (or PhD + 7 years) working with large-scale biological datasets, including ownership of end-to-end data products
• Deep expertise in at least one of: (a) imaging data—microscopy, cell phenotyping, spatial biology, and the data characteristics of image-based biological measurement; or (b) genomics data—bulk and single-cell sequencing, functional genomics, epigenomics, transcriptomics, spatial biology, and/or multi-omics
• Understanding of how to transform raw biological data into AI-ready datasets, including familiarity with scientific best practices, noise characteristics, batch effects, and quality assessment specific to your domain
• Experience with tokenization strategies for non-text data (images, sequences, graphs, time series) or with creating data representations and feature engineering for machine learning in scientific or biological contexts
• Strong expertise in data science and statistical modeling; familiarity with modern ML architectures (transformers, diffusion models, or similar) and how data representation choices affect learning
• Strong computational skills; demonstrated ability to design robust, extensible data architectures
• Excellent communication and leadership skills, with the ability to translate between biology, ML, and engineering audiences and align teams to deliver complex projects
• Creative, first-principles thinking about how to structure data for learning

Compensation

The Redwood City, CA  &  New York City, NY  base pay range for a new hire in this role is $241,000.00 - $331,100.00. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process. 

Better Together

As we grow, we’re excited to strengthen in-person connections and cultivate a collaborative, team-oriented environment. This role is a hybrid position requiring you to be onsite for at least 60% of the working month, approximately 3 days a week, with specific in-office days determined by the team’s manager. The exact schedule will be at the hiring manager's discretion and communicated during the interview process.

Benefits for the Whole You 

We’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible. 

• Provides a generous employer match on employee 401(k) contributions to support planning for the future.
• Paid time off to volunteer at an organization of your choice. 
• Funding for select family-forming benefits. 
• Relocation support for employees who need assistance moving

If you’re interested in a role but your previous experience doesn’t perfectly align with each qualification in the job description, we still encourage you to apply as you may be the perfect fit for this or another role.

#LI-Hybrid 

The Role:

We are seeking a Looker Data Engineer for a project-based assignment to support a key client initiative. This role will focus on building and optimizing data models, developing scalable reporting solutions, and enabling data-driven decision-making through Looker and modern data stack technologies. The ideal candidate will have strong hands-on experience with Looker development, data modeling, and programmatic reporting, along with a solid foundation in SQL and cloud data platforms.

Key Responsibilities:

• Develop and maintain Looker data models, including LookML, models, and explores
• Build and optimize scalable, consumable data models to support business intelligence and strategic decision-making
• Utilize Looker API 4.0 to enable programmatic access to dashboards, looks, and explores
• Automate report generation and delivery using Looker API endpoints
• Write and optimize complex SQL queries to improve performance and efficiency
• Work with Snowflake, dbt, and Python to support data transformation and pipeline development
• Collaborate with stakeholders to translate data requirements into scalable BI solutions
• Ensure data accuracy, consistency, and performance across reporting layers

Required Skills:

• 3+ years Looker development experience (LookML, models, explores)
• Experience working with Looker API 4.0 for programmatic access
• Experience automating reporting using Looker API endpoints
• Ability to transform complex data into scalable, consumable data models
• Hands-on experience with Snowflake and Python
• SQL experience with query optimization

Nice to Have:

• Experience with dbt
• Looker administration experience
• Experience working with BigQuery
• Experience with modern data pipelines and ELT workflows
• Familiarity with data governance, data quality, or BI best practices
• Experience working in a client-facing or consulting environment

Employment Type:

Overview

The Director, AI Product is responsible for translating enterprise AI strategy into high-impact, production-ready AI products and capabilities. Reporting to the Senior Director of AI, this role owns the AI product portfolio—from discovery through scaled execution—ensuring AI initiatives are designed, delivered, and adopted as true business products with clear outcomes. 

This leader serves as the connective tissue between business sponsors, AI engineering teams, data/platform leaders, and the AI Center of Excellence (CoE). The role requires strong product leadership, systems thinking, and the ability to operate AI initiatives with discipline, speed, and measurable value. 

What you’ll do

Become part of an iconic brand that is set to revolutionize the electric pick-up truck & rugged SUV marketplace by achieving the following:

AI Product Strategy & Portfolio Ownership  

• Own and manage a portfolio of AI products and use cases aligned to enterprise priorities and strategic domains. 
• Translate business problems into well-defined AI product roadmaps with clear success metrics and value hypotheses. 
• Ensure AI initiatives progress through defined lifecycle stages (Discover → Prototype → Execute → Available). 

Product Management & Delivery 

• Act as senior product owner for priority AI initiatives, partnering with business sponsors to define outcomes, KPIs, and adoption plans. 
• Lead cross-functional delivery teams (AI/ML, data, engineering, analytics, UX) to deliver production-ready AI capabilities. 
• Balance experimentation with execution—knowing when to pivot, scale, or stop initiatives based on evidence. 

Business Partnership & Value Realization 

• Partner closely with business leaders to ensure AI products solve real problems and drive measurable operational or financial impact. 
• Support business owners through handoff and scaling, enabling sustained ownership post-deployment. 
• Contribute to AI value storytelling and executive reporting in partnership with the Senior Director of AI. 

AI Operating Model & Governance 

• Operate within the AI Center of Excellence hub-and-spoke model, ensuring AI products align to enterprise standards and governance. 
• Collaborate with Responsible AI, security, privacy, and architecture stakeholders to embed controls early and consistently. 
• Reinforce product discipline, documentation, and lifecycle management across the AI portfolio. 

Team Leadership & Capability Building 

• Lead and mentor AI Product Owners, Business Analysts, and cross-functional product contributors. 
• Establish repeatable product practices, templates, and playbooks for AI delivery at scale. 
• Contribute to the broader AI product and innovation culture across the enterprise. 

Location & Travel Expectations:

• This role will be based out of the Scout Motors location in Charlotte, North Carolina. 
• This role requires 4 days per week in the office, with regular in-person meetings and events. 
• Applicants should expect that the role will require the ability to convene with Scout colleagues in person and travel to participate in events on behalf of the company from time to time.

What you’ll bring 

We expect all Scout employees to have integrity, curiosity, resourcefulness, and strive to exhibit a positive attitude, as well as a growth mindset. You’ll be comfortable with change and flexible in a fast-paced, high-growth environment. You’ll take a collaborative approach to achieve ambitious goals. Here's what else you'll bring:

Required 

• 12+ years of experience in product management, digital platforms, data, or AI-adjacent roles. 
• Proven experience owning and delivering complex, cross-functional products from concept to scale. 
• Strong ability to partner with business leaders and translate strategy into execution. 
• Working knowledge of AI/ML concepts, data platforms, and product lifecycle management.   

Preferred 

• Experience managing AI or advanced analytics products in an enterprise environment. 
• Familiarity with portfolio-based funding, governance, and value measurement. 
• Experience operating within a federated or hub-and-spoke delivery mode 

What you'll gain

The benefits of joining Scout include the chance to build products and a company from the ground up.  This is a chance to create something new and lasting – with an iconic brand at its foundation.  In addition, Scout provides competitive compensation and benefits to support your physical, mental, and financial wellbeing. Program specifics are detailed in company policies and employee benefit guides, select highlights:

• Competitive insurance including:
  • Medical, dental, vision and income protection plans
• 401(k) program with:
  • An employer match and immediate vesting
• Generous Paid Time Off including:
  • 20 days planned PTO, as accrued
  • 40 hours of unplanned PTO and 14 company or floating holidays, annually
  • Up to 16 weeks of paid parental leave for biological and adoptive parents of all genders
  • Paid leave for circumstances related to bereavement, jury duty, voting time, or military leave
• Corporate Vehicle Program with:
  • Eligibility for 1 assigned vehicle
  • A mobility stipend

Pay Transparency

This is a full-time, exempt position eligible to receive a base salary and to participate in an annual performance bonus program. Final salary offered will be determined based on factors including but not limited to the candidate's skills and experience. The annual performance bonus program is preset and not candidate dependent.

Initial base salary range = $180,000.00 - $220,000.00

Internal leveling code: M6

The Role:

We are seeking a Looker Data Engineer for a project-based assignment to support a key client initiative. This role will focus on building and optimizing data models, developing scalable reporting solutions, and enabling data-driven decision-making through Looker and modern data stack technologies. The ideal candidate will have strong hands-on experience with Looker development, data modeling, and programmatic reporting, along with a solid foundation in SQL and cloud data platforms.

Key Responsibilities:

• Develop and maintain Looker data models, including LookML, models, and explores
• Build and optimize scalable, consumable data models to support business intelligence and strategic decision-making
• Utilize Looker API 4.0 to enable programmatic access to dashboards, looks, and explores
• Automate report generation and delivery using Looker API endpoints
• Write and optimize complex SQL queries to improve performance and efficiency
• Work with Snowflake, dbt, and Python to support data transformation and pipeline development
• Collaborate with stakeholders to translate data requirements into scalable BI solutions
• Ensure data accuracy, consistency, and performance across reporting layers

Required Skills:

• 3+ years Looker development experience (LookML, models, explores)
• Experience working with Looker API 4.0 for programmatic access
• Experience automating reporting using Looker API endpoints
• Ability to transform complex data into scalable, consumable data models
• Hands-on experience with Snowflake and Python
• 2+ years SQL experience with query optimization

Nice to Have:

• Experience with dbt
• Looker administration experience
• Experience working with BigQuery
• Experience with modern data pipelines and ELT workflows
• Familiarity with data governance, data quality, or BI best practices
• Experience working in a client-facing or consulting environment

Employment Type:

The Search Recommendations & Relevance team at Reddit is building the next generation of search - one that goes beyond “10 blue links” to deliver real answers, perspectives and conversation from the world's largest corpus of human conversation. We power both Reddit Search and our AI-native Search experience, redefining how users discover and interact with information.

Redditors produce the most amazing content about every niche topic in the world – this underleveraged data coupled with modern advances in AI systems is presenting a unique opportunity to quickly build a new kind of search engine. As a Senior Staff, you will design and build a large-scale system that powers end-to-end search relevance at scale. You’ll  work across multiple areas of the stack, including query understanding, retrieval, ranking, features, measurement, LLM-based answers, RAG etc, partnering deeply with product, org leads, and other XFN to deliver reliable, high quality systems that can help Reddit Search scale to billions of users.

What You’ll Do

• Contribute to advancing Reddit's Search and Recommendations products by designing AI-driven Search experience prioritizing seamless and delightful user experience. 
• Deeply understand the Reddit search product and drive the vision for the search relevance team.
• Enhance core search retrieval and ranking, design and implement new search engine features,  build and scale search indexes, develop and test new pipeline components.  You will also deploy  ML models, integrate LLMs, and ensure robust monitoring and smooth product integration throughout the process.
• Collaborate across disciplines and with ML, Product, Infrastructure, and DS teams at Reddit to find technical solutions to complex challenges.
• Mentor and guide senior and staff engineers in the team.
• Influence org-wide technical direction and partner closely with senior leadership to shape the long-term roadmap

Who You Are

• 10+ years of industry experience with deep expertise in large-scale search and recommendation systems. 
• Proven ability to identify key opportunities, define roadmaps and drive scalable improvement in  search relevance.
• Strong experience in building and deploying large-scale ML models using frameworks such as PyTorch or Tensorflow.
• Experience working with LLM in production, including evaluation, tuning and deployment.
• In-depth knowledge and experience working with lexical and semantic retrieval systems.
• Proficiency in object-oriented programming (Python, Golang).
• Nice to have: experience building production Agentic AI frameworks.

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

#LI-remote, #LI-JS5

We’re looking for a Senior Staff Machine Learning Engineer to lead Reddit’s next-generation user understanding initiative: building a unified, high-fidelity representation of each user that powers personalization across the platform.

This role requires deep expertise in mainstream ML user modeling approaches (e.g., large-scale embeddings, user interest modeling, affinities, behavioral signals) and the ability to reimagine these systems in the GenAI era—leveraging LLMs and foundation models to unlock step-change improvements in fidelity, adaptability, and expressiveness.

You will set the technical direction for this space, leading the design and implementation of Reddit’s core user representation layer—spanning embeddings, interest modeling, and key user attributes. You’ll ensure this foundation is scalable, reliable, and widely adopted across Feeds, Search, Notifications, and Ads, partnering closely with product, infrastructure, and downstream ML teams to drive measurable impact.

This is a high-impact role. The systems you build will shape how hundreds of millions of people experience Reddit every day—what they see, what they discover, and the communities they connect with. Your work will directly advance personalization and relevance at global scale, strengthening Reddit as a platform for meaningful connection and belonging.

What you'll do:

• Design User Understanding Strategy: Define a unified user understanding framework and strategy: how users are represented (embeddings, tags, attributes, LLM-based user profile), how they are computed, stored, and exposed. Provide thought leadership in user understanding and user modeling by setting a long-term technical vision and advancing the state-of-the-art in the field.
• Build Foundational User Models: Lead design and implementation of advanced user models, e.g. large-scale user representation learning (sequence-based, multi-interest, multi-task) that share representations across surfaces to improve personalization experience across key Reddit products e.g. Feeds, Notification, Search and Ads, balancing latency, cost, and performance.
• Reimagine user understanding with LLM/Gen-AI: Evolve user modeling beyond traditional representations by leveraging LLMs to build richer user understanding (e.g., dynamic user profiles, intent inference, semantic reasoning over user behavior). Explore how LLMs can augment or unify embeddings, attributes, and taxonomies to enable more adaptive, interpretable, and context-aware personalization.
• Ship Large Scale User Understanding as a System: Partner with platform teams to design and build core components for large-scale learning and serving: storage/retrieval for embeddings, feature pipelines, and APIs. Collaborate with ML/Ranking infra to ensure low-latency serving, high availability, and integration with MLOps systems.
• Drive Cross-Team Integration & Impact: Partner with Feeds, Notification, Search and Ads teams to drive experimentation and adoption of new user understanding models with product teams across Reddit, ensuring measurable end-to-end impact on key metrics.
• Set Technical Bar & Mentor: Mentor senior to staff engineers, lead design reviews, steward technical decisions across the user understanding domain, and champion and drive engineering processes and best practices

Who you might be:

• You have at least 10 years experience building and scaling production-grade ML systems, particularly in user modeling, large-scale representation learning, or recommender systems.
• You have a track record of driving ambiguous, high-impact initiatives from concept to production, shaping both technical direction and execution.
• You are product- and impact-oriented: you care deeply about how your work moves real metrics (e.g., engagement, retention, revenue), not just model quality.
• You bring strong fundamentals in mainstream user understanding ML approaches (e.g., representation learning, behavioral modeling, user clustering), and understand their trade-offs in real-world systems.
• You are excited about the GenAI shift and have experience (or strong intuition) applying LLMs or foundation models to evolve existing systems,  going beyond incremental improvements.
• You think in systems, not just models: you consider data, training, evaluation, serving, and adoption as a cohesive whole, and design with end-to-end impact in mind.
• You influence beyond your immediate team: partnering effectively with product, infra, and other ML teams, and driving alignment across multiple stakeholders.
• You raise the technical bar: mentoring senior engineers, leading design reviews, and establishing best practices for building reliable, scalable ML systems.
• You are comfortable navigating trade-offs across quality, latency, cost, and safety, especially in large-scale, user-facing systems.

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

#LI-remote, #LI-JS5

We’re looking for a Senior Staff Machine Learning Engineer to join our Feed Relevance team, which is responsible for the end-to-end systems that power personalization and ranking for the main Reddit feeds. This is a critical role that blends hands-on development with technical leadership, focusing on building scalable, extensible, and highly performant personalization systems. You will be instrumental in defining the technical direction for the team, collaborating closely with Product and Engineering leadership to set the strategy, and working with other individual contributors to execute and scale our systems to serve tens of millions of users. This work will directly enable our Machine Learning Engineers (MLEs) and engineers to quickly iterate and continuously improve the user experience. You will also partner with Infra and Platform teams to inform the direction of our core infrastructure, building for the future of ML at Reddit.

Responsibilities:

• Deliver on technical initiatives that have significant company-wide impact
• Set technical direction for the broader Relevance and Feeds teams at Reddit, able to identify opportunities and influence strategy across multiple orgs
• Work with management on goal setting, planning, and de-risking critical projects
• Mentor and grow Senior and Staff engineers
• Create a strong healthy engineering culture

Qualifications:

• 10+ years of industry experience building systems for relevance driven products
• Subject matter expert in relevance, recommendation, and ML systems; able to solve complex problems in these domains that few others can 
• Deep understanding of how to build sustainable software systems at a large scale engineering organization
• Experience in influencing organizations on technical direction/best practices
• Experience working with cross-functional teams such as design, product, business & data teams to deliver great experiences.
• Strong focus on user experience, usability, scalability, reliability and quality. You are an undying advocate for the user, and you have a deep intuition for how people & machines interact with software at scale.
• High empathy, excellent communication skills, and the ability to find compromise working across the entire engineering org

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

#LI-remote, #LI-JS5

Reddit has a flexible first workforce!

The Ads Measurement Org is dedicated to enhancing the efficiency and user-friendliness of our advertising platform. The Measurement Modeling team owns all the Machine Learning solutions for Ads Measurement, including Identity Matching, Identity Graph, Utility Enhancement for Ads Privacy, Modeled Conversion, and new Measurement Modeling Initiative. As critical and complex part, in Identity Modeling, we are building new advanced machine learning solutions, the space resides in intersection of ads stack that interacts with various upstream and downstream systems, it serves critical business needs for monetization and consumer as well, including Measurement & Reporting, Experimentation, Personalization, Delivery, and Safety etc, requires major XFN as well as cross team/org collaborations.

We are looking for an IC5 Staff ML Engineer of Ads Identity Modeling, to define long term direction and drive architecture evolution, be responsible for engineering quality and enforce best practice, lead new exploration and cross-org collaboration in new modeling initiatives, and champion ML/AI innovation to ensure the solutions utilize SOTA ML technology. Our diverse group of engineers, product managers, data scientists, and ads specialists is excited to welcome you on board!

Minimum Qualifications:

• 7+ years of professional software engineering experience, with at least 3+ years focused on ML-driven systems at scale
• Demonstrated experience architecting and building ads measurement modeling solutions leveraging advanced machine learning techniques
• Strong knowledge of various identifiers (cookies, hashed emails, phone numbers, IP addresses, user agents) and their use in identity resolution
• Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries for feature engineering, model training, and inference
• Solid understanding of large-scale data processing, distributed computing, and data infrastructure (e.g., Spark, Kafka, Beam, Flink)
• Proven technical leadership in cross-functional settings, driving architectural decisions and influencing stakeholders (product, data science, privacy, legal)
• Excellent communication, mentoring, and collaboration skills to align teams on a long-term vision for identity resolution

Responsibilities:

• Lead the technical strategy and architecture for our company’s ads identity modeling solutions and other related ads measurement models
• Design and train advanced ML models while ensuring accuracy, scalability, and compliance with privacy requirements, managing trade-offs between complexity, latency, and prediction quality
• Oversee end-to-end ML workflows—from data ingestion and feature engineering to model training, evaluation, and deployment—optimizing for performance and cost
• Partner with cross-functional teams (e.g., product management, data science, platform engineering, privacy, legal) to define the roadmap and set long-term goals
• Establish engineering best practices, code quality standards, and data governance guidelines to ensure maintainability and trustworthiness of the identity graph
• Mentor and coach junior engineers, fostering a culture of innovation, technical excellence, and knowledge sharing across the organization

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

#LI-AK1

Ads Content Understanding (ACU) is Reddit’s core commercial content understanding team for Ads. The team owns and produces signals that describe what Reddit content is about, how brand safe and suitable it is, and what users are trying to accomplish in commercial conversations. ACU is responsible for:

• The Knowledge Graph (entities, brands, products, and relationships across Reddit and external sources).
• Content taxonomies such as IAB, Shopify Standard Product Taxonomy, IAS, and other commercial taxonomies used for targeting, safety, and marketplace dynamics.
• Opinion mining for ads use cases: sentiment, stance, commercial intent, and other qualitative attributes of conversations.
• Shopping / product understanding: detecting product entities, product categories, and product attributes in organic conversations and aligning them with shopping catalogs.
• Signals and tags registry: a unified, governed catalog of ACU signals that powers retrieval, ranking, safety, and insights across Ads Foundations and partner teams. 

We are looking for a Staff Machine Learning Engineer who will lead the Commercial Content Understanding roadmap for the Monetization org and act as the technical owner for ACU’s signals and ML systems. Roughly 50% of their time should be spent in technical leadership and mentorship (driving designs, standards, cross-team alignment), and 50% in direct hands-on work (modeling, pipelines, and debugging complex production systems). 

Responsibilities:

• Provide technical leadership and mentorship to MLEs and SWEs doing ML work in ACU, acting as de facto tech lead for content understanding and signals: driving design reviews, setting technical standards, and uplifting the team’s modeling and systems craft.
• Develop evaluation systems and quality monitoring systems for content understanding signals, using SOTA LM-judge practices. 
• Drive operational excellence for ACU’s ML systems by defining SLOs, alerting, and dashboards for key signals (coverage, latency, precision/recall, cost)
• Build and evolve content understanding capabilities for commercial conversations (e.g., reviews vs. recommendations vs. comparisons vs. Q&A; sentiment and stance; product entities and categories) and operationalize them as robust signals that power contextual and shopping ads, auto-targeting, new formats, and insights products.
• Lead design and implementation of signals pipelines and produce an ACU signals registry. Partner with platform teams and other content understanding teams to ensure efficient, reliable serving at Reddit scale.
• Drive LLM and modern ML best practices within ACU: define when to prompt, finetune, or distill; design evaluation and safety harnesses; and lead at least one major distillation effort to replace external APIs with in-house models.
• Operate across the full ML lifecycle (problem framing, data, modeling, evaluation, deployment, monitoring, and oncall), designing scalable, resilient MLOps pipelines and championing responsible AI (bias, safety, explainability) for ACU’s models and signals in production.

Required Qualifications:

• 7+ years of relevant MLE experience delivering production ML systems (models + pipelines + serving) at scale, ideally in large-scale content understanding domains, or Ads. 
• Demonstrated Staff-level technical leadership: has driven architecture decisions, standards, and design reviews across multiple teams, and has aligned PMs, DSs, and engineers on shared ML systems or platforms without direct people-management authority.
• Excellent communication skills, with the ability to explain complex technical trade-offs to PMs, DSs, and other engineering teams, especially in ambiguous, cross-team problem spaces like Seekers/Searchers monetization. 
• Strong track record building and shipping NLP / Language models / content understanding models to production (e.g., classifiers, encoders, sequence or session models), with clear business outcomes (e.g., CTR/ROAS uplift, safety improvements). Experience with commercial or intent modeling is a strong plus.
• Practical experience using LLMs in production for labeling, evaluation, or distillation (e.g., LM-as-judge, prompt-based classifiers, LLM-generated labels distilled into smaller models), including managing quality, cost, and latency trade-offs.
• Deep experience with PyTorch, TensorFlow, or similar, and production-quality code in Python (and ideally one statically typed language like Go/Java/C++). Comfortable owning training, evaluation, and deployment code end-to-end.
• Experience designing ML systems and pipelines: offline training, feature pipelines (batch/streaming), online serving, monitoring, and experimentation for high-traffic surfaces.

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

#LI-Remote

Location: US remote-friendly or any office location - SF, LA, CHI, NY

Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet. 

Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes.

As a Staff Data Scientist on the team, you will play an influential role in guiding product strategy through proactively identifying opportunities, conducting exploratory analyses and sharing insights, and driving learning through experimentation.

Responsibilities:

• Help build the long term product strategy by identifying opportunities to attract new users, increase engagement, and drive retention 
• Influence strategic roadmaps through data-driven insights into user behaviors and needs
• Design metrics that help evaluate the health of the business and the success of our products, including any ETL development needed for consistent and robust analysis
• Drive experimentation from design through execution and analysis to maximize learnings and guide future investment decisions
• Build self-serve tools for product and engineering partners that answer common questions and/or increase data literacy in the organization
• Work cross functionally with product, engineering, and design teams to ensure insights make it to the product
• Scale your work to other parts of the data organization through mentoring more junior data scientists, improving processes, and providing perspective on the most important problems

Required Qualifications:

• Advanced degree (Master's or Ph.D.) in Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 10+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 6+ years of industry experience in applied science or data science roles
• Expert knowledge of SQL and relational databases
• Familiarity with statistical analysis and the preferred programming languages of the team (R / Python)
• Demonstrated ability to influence and guide product strategy with data
• Demonstrated ability to take ambiguous problems and solve them in a structured, hypothesis-driven, data-supported way
• Familiarity with causal inference techniques and causal models
• Excellent communication and experience working with senior leaders / stakeholders 
• Entrepreneurial, self-directed, and enthusiastic about solving problems
• Demonstrated ability to mentor other data scientists and share best practices to elevate the data science practice at Reddit
• Conform in innovative and fast-paced environments, and have a bias toward action.
• Can discuss complex topics with technical and non-technical audiences

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave  

#LI-Remote

Location: At Reddit we continue to grow our teams with the best talent. We're completely remote friendly.

Team Description:

The Marketing Science team at Reddit leverages data to maximize the impact of Reddit’s own marketing investments. We serve as the engine behind our growth, using advanced experimentation, causal inference, and econometrics to understand what drives users to Reddit and what brings advertisers to our platform. We work at the intersection of brand building and performance marketing, ensuring every dollar spent is an investment in the long-term health of our ecosystem.

Role Description:

Reddit is looking for a highly experienced Staff Data Scientist to lead the strategy and technical execution of our Marketing Intelligence efforts. In this role, you will be the primary architect of how we measure and optimize Reddit’s marketing spend. You will focus on two critical flywheels: B2B Marketing (acquiring and retaining advertisers) and B2C Growth (acquiring and engaging new Redditors).

This is a high-autonomy, high-impact role where you will set the long-term strategic goals for Reddit’s marketing measurement, influencing senior leadership and defining how we value our brand and performance efforts.

Responsibilities:

• Set Long-Term Marketing Strategy: Define the 2–3 year technical roadmap for marketing measurement. Establish the "North Star" metrics and frameworks that determine how Reddit allocates hundreds of millions in marketing budget.
• Optimize Marketing ROI: Build and refine Media Mix Models (MMM) and Multi-Touch Attribution (MTA) systems to mathematically quantify the incremental impact of marketing spend.
• Bridge B2B & B2C Growth: Design unified frameworks to optimize marketing aimed at both new advertisers (driving revenue) and new users (driving engagement), identifying synergies where brand awareness for one fuels growth for the other.
• Advance Causal Inference & Experimentation: Lead the design of complex "always-on" incrementality testing and geo-holdout experiments. Develop methodologies to measure the long-term "halo effect" of brand marketing on organic growth.
• Lead Through Influence: Collaborate deeply with Marketing, Growth, and Finance to translate complex data insights into actionable budget shifts. 
• Be the Technical Guide for the Team: Mentor junior scientists and set the technical bar for code quality and statistical rigor across the Marketing organization.

Minimum Qualifications:

• Education: Advanced degree (Master’s or Ph.D.) in Statistics, Economics, Mathematics, or a related quantitative field.
• Experience:
• For M.S. holders: 10+ years of industry experience in marketing science, growth data science, or econometrics.
• For Ph.D. holders: 6+ years of industry experience.
• Domain Expertise: Deep understanding of the marketing ecosystem, including hands-on experience with Marketing Mix Modeling (MMM), Incrementality Testing, and Customer Lifetime Value (LTV) prediction.
• Technical Skills: Advanced proficiency in Python or R and SQL. Experience building production-grade data pipelines and using machine learning for predictive modeling (e.g., churn prediction, lead scoring).
• Strategic Communication: Proven track record of influencing C-suite stakeholders and "translating" complex statistical concepts into business strategy.
• Adaptability: Experience working in fast-paced environments where you must navigate ambiguity and build frameworks from the ground up.

Preferred Qualifications:

• Experience with Bayesian structural time series or causal inference libraries.
• Previous experience in a high-growth marketplace or social media platform.
• A passion for the Reddit community and an understanding of our unique "Ads-as-Content" philosophy.

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

We are looking for a highly motivated and experienced Senior Data Scientist to join our growing Ads Data Science team. As a Senior Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve the adoption and performance of our advertising platform through data-driven insights. You will work closely with product managers, engineers, and other data scientists to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Design, develop, and apply DS solutions to inform improvements in advertiser experience and Reddit's ad platform
• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Collaborate with product managers and engineers to define product requirements and translate them into data science solutions
• Develop ML models & DS methods to improve anomaly detection, prediction, & pattern recognition 
• Communicate findings and recommendations to stakeholders across the organization
• Stay up-to-date on the latest advancements in machine learning and data science
• Mentor and guide junior data scientists on the team

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 5+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 4+ years of industry experience in applied science or data science roles
• Platform experience and a deep understanding of the ads ecosystem
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills
• Passion for Reddit and the online advertising industry

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Comprehensive Medical Benefits & Health Care Spending Account
• Registered Retirement Savings Plan with matching contributions
• Income Replacement Programs
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

#LI-Remote

Location: US remote-friendly

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

We are looking for a highly motivated and experienced Senior Data Scientist to join our growing Ads Data Science team. As a Senior Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve the adoption and performance of our advertising platform through data-driven insights. You will work closely with product managers, engineers, and other data scientists to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Design, develop, and apply DS solutions to inform improvements in advertiser experience and Reddit's ad platform
• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Collaborate with product managers and engineers to define product requirements and translate them into data science solutions
• Develop ML models & DS methods to improve anomaly detection, prediction, & pattern recognition 
• Communicate findings and recommendations to stakeholders across the organization
• Stay up-to-date on the latest advancements in machine learning and data science
• Mentor and guide junior data scientists on the team

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 5+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 4+ years of industry experience in applied science or data science roles
• Platform experience and a deep understanding of the ads ecosystem
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills
• Passion for Reddit and the online advertising industry

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave  

#LI-Remote

Benefits:

• Comprehensive Healthcare Benefits
• 401k Matching
• Workspace benefits for your home office
• Personal & Professional development funds
• Family Planning Support
• Flexible Vacation (please use them!) & Reddit Global Wellness Days
• 4+ months paid Parental Leave
• Paid Volunteer time off

#LI-Remote

Location: US remote-friendly or any office location - SF, LA, CHI, NY

The Data Science Team at Reddit is growing and we are looking for experienced Data Scientists to partner with our cross-functional partners (Product, Engineering, Designer, Marketing, Business Development etc.) to help us build and improve the systems that continuously drive our user and revenue growth. 

As a Senior Data Scientist on the team, you will have the opportunity to play a significant role in driving the success of key product areas at Reddit (Consumer, Ads, Safety etc.). You will lead and contribute to defining the product strategy through measurement and metrics design, experimentation and causal analyses, supporting product decisions via deep data analyses, and research. 

This person will be an industry technical leader with a solid technical background, strong business acumen, and excellent cross-functional stakeholders management skills. You will go through a general Data Scientists hiring process and get matched to the product area that best fits your background and interest. 

Responsibilities:

• Develop action-oriented insights to drive the product strategy through observational causal analysis and experiment meta-analysis, and clearly communicate results to stakeholders up to the C-suite to take action based on the recommendations
• Uplevel experimentation practices on the team through guiding design, execution, and deep dive analyses to maximize learnings from A/B tests
• Create new ETLs, tables, dashboards, and other self-serve tools to enable other data scientists and cross-functional partners to find and interact with data seamlessly
• Design, evaluate, and/or measure team-level KPIs to enable quarterly goal setting and demonstrate team impact
• Regularly engage with stakeholders to gather feedback and share progress on work at all stages to ensure alignment between DS and other teams on business goals and outcomes
• Mentor more junior data scientists and business partners in data science best practices and methods to increase data literacy and improve decision making

Required Qualifications: 

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 5+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 4+ years of industry experience in applied science or data science roles
• Expertise in querying relational databases (SQL) and programming languages (e.g., R / Python)
• Deep understanding of online experimentation (A/B testing), causal inference, and statistical techniques
• Comfortable in innovative and fast-paced environments, and a bias toward action
• Strong technical communication / data storytelling skills and demonstrated ability to discuss complex topics with technical and non-technical audiences alike
• Able to tackle ambiguous and undefined problems by creating an action plan, getting feedback, and iterating

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave  

#LI-Remote #LI-NH1 

At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning.

We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem.

We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit.

If you love working on complex, real-world ML problems at massive scale, this role is for you.

What You’ll Work On

As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including:

• Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities
• Intelligent advertising systems including ranking, bidding, measurement, and optimization
• Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals
• Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems
• Applied AI and LLM-driven experiences that improve relevance, discovery, and user engagement

You’ll work on high-impact systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes.

What You’ll Do

• Design, build, and deploy production-grade machine learning models and systems at scale
• Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring
• Build scalable data and model pipelines with strong reliability, observability, and automated retraining
• Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems. 
• Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions
• Improve system performance across latency, throughput, and model quality metrics
• Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph & transformers based, and LLM evaluation/alignment 
• Contribute to technical strategy, architecture, and long-term ML roadmap

Basic Qualifications

• 3-5+ years of experience building, deploying, and operating machine learning systems in production
• Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals
• ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)
• Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
• Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure
• Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions
• Experience improving measurable metrics through applied machine learning

Preferred Qualifications

• Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems
• Familiarity with distributed systems and large-scale data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)
• Experience working with real-time systems and low-latency production environments
• Background in feature engineering, model optimization, and production monitoring
• Experience with LLM/Gen AI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale
• Advanced degree in Computer Science, Machine Learning, or related quantitative field

Potential Teams

• Ads Measurement Modeling 
• Ads Targeting and Retrieval
• Advertiser Optimization
• Ads Marketplace Quality
• Ads Creative Effectiveness
• Ads Foundational Representations
• Ads Content Understanding
• Ads Ranking
• Feed Relevance
• Search and Answers Relevance
• ML Understanding
• Notifications Relevance

Benefits

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning.

We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem.

We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit.

If you love working on complex, real-world ML problems at massive scale, this role is for you.

What You’ll Work On

As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including:

• Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities
• Intelligent advertising systems including ranking, bidding, measurement, and optimization
• Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals
• Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems
• Applied AI and LLM-driven experiences that improve relevance, discovery, and user engagement

You’ll work on high-impact systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes.

What You’ll Do

• Design, build, and deploy production-grade machine learning models and systems at scale
• Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring
• Build scalable data and model pipelines with strong reliability, observability, and automated retraining
• Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems. 
• Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions
• Improve system performance across latency, throughput, and model quality metrics
• Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph & transformers based, and LLM evaluation/alignment 
• Contribute to technical strategy, architecture, and long-term ML roadmap

Basic Qualifications

• 3-5+ years of experience building, deploying, and operating machine learning systems in production
• Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals
• ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)
• Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
• Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure
• Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions
• Experience improving measurable metrics through applied machine learning

Preferred Qualifications

• Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems
• Familiarity with distributed systems and large-scale data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)
• Experience working with real-time systems and low-latency production environments
• Background in feature engineering, model optimization, and production monitoring
• Experience with LLM/Gen AI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale
• Advanced degree in Computer Science, Machine Learning, or related quantitative field

Potential Teams

• Ads Measurement Modeling 
• Ads Targeting and Retrieval
• Advertiser Optimization
• Ads Marketplace Quality
• Ads Creative Effectiveness
• Ads Foundational Representations
• Ads Content Understanding
• Ads Ranking
• Feed Relevance
• Search and Answers Relevance
• ML Understanding
• Notifications Relevance

Benefits

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

The GenAI Security team within Reddit’s Security, Privacy, Assurance, and Corporate Engineering organization protects Reddit’s GenAI usage across employee tools, internal agents, and production user-facing systems. Our mission is to secure and protect Reddit’s AI traffic and GenAI adoption by default.

We are building zero-trust, defense-in-depth systems that verify identity, permissions, data access, and semantic intent across AI workflows. A core part of this work is developing practical, high-quality ML models that detect and prevent security risks such as prompt injection, jailbreak attempts, sensitive data exfiltration, unsafe model behavior, anomalous usage, and unauthorized agent actions.

We are looking for a Senior Machine Learning Engineer to lead model development for GenAI Security and help establish strong ML practices across SPACE. This role owns the full machine learning lifecycle: problem definition, data ETL, feature engineering, model training, model evaluation, deployment, experimentation, prediction, monitoring, debugging, and retraining.

What You’ll Do

• Build and improve security-focused ML models for Reddit’s GenAI traffic, including guardrail models, semantic classifiers, anomaly detection models, and other neural network based security signals.
• Own model development end to end: define the security problem, assemble and label datasets, build ETL pipelines, engineer features, train models, evaluate quality, deploy to production, monitor performance, and retrain from production feedback.
• Use modern deep learning architectures, including neural networks, transformers, sequence models, embeddings, and model distillation where they are the right practical fit.
• Design rigorous evaluation suites for adversarial examples, hard negatives, long-context inputs, structured payloads, tool calls, multi-turn workflows, and real production traffic.
• Improve model precision, recall, latency, cost, calibration, and operational reliability for high-impact production surfaces.
• Build repeatable MLOps workflows for SPACE, including training pipelines, model lineage, artifact management, holdout evaluation, dashboards, rollback paths, and retraining loops.
• Partner closely with ML Infrastructure, LLM Gateway, DevX, Ads, Answers, Safety, Privacy, Compliance, and other Security teams to bring security models into real production workflows.
• Work pragmatically with Reddit’s evolving ML platform, using existing infrastructure where possible and building focused tooling when needed to keep model iteration moving.
• Translate security goals into measurable model outcomes and help partners understand tradeoffs between risk reduction, latency, false positives, and product impact.
• Provide technical direction to other engineers and serve as a go-to ML expert for GenAI Security and broader SPACE model needs.

Who You Might Be

• 5+ years of experience building, training, evaluating, and deploying production ML or deep learning models.
• Hands-on experience with modern ML frameworks such as PyTorch, TensorFlow, or similar.
• Strong practical understanding of the full ML lifecycle: problem definition, data ETL, feature engineering, training, evaluation, deployment, monitoring, debugging, and retraining.
• Experience building data pipelines and working with large-scale datasets.
• Experience designing rigorous model evaluations, including precision/recall/F1, false positive analysis, threshold tuning, calibration, holdout sets, regression tests, and production-quality validation.
• Experience shipping production-quality software, preferably in Python and/or Go.
• Strong communication skills and ability to explain model behavior, risk tradeoffs, and technical decisions to cross-functional partners.
• BS degree in Computer Science, Machine Learning, a related technical field, or equivalent practical experience.
• Experience in the following areas is a plus:
  • Applying ML to security, privacy, trust and safety, abuse prevention, adversarial ML, or GenAI security problems.
  • Training or fine-tuning neural text models for complex inputs such as long-context prompts, structured payloads, code-like content, multi-turn interactions, or tool calls.
  • Production MLOps or model serving systems such as Airflow, Ray, MLflow, Triton, ONNX, Kubernetes, or similar.
  • Improving model quality through labeling strategy, hard-negative mining, synthetic data generation, distillation, or active learning.

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave  

#LI-remote

Brooklyn Sports & Entertainment creates bold, authentic, and unforgettable experiences that redefine sports, entertainment, and hospitality, The Brooklyn Way. As the parent company of marquee properties including the Brooklyn Nets, NY Liberty and Barclays Center, Brooklyn Sports & Entertainment operates at the intersection of live entertainment, premium hospitality, and community engagement.

As it expands its existing portfolio, Brooklyn Sports & Entertainment now includes a media portfolio including BK Mag, as well as Brooklyn Wine Club, and a hospitality business developing several location-based entertainment properties.

Whether on the court, on stage, or in the workplace, Brooklyn Sports & Entertainment is driven by a pursuit of excellence—constantly evolving, innovating, and pushing boundaries to elevate its business and expand its fan base. The company is deeply committed to fostering a culture of belonging and inclusion, ensuring that every interaction reflects its values of growth mindset, integrity, accountability and care.

We are guided by our core values:

• Integrity: Be intellectually honest at all times. Demonstrate the highest professional and ethical standards.
• Care: Care for everything and everyone around us. Practice empathy, respect, and inclusion to promote an environment of excellence and success.
• Growth Mindset: Develop ourselves and those around us. Experiment, learn, and improve from everything we do.
• Accountability: Deliver on our word, take responsibility for our actions, and work in the interest of our team.

SUMMARY

The AI Engineer builds agent-based systems and intelligent workflows that power Brooklyn Sports & Entertainment’s AI platform. This role focuses on developing agentic applications that automate business workflows across ticketing, venue operations, partnerships, HR, and internal development processes.

Working primarily within an AWS and Amazon Bedrock environment, the AI Engineer builds agent workflows using frameworks such as LangGraph and contributes to the organization’s internal CodeAI platform for AI-assisted development.

The team operates with shared responsibility for building and operating AI systems in production. Engineers participate in development, deployment, monitoring, and incident response while maintaining deeper expertise in their focus areas.

This role reports into the VP, Artificial Intelligence.

WHAT YOU WILL DO

Agent Development for Business Workflows

• Design and build agent-based workflows that automate internal processes across departments such as ticketing, partnerships, HR, digital products, and venue operations. Examples of workflows include but are not limited to:
  • A Ticketing Meeting Preparation Agent that gathers relevant sales insights, CRM data, and historical context to help ticketing teams prepare for client meetings.
  • Early prototypes of a Generalized "AI Coworker" agent capable of assisting teams across departments with research, reporting, and operational tasks.
• Develop agent orchestration patterns using LangGraph and Amazon Bedrock.
• Build integrations with systems such as Salesforce, internal APIs, analytics dashboards, and operational data platforms.
• Implement reliable tool-calling patterns that allow agents to safely execute operational tasks.

CodeAI Development Agents

• Build CodeAI agents that support engineering workflows including code generation, test creation, documentation, debugging, and pull request analysis.
• Work with AI-assisted developer tools including, Codex, Cursor, Claude Code, Claude Code agents.
• Contribute to internal AI-assisted development pipelines and guardrails for “vibe coding.”

Shared Production Ownership

• Participate in deployment, monitoring, and incident response for AI systems.
• Improve agent reliability through evaluation pipelines, observability metrics, and tool-call success monitoring.
• Collaborate with the LLMOps Engineer to ensure workflows meet operational reliability standards.

WHAT YOU WILL BRING

• 2–5 years of software engineering experience building production systems.
• Strong programming experience with Python or TypeScript.
• Familiarity with AWS cloud services and API-driven applications.
• Experience working with LLM APIs or AI frameworks.
• Exposure to agent frameworks such as LangGraph or similar orchestration tools.
• Familiarity with Amazon Bedrock or other LLM platforms.
• Experience using AI-assisted development tools such as Codex, Cursor, or Claude Code.

WHO YOU ARE

• You enjoy turning complex workflows into reliable automation.
• You are curious about emerging AI technologies and continuously experiment with new tools and frameworks.
• You demonstrate a strong growth mindset and actively learn as the AI ecosystem evolves.
• You thrive in fast-moving environments where experimentation and iteration are encouraged.
• You take ownership of the systems you build and are comfortable supporting them in production.

COMPENSATION

 $125,000 - $150,000 per year

Full-time employees are eligible for a robust slate of total rewards, including:

• Bonus eligibility
• Medical, dental, and vision coverage; HSA and FSA eligibility
• 401k Employer Match at 4%
• Competitive PTO policy & Company Holidays
• Parental leave policy eligible after 6 months of service
• Access to events at Barclays Center, subject to ticket availability
• Free lunch onsite Monday - Thursday; onsite barista bar
• And more!

WORK ENVIRONMENT

Works primarily in an office environment and may be expected to contribute additional hours to support system implementations.

We are an Equal Employment Opportunity (“EEO”) Employer. It has been and will continue to be a fundamental policy of the Company not to discriminate on the basis of race, color, creed, religion/creed, gender, gender identity, transgender status, pregnancy and lactation accommodations, marital status, partnership status, domestic violence victim status, sexual orientation, age, national origin, alienage, immigration, or citizenship status, veteran or military status, disability, genetic information, height and weight, arrest or conviction record, caregiver status, credit history, unemployment status, sexual and reproductive health decisions, salary history, status as a victim of domestic violence, stalking, and sex offenses, or any other characteristic prohibited by federal, state or local laws. 

At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning.

We are hiring Machine Learning Engineers across our Consumer Engineering organization, giving you the opportunity to work on a wide range of high-impact problems across the Consumer ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, and who want to help shape the future of discovery, relevance, and monetization at Reddit.

If you love working on complex, real-world ML problems at massive scale, this role is for you.

What You’ll Work On

We are looking for a Staff Machine Learning Engineer to help drive the next generation of Reddit’s ML ecosystem across recommendations, search, messaging, and foundational AI systems. You will lead high-impact initiatives from ideation to production, shaping both technical strategy and product direction across multiple ML domains. This is a highly cross-functional role partnering with Product, Data Science, and Engineering to deliver meaningful user and business impact.

This role sits at the intersection of:

• Relevance & recommendation systems (content, search, notifications)
• AI-powered discovery & LLM-driven experiences
• Content and user understanding & large-scale representation learning
• Large-scale ML infrastructure and pipelines

What You’ll Do

• Lead end-to-end ML initiatives from ideation through production and iteration, shaping technical direction and translating product goals into scalable solutions  
• Architect, build and deploy large-scale ML systems across recommendation, search, and content/user understanding, including retrieval/ranking models, representation learnings embeddings optimizations, and LLM or GenAI-powered capabilities  
• Drive measurable impact on user engagement, discovery, and long-term value
• Collaborate with cross-functional teams to align product and technical roadmaps and unlock key future ML capabilities
• Stay at the forefront of AI research, evaluating and introducing new AI/ML paradigms to keep Reddit’s ML ecosystem at the cutting edge
• Contribute to the development of best practices, guidelines, and ethical AI principles for responsible LLM development and deployment
• Mentor and guide senior and mid-level ML engineers, fostering a culture of excellence, innovation, and knowledge sharing
• Set technical vision and drive technical discussions, present findings to leadership, and contribute to long-term ML planning and decision-making

Required Qualifications

• 7+ years of experience building, deploying, and operating machine learning systems in production
• Deep understanding of machine learning methods, spanning classical approaches and modern deep learning (e.g., Transformers, GNN, etc)
• Expert at developing and productionizing models using TensorFlow, PyTorch, or Hugging Face Transformers
• Experience building production-quality code incorporating testing, evaluation, and monitoring using object-oriented programming, including experience in Python and Golang
• Experience designing and scaling ML systems, including data pipelines, feature engineering, model training/serving, and production monitoring
• Excellent communication and collaboration skills, with the ability to discuss complex technical topics with diverse teams and translating product needs into scalable ML solutions
• Track record of driving measurable impact through applied machine learning in real-world products

Preferred Qualifications

• Subject matter expertise in one of the following domains:
• Recommender systems
• Search systems (lexical and semantic retrieval and ranking)
• Content understanding (NLU/NLP/LLM, topic/taxonomy modeling, interest graphs or clustering, and multimodal understanding)
• Familiarity with distributed systems and large-scale data processing frameworks (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)
• Experience working with real-time systems and low-latency production environments
• Experience with LLM/GenAI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale
• Strong experimentation rigor, with experience formulating clear hypotheses, designing actionable learning plans and building offline/online correlations
• Advanced degree in Computer Science, Machine Learning, or related quantitative field

Potential Teams

• Home Experience
• ML Understanding
• Feed Relevance
• Answer Experience
• Search and Answers Relevance
• Search Experience

Benefits

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

#LI-Remote

Purpose of the Role

Enterprise Discovery customers increasingly require hands-on customisation beyond standard product configuration. The Machine Learning Customer Engineer is a dedicated, customer-embedded engineering role designed to own the full spectrum of technical customisation for our top-tier accounts.

You will bridge the gap between post-sales support and core product engineering, serving as a technical "special forces" operative who translates complex business requirements into tangible code and system optimisations.

The Customisation Spectrum

The FDE is purpose-built to own Levels 1–5 of the customisation spectrum, ensuring that core R&D remains focused on next-generation platform development:

1. Education: Platform training, feature evangelism, and root-cause explanation.
2. Configuration: Dashboard, integration, and algorithm configuration changes.
3. Surgical Tweaks: Customer-specific process changes and deep data analysis.
4. Custom Code: Conversational agents, platform extensions, and feature customization.
5. Escalation: Identifying major product changes for Core Engineering cycles.

Key Responsibilities

• Account Ownership: Maintain ongoing technical ownership of 2–3 high-value enterprise accounts; this is not a rotational assignment.
• Technical Implementation: Build and deploy conversational agents, custom extensions, and algorithmic tweaks to solve specific business problems.
• Data-Driven Validation: Use A/B testing and deep data analysis to validate the impact of technical changes on customer KPIs.
• On-Site Collaboration: Travel to customer sites (EMEA/AMER) to lead technical workshops and deeply understand their architectural constraints.
• Feedback Loop: Act as a critical bridge to R&D, identifying recurring customization needs that should be productized in the core platform.

Candidate Profile

We are looking for a unique blend of high-level engineering talent and strategic business acumen:

• The Mix: 50% Programmer · 30% Product Acumen · 20% Soft Skills & Problem Solving.
• Search Specialist: Deep knowledge of search internals, including ranking models, catalog configuration, relevance, recall, and personalization.
• Technical Generalist: Fluent enough in code to make minor to moderate changes to support testing and custom extensions.
• Consultative Mindset: Ability to translate nebulous business goals into specific technical solutions and communicate those to stakeholders.

Requirements

• Experience: Proven track record in Search Engineering, Machine Learning Engineering, or high-end Technical Delivery.
• Product Knowledge: Deep understanding of Discovery platforms and how ranking/algorithms impact e-commerce performance.
• Soft Skills: Exceptional communication skills with the ability to navigate complex enterprise environments.
• Mobility: Willingness to travel internationally to engage with customers in their own environments.

#LI-HO1

Important Information

Experience: +5 years

Job Mode: Full-time

Work Mode: In Person, Monterrey Mexico Offices

ID: 21306

**This is a hybrid position in Monterrey, Mexico**

Responsibilities and Duties

Co-design, prepare and deliver KPIs, helping commercial areas and sales organization to measure they performance interconnecting available data with a well designed KPIs strategy.

1. Design and develop requested KPIs from different areas / countries
2. Define and implement initiatives to improve the information homologation and standardization
3. Propose and implement new opportunities to obtain valuable information that can improve the customer experience.

Position challenges: Manage and coordinate several teams from different countries, cultures, backgrounds and expectations Maintain a constantly evolving model with all project's information

Qualifications and Skills

• Academic Background: Analytics Bachelor Degree or similar, +2 years in digital adoption areas or similar
• Areas of expertise: Commercial, Customer Experience, Process & IT, Analytics, Digital tools Technical
• Skills required by role: Software skills for data collection and presentation, Advanced Excel, Statistical programming knowledge, Ability to articulate data-driven decisions, ability to summarize and present data, well versed in the latest innovations and trends in the market related to data manipulation product and services. SQL / Snowflake is a must
• Hard Skills: Data Modeling – Snowflake DB (SQL), Excel, SQL
• Soft Skills: Decision making, Problem Solving, Resilience & Adaptability, Strategic Thinking & Execution, Teamwork & Collaboration, Time Management

About Encora 

Encora is a global company that offers Software and Digital Engineering solutions. Our practices include Cloud Services, Product Engineering & Application Modernization, Data & Analytics, Digital Experience & Design Services, DevSecOps, Cybersecurity, Quality Engineering, AI & LLM Engineering, among others. 

At Encora, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality. 

At Reddit we continue to grow our teams with the best talent. We're completely remote friendly.

Team Description:

The Data Science Team at Reddit is expanding, and we are looking for an experienced leader to head a team of talented data scientists focused on the Marketing & Business Development domain. Our core mission is to evolve Marketing & BD Data Science from ad-hoc reporting to a strategic data science partnership that scales Reddit’s marketing efforts, and to help product and marketing teams make data-driven, high-confidence decisions.

The team's work is centered around three strategic pillars:

• Data Foundations: Building and maintaining a canonical single source of truth for marketing performance and attribution, leveraging robust data foundations to power reliable campaign analyses, experimentation, and accurate Lifetime Value (LTV) modeling.
• Causal Measurement & Metrics: Ensuring consistent measurement of campaign quality and ROI by defining and deploying advanced causal decision frameworks and models.
• Decision-Making Insights: Functioning as a strategic partner to the Marketing organization, translating data into clear, actionable recommendations to guide budget allocation and identify high-value growth segments.

Responsibilities:

As a Data Science Senior Manager, you will lead a team that is crucial to Reddit's user growth strategy. You will:

• Lead and Develop: Build, lead, and mentor a high-performing team of data scientists focused on the Marketing & Business Development domain.
• Drive Strategy: Serve as a thought-partner to cross-functional leaders (Product, Engineering, Design, and Marketing), communicating and shaping the roadmap and strategy for Reddit by identifying actionable and impactful insights.
• Deliver Causal Insights: Lead initiatives to quantify the true incremental lift of marketing spend and prevent budget allocation on non-incremental channels, including developing and deploying Incremental/Predictive LTV models.
• Standardize Measurement: Oversee the establishment of measurement frameworks (incl. effective experimental designs and/or Causal inference methods) to evaluate Brand Initiatives and ensure consistent metrics are aligned across the organization for campaign quality and ROI.
• Drive Adoption: Drive the adoption of strategic and tactical recommendations based on deep product experience and data understanding to maximize our value to consumers.
• Ensure Data Quality: Take a keen interest in the collection and quality of underlying data, including overseeing work on ETLs, reporting dashboards, and data aggregations needed for business tracking and/or ML model development.
• Enable Self-Service: Lead initiatives to enable analytics self-serve capabilities for cross-functional teams.

Required Qualifications: 

• You have experience in driving product strategy and roadmaps through analytics, ideally for consumer technology products and marketplaces
• You built, led and developed high performing product analytics teams before: ideally 5+ years of leadership experience as a people manager, leading a team of up to 10 data scientists. 
• Teams you have led had expertise in causal inference, A/B testing experimentation, metric definition and governance, and product strategy
• You have led initiatives to enable analytics self serve for cross-functional teams
• You excel at communicating to both technical and non-technical people
• You have an ability to understand nuanced complex concepts and systems, and explain them simply.
• You are proficient in SQL and Python/R for hands-on analysis. You can roll up your sleeves and work side by side with your team when needed
• You have experience in leveraging AI-assisted development tools (e.g., Cursor, Claude, or similar LLMs) to improve personal and team productivity, code quality, and technical problem-solving.
• You have a collaborative attitude and natural curiosity and strong evidence-backed product opinions

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

Who We Are:
The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams.

What You’ll Do:
As a Senior Staff Software Engineer, you will help define and lead the vision for Reddit’s large-scale GenAI Platform, shaping the strategy, architecture, and operating model that enable teams across the company to build, deploy, and scale generative AI products with confidence.

Contribute to the design, implementation, and maintenance of the LLM Gateway, focusing on features like unified API endpoints for internal/externally hosted LLM, rate/token limit management, and intelligent failover mechanisms to boost uptime and reliability.

• Lead and execute the vision, strategy, and roadmap for Reddit’s large-scale GenAI Platform.
• Define the platform architecture and operating model that enable teams to build, deploy, and scale GenAI products reliably.
• Drive the strategy for a unified LAG Gateway supporting internally and externally hosted LLMs through consistent APIs and abstractions.
• Set the direction for core platform capabilities such as rate and token limit management, intelligent failover, and production resilience.
• Shape Reddit’s approach to an enterprise-grade RAG system
• Establish the strategic direction for agentic AI workflows and tool-use patterns across the platform.
• Own the end-to-end platform strategy from concept through production adoption and long-term evolution.
• Drive MLOps and LLMOps standards across CI/CD, testing, versioning, evaluation, and lifecycle management.
• Define best practices for observability, monitoring, governance, and operational excellence across GenAI systems.
• Partner across engineering, product, and leadership to align platform investments with company priorities and user needs.
• Champion platform thinking with a strong focus on scalability, reliability, performance, and developer experience.
• Influence technical direction across teams by turning emerging AI capabilities into a scalable platform strategy.

Who You Might Be:

• 10+ years of experience in ML Engineering, AI Platform Engineering, or Cloud AI Deployment roles.
• Have a track record of leading technical strategy and delivering AI platforms in cloud-based production environments at scale.
• Demonstrate strong execution by turning strategy into action, driving complex initiatives end to end, and consistently delivering high-quality platform outcomes.
• Bring deep experience operating Kubernetes and other orchestration systems in large-scale production environments.
• Deep experience with cloud-based technologies for supporting an ML platform, including tools like AWS, Google Cloud Storage, infrastructure-as-code (Terraform), and more
• Proficiency with the common programming languages and frameworks of ML, such as Go, Python, etc.
• Excellent communication skills with the ability to articulate technical AI concepts to non-technical stakeholders
• Strong focus on scalability, reliability, performance, and developer experience. You are an undying advocate for platform users and have a deep intuition for the genAI product development lifecycle.
• Strong knowledge of model serving, inference pipelines, monitoring, and observability for AI systems is a plus

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave 

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

Reddit’s Ads Data Science team is looking for a highly experienced Staff Data Scientist to advance the intelligence powering the advertiser experience on Reddit. In this role, you'll take deep ownership of a high-impact problem space within advertising, specializing in measurement, identity, and signal quality.

This is a high-impact, high-autonomy role where you'll influence strategic direction, set a high technical bar, and drive cross-functional initiatives across one or more critical focus areas in the Ads organization.

Responsibilities:

• Design the Future of Ads Identity: Develop/employ probabilistic models for identity resolution. Design the methodology that links on-platform and off-platform actions to maximize addressability while honoring privacy.
• Advance Lift Methodologies & Experimentation: Own the statistical rigor behind Reddit’s Brand and Conversion Lift products. Innovate experimental design and develop infrastructure that supports large-scale, high-velocity, low-bias testing for advertisers.
• Maximize Signal for Predictive Performance: Define the strategy for new signal sources. You will mathematically quantify the value of these signals and work with modeling teams to incorporate them into predictive models, directly improving bidding efficiency and ROAS.
• Define Ground Truth & Evaluation Frameworks: Solve the industry-wide challenge of validating identity and measurement. Design the objective functions and truth sets used to train our models and measure the incremental impact of our identity graph.
• Lead Through Cross-Functional and Technical Influence: Collaborate deeply with engineering, product, and sales to align on strategic goals, translate insights into action, and drive execution. Set a high technical bar by mentoring others and championing best practices across modeling, experimentation, and measurement.

Qualifications:

• Required:
  • Advanced degree (Master's or Ph.D.) in Statistics, Mathematics, Physics, Economics, or Operations Research
  • For M.S. holders: 10+ years of industry experience in applied science or data science roles
  • For Ph.D. holders: 6+ years of industry experience in applied science or data science roles
  • Deep understanding of the ads ecosystem
  • Demonstrated expertise in at least one of the following areas:
    • Measurement & Experimentation at Scale (with focus on lift and attribution)
    • Identity Graph Creation & Resolution Methodology and Infrastructure
    • Predictive Modeling with Signal Loss
  • Advanced proficiency in statistical programming (Python or R) and SQL
  • Experience with machine learning or optimization techniques
  • Strong understanding of experimental design, causal inference, or A/B testing methodologies
  • Exceptional problem-solving and communication skills, with a track record of influencing product and engineering partners
  • Experience working in fast-paced, ambiguous environments with cross-functional teams

Benefits:

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Comprehensive Medical Benefits & Health Care Spending Account
• Registered Retirement Savings Plan with matching contributions
• Income Replacement Programs
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

#LI-Remote

Who We Are:
The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams.

What You’ll Do:
As a Staff ML Infrastructure Engineer, you will lead development of a platform for large scale ML models at Reddit.

• Design end-to-end model lifecycle patterns (MLOps) to boost velocity of development for ML engineers, including data preparation, model management, experiment tracking, and more
• Zero-to-one development and support of a graph ML codebase and platform that abstracts away common patterns and enables greater model scalability and iteration
• Collaborate with ML engineers on performance tuning, including improving model training time, efficiency, and GPU training costs in a large, distributed ML training environment
• Optimize batch data processing within a data warehouse and with tools such as Apache Beam, Apache Spark, Ray Data, and more
• Architect pipelines to build and maintain massive graph data structures on the order of billions of nodes and tens of billions of edges

Who You Might Be:

• 8+ years of experience in ML infrastructure, including model training and model deployments
• Hands-on experience with ML optimization, including memory and GPU profiling
• Deep experience with cloud-based technologies for supporting an ML platform, including tools like GCP BigQuery, Google Cloud Storage, infrastructure-as-code (Terraform), and more
• Hands-on experience administering and integrating MLOps tools for experiment tracking, model serving, and model registries (e.g. MLflow or Wandb)
• Proficiency with the common programming languages and frameworks of ML, such as Python, PyTorch, Tensorflow, etc.
• Deep experience working with distributed training frameworks, including Ray and Kubernetes
• Strong focus on scalability, reliability, performance, and ease of use. You are an undying advocate for platform users and have a deep intuition for the machine learning development lifecycle.
• Strong organizational & communication skills
• Experience working with graph databases (Neo4j, JanusGraph, TigerGraph) is a big plus
• Experience working with graph neural networks (GNNs) and associated graph ML frameworks (PyTorch Geometric, Deep Graph Library) is a big plus

Location: US remote-friendly

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

Reddit’s Ads Data Science team is looking for a highly experienced Staff Data Scientist to advance the intelligence powering the advertiser experience on Reddit. In this role, you'll take deep ownership of a high-impact problem space within advertising, specializing in measurement, identity, and signal quality.

This is a high-impact, high-autonomy role where you'll influence strategic direction, set a high technical bar, and drive cross-functional initiatives across one or more critical focus areas in the Ads organization.

Responsibilities:

• Design the Future of Ads Identity: Develop/employ probabilistic models for identity resolution. Design the methodology that links on-platform and off-platform actions to maximize addressability while honoring privacy.
• Advance Lift Methodologies & Experimentation: Own the statistical rigor behind Reddit’s Brand and Conversion Lift products. Innovate experimental design and develop infrastructure that supports large-scale, high-velocity, low-bias testing for advertisers.
• Maximize Signal for Predictive Performance: Define the strategy for new signal sources. You will mathematically quantify the value of these signals and work with modeling teams to incorporate them into predictive models, directly improving bidding efficiency and ROAS.
• Define Ground Truth & Evaluation Frameworks: Solve the industry-wide challenge of validating identity and measurement. Design the objective functions and truth sets used to train our models and measure the incremental impact of our identity graph.
• Lead Through Cross-Functional and Technical Influence: Collaborate deeply with engineering, product, and sales to align on strategic goals, translate insights into action, and drive execution. Set a high technical bar by mentoring others and championing best practices across modeling, experimentation, and measurement.

Qualifications:

• Required:
  • Advanced degree (Master's or Ph.D.) in Statistics, Mathematics, Physics, Economics, or Operations Research
  • For M.S. holders: 10+ years of industry experience in applied science or data science roles
  • For Ph.D. holders: 6+ years of industry experience in applied science or data science roles
  • Deep understanding of the ads ecosystem
  • Demonstrated expertise in at least one of the following areas:
    • Measurement & Experimentation at Scale (with focus on lift and attribution)
    • Identity Graph Creation & Resolution Methodology and Infrastructure
    • Predictive Modeling with Signal Loss
  • Advanced proficiency in statistical programming (Python or R) and SQL
  • Experience with machine learning or optimization techniques
  • Strong understanding of experimental design, causal inference, or A/B testing methodologies
  • Exceptional problem-solving and communication skills, with a track record of influencing product and engineering partners
  • Experience working in fast-paced, ambiguous environments with cross-functional teams

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave  

#LI-Remote