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

About the Team: The Brand Ad Formats team drives the development of ad formats that help advertisers maximize reach and brand impact. They focus on high-visibility, awareness-driven solutions that create memorable experiences for Reddit users. By delivering guaranteed placements and engaging ad interactions, they support major brand initiatives and help advertisers achieve measurable outcomes.  The team is building fully customizable interactive formats and AI-driven ads that incorporate User-Generated Content (UGC).  Moving forward, we will be doubling down on Video Ads, with the goal of turning Reddit into an industry leader and a ‘must buy’ for advertisers to promote video content.

As a Staff Android Engineer, you will lead the technical strategy to turn Reddit’s Video Ads into a premier offering for brand advertisers.  You will also build and provide technical guidance on new reddit-unique ad formats on Android, ensuring they are high performance, high quality and scalable.

What you’ll do: 

• Video Ads Tech Lead: Partner closely with Product and Design to build a roadmap that will transform our Video Ads format into an industry leader in the space, and drive the technical design and execution of projects that turn the roadmap into reality.
• Technical Strategy: Provide guidance to the team working on building video ads as well as reddit-unique ad formats that scale to millions of users, by establishing Android best practices and providing design reviews.
• Full-Cycle Leadership: Drive the entire development lifecycle—from early-stage discovery and prototyping to testing, data-driven experimentation, and deployment.
• Raise the Bar: Mentor senior engineers across teams in ad formats and establish best practices for design, testing and operational excellence, while also leading by example in understanding and advocating for our customers.

What we expect from you: 

• 8+ years of software engineering experience (Staff level seniority). 
• Android Mastery: (Minimum of 3+ years) Deep expertise in Kotlin and modern Android architectural patterns.  Completed 4+ Android development projects from ideation to deployment in production.
• Prior experience in Ad Tech, building highly interactive/rich-media mobile experiences.
• Product Mindset: Proven track record of delivering user-facing features where UI polish and performance are critical. 
• System Design: Ability to navigate complex, data-intensive environments and build fault-tolerant client-side systems.
• AI: Experience leveraging GenAI tools to increase software engineering productivity.
• Experimentation/Analysis: Fluency working with product metrics, designing and analyzing experiments with exposure to tools like BigQuery, HEX, Firebase, etc.
• Versatility: An openness to work across the stack when necessary and explore innovative approaches (e.g., AI/ML integration).
• Entrepreneurial spirit: You must be self-directed, innovative, and biased towards action. You live to build new things and thrive in ambiguity.
• Excellent communication skills: You must be able to collaborate with teams in a fully remote environment, and discuss complex topics with technical and non-technical audiences.
• An experienced technical leader with a strong track record of mentoring and uplifting team members technical skills and aptitude.
• Strong organizational skills, the ability to prioritize tasks and keep projects on schedule for the team.
• BS degree in Computer Science, similar technical field of study, or equivalent practical experience.

Bonus points:

• Experience working on Video Ads
• Experience working at a scaled peer company
• Experience with Jetpack Compose

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

About the Team: The Brand Ad Formats team drives the development of ad formats that help advertisers maximize reach and brand impact. They focus on high-visibility, awareness-driven solutions that create memorable experiences for Reddit users. By delivering guaranteed placements and engaging ad interactions, they support major brand initiatives and help advertisers achieve measurable outcomes.  The team is building fully customizable interactive formats and AI-driven ads that incorporate User-Generated Content (UGC).  Moving forward, we will be doubling down on Video Ads, with the goal of turning Reddit into an industry leader and a ‘must buy’ for advertisers to promote video content.

As a Staff Android Engineer, you will lead the technical strategy to turn Reddit’s Video Ads into a premier offering for brand advertisers.  You will also build and provide technical guidance on new reddit-unique ad formats on Android, ensuring they are high performance, high quality and scalable.

What you’ll do: 

• Video Ads Tech Lead: Partner closely with Product and Design to build a roadmap that will transform our Video Ads format into an industry leader in the space, and drive the technical design and execution of projects that turn the roadmap into reality.
• Technical Strategy: Provide guidance to the team working on building video ads as well as reddit-unique ad formats that scale to millions of users, by establishing Android best practices and providing design reviews.
• Full-Cycle Leadership: Drive the entire development lifecycle—from early-stage discovery and prototyping to testing, data-driven experimentation, and deployment.
• Raise the Bar: Mentor senior engineers across teams in ad formats and establish best practices for design, testing and operational excellence, while also leading by example in understanding and advocating for our customers.

What we expect from you: 

• 8+ years of software engineering experience (Staff level seniority). 
• Android Mastery: (Minimum of 3+ years) Deep expertise in Kotlin and modern Android architectural patterns.  Completed 4+ Android development projects from ideation to deployment in production.
• Prior experience in Ad Tech, building highly interactive/rich-media mobile experiences.
• Product Mindset: Proven track record of delivering user-facing features where UI polish and performance are critical. 
• System Design: Ability to navigate complex, data-intensive environments and build fault-tolerant client-side systems.
• AI: Experience leveraging GenAI tools to increase software engineering productivity.
• Experimentation/Analysis: Fluency working with product metrics, designing and analyzing experiments with exposure to tools like BigQuery, HEX, Firebase, etc.
• Versatility: An openness to work across the stack when necessary and explore innovative approaches (e.g., AI/ML integration).
• Entrepreneurial spirit: You must be self-directed, innovative, and biased towards action. You live to build new things and thrive in ambiguity.
• Excellent communication skills: You must be able to collaborate with teams in a fully remote environment, and discuss complex topics with technical and non-technical audiences.
• An experienced technical leader with a strong track record of mentoring and uplifting team members technical skills and aptitude.
• Strong organizational skills, the ability to prioritize tasks and keep projects on schedule for the team.
• BS degree in Computer Science, similar technical field of study, or equivalent practical experience.

Bonus points:

• Experience working on Video Ads
• Experience working at a scaled peer company
• Experience with Jetpack Compose

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

About the Team: The Brand Ad Formats team drives the development of ad formats that help advertisers maximize reach and brand impact. They focus on high-visibility, awareness-driven solutions that create memorable experiences for Reddit users. By delivering guaranteed placements and engaging ad interactions, they support major brand initiatives and help advertisers achieve measurable outcomes.  The team is building fully customizable interactive formats and AI-driven ads that incorporate User-Generated Content (UGC).  Moving forward, we will be doubling down on Video Ads, with the goal of turning Reddit into an industry leader and a ‘must buy’ for advertisers to promote video content.

As a Staff Android Engineer, you will lead the technical strategy to turn Reddit’s Video Ads into a premier offering for brand advertisers.  You will also build and provide technical guidance on new reddit-unique ad formats on Android, ensuring they are high performance, high quality and scalable.

What you’ll do: 

• Video Ads Tech Lead: Partner closely with Product and Design to build a roadmap that will transform our Video Ads format into an industry leader in the space, and drive the technical design and execution of projects that turn the roadmap into reality.
• Technical Strategy: Provide guidance to the team working on building video ads as well as reddit-unique ad formats that scale to millions of users, by establishing Android best practices and providing design reviews.
• Full-Cycle Leadership: Drive the entire development lifecycle—from early-stage discovery and prototyping to testing, data-driven experimentation, and deployment.
• Raise the Bar: Mentor senior engineers across teams in ad formats and establish best practices for design, testing and operational excellence, while also leading by example in understanding and advocating for our customers.

What we expect from you: 

• 8+ years of software engineering experience (Staff level seniority). 
• Android Mastery: (Minimum of 3+ years) Deep expertise in Kotlin and modern Android architectural patterns.  Completed 4+ Android development projects from ideation to deployment in production.
• Prior experience in Ad Tech, building highly interactive/rich-media mobile experiences.
• Product Mindset: Proven track record of delivering user-facing features where UI polish and performance are critical. 
• System Design: Ability to navigate complex, data-intensive environments and build fault-tolerant client-side systems.
• AI: Experience leveraging GenAI tools to increase software engineering productivity.
• Experimentation/Analysis: Fluency working with product metrics, designing and analyzing experiments with exposure to tools like BigQuery, HEX, Firebase, etc.
• Versatility: An openness to work across the stack when necessary and explore innovative approaches (e.g., AI/ML integration).
• Entrepreneurial spirit: You must be self-directed, innovative, and biased towards action. You live to build new things and thrive in ambiguity.
• Excellent communication skills: You must be able to collaborate with teams in a fully remote environment, and discuss complex topics with technical and non-technical audiences.
• An experienced technical leader with a strong track record of mentoring and uplifting team members technical skills and aptitude.
• Strong organizational skills, the ability to prioritize tasks and keep projects on schedule for the team.
• BS degree in Computer Science, similar technical field of study, or equivalent practical experience.

Bonus points:

• Experience working on Video Ads
• Experience working at a scaled peer company
• Experience with Jetpack Compose

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 Safety Enforcement Team’s mission is to fairly and consistently remove violative content, educate Reddit users as well as internal teams on Content Policy, and use technology to improve enforcement at scale. We’re looking for our first ever AI Operations Specialist to join a founding team on a greenfield initiative that will  influence the safety and experience of hundreds of millions of users and shape how Reddit approaches automated safety for years to come. 

As a Senior AI Enforcement Analyst, you won’t just follow a playbook. You will be tasked with authoring it! This is a rare opportunity to be a founding member of a team that is fundamentally changing how Reddit thinks about safety. You will architect the automation of enforcement and shape how policy intent is translated into live model behavior across Reddit’s safety systems. 

This is not a technical role. We don't need more people to build the engines; we need the specialized "pilots" who know exactly where and how to fly them. We are looking for senior Trust & Safety operators with strong AI literacy who understand how to leverage automation responsibly at scale and bridge the gap between high-level policy intent and production enforcement systems. You will own the evolution of our AI-driven enforcement quality, ensuring systems remain effective, ethical, and resilient as policies, products, and adversarial behavior evolve.

If you’re excited by the challenge of making LLMs understand the messy, beautiful nuance of Reddit’s niche communities, this is your role.

Responsibilities:

• Own Automated Enforcement Quality: Serve as a strategic owner for enforcement outcomes across AI-driven systems. You will diagnose underperformance and make go/no-go recommendations on when models are ready for production.
• Translate Policy Into Models: Act as the primary “policy-to-model” translator. You’ll craft prompts, define evaluation criteria, and curate high-quality datasets (“golden sets”) that teach models to distinguish between contextual debate and policy violations.
• Guide Model Evolution: Monitor enforcement performance over time, identifying concept drift, policy changes, or emerging threats that require retraining, prompt updates, or evaluation redesign.
• Surface Blind Spots: Develop monitoring strategies for niche communities, edge cases, and emerging behaviors to ensure enforcement systems reflect Reddit’s diversity and complexity.
• Safeguard Model Integrity: Flag risks, escalate incidents, and recommend rollbacks or mitigations when automated systems fall below quality or safety thresholds, in partnership with ML and Product stakeholders.

Qualifications: 

• 5-7+ years of experience in Trust & Safety, with hands-on exposure to automated or scaled enforcement systems.
• AI-Literate with an understanding of how LLM-based and classifier-driven enforcement systems behave in production, including their strengths, limitations, and failure modes. You can evaluate errors, interpret metrics, and connect model behavior back to policy intent. 
• Familiarity with AI safety concepts such as evaluation design, data quality, labeling strategies, and continuous improvement loops, applied through an operational lens.
• Experience in SQL and/or Python is preferred. Overall, you should be able to use data to investigate issues, assess tradeoffs, and inform decisions—not just report outcomes.
• Ability to move fluidly between technical discussions with ML partners and strategic alignment with Policy, Legal, and Product leaders.
• Experience with content moderation, scaled enforcement programs, policy interpretation, and real-time incident response in complex environments.

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-SP1

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

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

Reddit’s lower funnel business is rapidly growing and pushing the heavy ranking web conversion models towards state-of-the-art is critical for continued growth. The Conversion modeling Team plays a pivotal role in developing and maintaining machine learning models that drive user conversions from Reddit Ads, with a special focus on predictive modeling around interactions like purchase, signup, add to cart, and other lower funnel user actions. 

As we expand our machine learning infrastructure and incorporate new engagement signals, we are looking for a skilled Engineering Manager who can lead this critical team. This role is well-suited for a leader with deep machine learning expertise, strategic vision, and a collaborative mindset to engage with both technical and cross-functional stakeholders.

We’re a remote-friendly company, and this position is open to candidates anywhere in the U.S.

Target Skills and Expertise

The Engineering Manager (EM) will be responsible for defining the team’s vision, setting strategic direction, and executing a technical roadmap for conversion modeling at Reddit. This involves:

• Model Architectures: Expertise in architecting and implementing deep learning models, with experience in ranking, recommendation, or conversion modeling.
• ML Frameworks: Proficiency with mainstream ML libraries (TensorFlow, PyTorch).
• End-to-End ML Lifecycle: Experience in training, testing, and deploying production-grade machine learning models.
• Data Pipelines: Experience orchestrating large-scale data generation and processing pipelines.
• Ads domain Experience: Experience in interaction of ranking model with rest of Ads systems like bidding, auction, retrieval etc
• Ads Modeling (Preferred): Background in ads modeling or familiarity with engagement prediction models in the ads domain is beneficial.

Role responsibilities:

The EM will lead a diverse, high-impact team and will need to navigate and foster collaboration with various teams such as PM, DS, and engineering functions within Ads. Ideal candidates will have:

• People Management Experience: Prior experience managing engineering teams with a strong emphasis on technical mentorship and team growth.
• Set Technical Vision and Strategy: Ability to plan and execute a long-term technical strategy aligned with business objectives. Define and execute a roadmap for conversion modeling, balancing innovative modeling approaches with business objectives.
• Drive Technical Execution: Oversee the model development lifecycle from ideation to deployment, ensuring high standards of ML performance and robustness.
• Lead and Mentor a High-Performing Team: Recruit, mentor, and retain top ML talent, fostering a culture of growth, collaboration, and technical excellence.
• Collaborate Cross-Functionally: Partner with PMs, data scientists, and other engineering teams to align on engagement strategies, data requirements, and model KPIs.
• Innovate in ML Architecture: Implement and optimize model architectures tailored to conversion prediction, leveraging deep learning and advanced ML techniques.

Required qualifications:

• At least 2+ of experience building and managing high-performing machine learning teams, ideally in the Ads domain. Will consider tech lead experience as well
• Deep ML Expertise: Deep hands-on experience working with machine learning models and deploying them in large-scale production systems.  Proven ability in training, evaluating, and deploying large-scale models.
• Technical Domain Knowledge:  Experience with Ads conversion modeling, ranking (heavy ranker experience) & recommendations experience is required. 
• Strategic Thinking: Ability to develop and communicate a clear, compelling technical strategy that supports broader company objectives and addresses the needs of internal customers.
• Impact-Driven Mindset: Passion for developing scalable, well-designed, and responsible AI solutions that drive business value.
• Exceptional Communication & Collaboration: Strong interpersonal skills and a collaborative mindset, with the ability to effectively communicate complex technical topics to diverse audiences and build strong relationships with cross-functional partners

Experience with Ads conversion modeling is a plus

Perks and Benefits:

• 100% remote opportunity (we have 4 office locations for hybrid/onsite work preference in NY, SF, LA and Chicago)
• Competitive salary and equity options
• Comprehensive health benefits (medical, dental, vision) & workplace perks (home office set up stipend etc)
• Generous 401k matching
• Flexible vacation policy 
• Paid parental leave (4+ months)
• Family planning support
• Paid volunteer time off

#LI-AS1

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  

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

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 

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

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 targeting, relevance modeling, auction optimization, measurement, and user experience. 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 Data Scientist to join our growing Ads Data Science team. As a Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve our understanding of the dynamics that drive the success of our advertising platform, and identify opportunities to accelerate that success. You will work closely with stakeholders across product, engineering, sales, marketing, and data to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Develop ML models & DS methods to for improved anomaly detection, prediction, pattern recognition
• Communicate findings and recommendations to stakeholders across the organization
• Collaborate with product, engineering, sales, and marketing partners to define product and program requirements and translate them into data science solutions
• Stay up-to-date on the latest advancements in machine learning and data science

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 3+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 2+ years of industry experience in applied science or data science roles
• 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

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 targeting, relevance modeling, auction optimization, measurement, and user experience. 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 Data Scientist to join our growing Ads Data Science team. As a Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve our understanding of the dynamics that drive the success of our advertising platform, and identify opportunities to accelerate that success. You will work closely with stakeholders across product, engineering, sales, marketing, and data to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Develop ML models & DS methods to for improved anomaly detection, prediction, pattern recognition
• Communicate findings and recommendations to stakeholders across the organization
• Collaborate with product, engineering, sales, and marketing partners to define product and program requirements and translate them into data science solutions
• Stay up-to-date on the latest advancements in machine learning and data science

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 3+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 2+ years of industry experience in applied science or data science roles
• 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

About the Team

The Advertiser Optimization team is a strategic, high-growth engine within Reddit Ads. Our mission is to democratize high-performance advertising by enabling brands to achieve world-class results with minimal friction. We empower advertisers to identify their ideal audiences and scale their impact through sophisticated automation and intelligence.

Our portfolio spans the core pillars of the Reddit Ads ecosystem:

• Precision & Reach: Targeting, Planning, and Forecasting.

• Performance & Scale: Bidding, Budget Management, and Pacing.

• Intelligence: AI-driven Recommendations and Optimization Scores.

The Role

As a leader within this critical organization, you will hold significant ownership over Reddit’s long-term monetization strategy. You will manage multiple broad product areas, leading a high-performing team to build products that are as delightful as they are effective.

Core Responsibilities

• Leadership & Growth: Hire, mentor, and develop a world-class team of Product Managers, fostering a culture of excellence and innovation.

• Strategy & Vision: Define and champion the long-term product vision for advertising products; translate complex advertiser needs into a cohesive, high-impact roadmap.

• Cross-Functional Partnership: Collaborate seamlessly with Engineering, Data Science, Design, Sales, and Marketing to launch products that drive measurable advertiser success.

• Execution: Own key performance indicators (KPIs) and drive the end-to-end execution of features within the product suite.

• Communication: Craft compelling product narratives and present strategic updates to diverse stakeholders, including the executive leadership team.

• Market Leadership: Stay at the forefront of ad tech evolution, identifying emerging opportunities to keep Reddit Ads ahead of the curve.

Qualifications

Minimum Requirements

• Industry Expertise: 8+ years of Product Management experience, specifically within Ads Quality or building Advertiser-facing products.

• Leadership: Proven track record as an experienced people manager with a focus on talent development.

• Strategic Impact: A history of developing product visions that result in quantifiable business growth.

• Analytical Rigor: Exceptional problem-solving skills and the ability to turn complex data into actionable product insights.

• Influence: Strong interpersonal and communication skills; able to align cross-functional teams and influence senior stakeholders.

Preferred Qualifications

• Management Scale: Experience managing people managers and leading multi-layered organizations.

• Technical Depth: A background in Computer Science, Mathematics, or a related quantitative field.

• Advanced Tech: Experience leading Machine Learning product teams or shipping ML-driven features.

Perks and Benefits:

• 100% remote opportunity (we have 4 office locations for hybrid/onsite work preference in NY, SF, LA and Chicago)
• Competitive salary and equity options
• Comprehensive health benefits (medical, dental, vision) & workplace perks (home office set up stipend etc)
• Generous 401k matching
• Flexible vacation policy 
• Paid parental leave (4+ months)
• Family planning support
• Paid volunteer time off 

#LI-AS1

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

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 

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

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

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 Software Engineer, Machine Learning Platform (Training Platform), you will be instrumental in architecting, implementing, and maintaining foundational Machine Learning (ML) infrastructure that powers Feeds Ranking, Content Understanding, Recommendations and much more to fulfill Reddit’s mission of bringing community and belonging to everyone in the world.  You will deliver a self service ML platform that enables the continuous iteration and improvement of systems that use ML techniques including Deep Learning, Natural Language Processing, Recommendation Systems, Representation Learning and Computer Vision.

• Lead the building, testing, and maintenance of ML training infrastructure at Reddit.
• Play a pivotal role in designing, building, and optimizing the infrastructure and tooling required to support large-scale machine learning workflows.
• Evolve the MLE experience, from provisioning interactive GPU environments through large-scale training, supporting on-demand and self-service workflows.
• Kubernetes Automation: Write custom Kubernetes Controllers and Operators to manage the lifecycle of interactive Jupyter workspaces and long-running ML training jobs, handle auto-idling, and ensure fault tolerance.
• GPU Orchestration: Work with the underlying compute team to ensure MLEs have efficient access to training hardware resources and handle resource contention gracefully.
• Developer Experience (DevX): Treat internal MLEs as your customers. Conduct user research, reduce friction in the "Idea-to-Prototype" loop, and standardize software environments (Docker images, Python dependency management).

Who You Might Be:

• 5+ years of software engineering experience, with a focus on Platform Engineering, ML Infrastructure, or Backend Systems.
• Deep Kubernetes Expertise: You know K8s beyond just "deploying pods." You understand CRDs, Controllers and the Operator pattern.
• Jupyter Ecosystem Knowledge: Experience customizing JupyterHub, JupyterLab extensions, or building similar interactive computing platforms.
• Strong Coding Skills: Proficiency in Python (for the ML ecosystem) and Go (for Kubernetes controllers/infrastructure tooling).
• GPU Experience: Hands-on practice with CUDA environments, GPU virtualization/containerization, and doing it all within Kubernetes.
• Cloud Provider Experience: Familiarity with both managed ML offerings (Vertex AI, Sagemaker, etc) and building custom ML components in AWS and/or GCP.
• Experience working with distributed training frameworks, including Ray and Kubernetes.
• Comfortable with distributed systems, big data (Petabyte scale) and data-intensive systems.
• 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.

Benefits

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k Match
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Reddit Global Days off
• Generous paid Parental Leave  
• Paid Volunteer time off

#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 Senior Software Engineer, you will lead the development of a large-scale GenAI Platform at Reddit.

• 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.
• Designed and developed ML and Generative AI systems in cloud-based production environments at scale.
• Build and manage enterprise-grade RAG applications using embeddings, vector search, and retrieval pipelines.
• Implement and operationalize agentic AI workflows with tool use using frameworks such as LangChain and LangGraph.
• Drive adoption of MLOps / LLMOps practices, including CI/CD automation, versioning, testing, and lifecycle management.
• Establish best practices for observability, monitoring, evaluation, and governance of GenAI pipelines in production.
• Strong ownership mindset and platform thinking.
• Ability to lead AI platform delivery from concept to production.

Who You Might Be:

• 5+ years of experience in ML Engineering, AI Platform Engineering, or Cloud AI Deployment roles.
• Have experience operating orchestration systems such as Kubernetes at scale
• 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 ease of use. 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
• Strong proficiency in Python and experience with modern AI/ML frameworks (e.g. LangChain, Vertex AI Agent Builder, TensorFlow, PyTorch 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 

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 Machine Learning Engineer, you will lead the development of a large-scale ML Inference Platform at Reddit.

• Lead the end-to-end design, implementation, and maintenance of a highly available, low-latency GPU-based model serving system for search, ranking, and LLMs supporting Millions of QPS.
• Design and develop ML and Generative AI systems in cloud-based production environments on Kubernetes at scale.
• Rapidly develop prototypes and develop a high-performance feature hydration and processing system as a part of the inference stack - including routing, caching, and batching.
• Lead a unified GPU model export framework to support converting trained models into optimized GPU inference models.
• Strong understanding of real-time ML observability to track feature/model performance.
• Experience working with LLM serving online at scale.
• Built an E2E inference performance benchmarking framework
• Deep Understanding of multi-cluster compute environment and network topology that is specific to ML inference use cases.

Who You Might Be:

• 7+ years of experience in ML Engineering, AI Platform Engineering, or Cloud AI Deployment roles.
• Have experience operating orchestration systems such as Kubernetes at scale
• 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 ease of use. 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
• Strong proficiency in Python and deep experience with modern AI/ML frameworks (Triton, Dynamo, vLLM, Pytorch)

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 

Search Infrastructure builds and operates the foundational components for platform teams at Reddit to build atop. Our systems satisfy needs ranging from classical ranking/search (BM25) to more modern and novel spaces involving vector embeddings. We are a team of software and machine learning engineers who build platforms around and evolve technologies including:

• Milvus
• Vespa
• Solr
• Kubernetes

Our platform strives to balance reliability, performance, efficiency, and developer productivity, in that order. We offer abstractions that enable our customers to express their needs and transparently map those into underlying infrastructure resources (CPU, memory, architecture, etc). Software engineering is the core of our DNA. We scale the team through automation, self healing, and orchestration.

As Reddit’s usage of AI and embedding models grows, conventional databases don’t fit the needs of our scale. This is an opportunity to sit at the cutting edge of this space and help establish the future of Reddit’s search capabilities while maturing a (relatively) newer ecosystem of technologies. These capabilities will post everything from Reddit.com’s search, to Ads Platforms, and many other ranking/relevance use cases.

Some Of Our Present And Future Challenges Include:

• Scaling search primitives, namely databases, to be secure, highly available, and geo-distributed.
• Contributing to ecosystems (OSS) involving codebases including Go, Rust, C++, and Java.
• Managing the full lifecycle of our systems including provisioning, scaling, self healing, and decommissioning via software engineering. 

Our interfaces are APIs and our operators are code, not humans.

• Working with and abstracting systems like Milvus, Vespa, and Solr to support key use cases, such as lexical search, semantic search, and relevance/ranking.
• Running these systems with high-efficiency without sacrificing reliability.

What You’ll Do

• Steer: Work with the team to select, scope, and drive high leverage projects that align with Reddit’s goals.
• Build: Build out your team to execute on a strategy and create more efficient, more reliable Storage systems.
• Amplify: Mentor your ICs and be a leader for the team.
• Collaborate: Work together with a variety of teams across Reddit Engineering.
• Evolve: Learn and improve your own technical and non-technical abilities.

You Have:

• 3+ years experience in people management of high performing engineering teams.
• 7+ years experience on backend infrastructure with a focus on storage systems.
  • 5+ years of this experience spent in high-scale environments is key.
    • Reddit’s challenges go beyond building/adopting new tech and often into how we scale them as one of the largest use cases.
  • Experience in storage systems pertaining to full-text search and vector similarity search (ANN) is a huge plus.
• Experience with running storage systems atop orchestration/distributed systems, such as Kubernetes.
• Strong focus on scalability, performance, and quality. You are an undying advocate for the user, and you have a deep intuition for how critical infra systems work 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

Who We Are:
The Machine Learning Platform team at Reddit is a high-impact team that owns the foundational embeddings and 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 Engineering Manager, Unified Embeddings Platform, you will work lead our Embeddings Platform Team and be instrumental in architecting, implementing, and maintaining platform providing foundational ML embeddings  based on state of the art architectures such as large scale graph neural networks, foundational models, large scale sequence models, etc.  empowering all product verticals at Reddit to fulfill Reddit’s mission of bringing community and belonging to everyone in the world. You’ll partner with teams across Reddit infrastructure and ML modelling at the center of machine learning to enable machine learning engineers (MLEs) and data scientists (DSs) to improve the ML feature software development lifecycle.

• Lead the creation of foundational embeddings at Reddit leveraging state of the art architectures such as graph neural networks, transformer based sequence models, foundational models, etc.
• Lead the design and long-term evolution of Reddit’s Embeddings platform enabling all ML teams access, store and share embeddings
• Drive high-impact, high-leverage projects that align with Reddit’s broader engineering and business goals
• Build and grow a high-performing team, including hiring, mentoring, and creating a culture of technical excellence
• Establish and champion best practices for the production, consumption, and governance of machine learning features
• 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.

Who You Might Be:

• 4+ years of experience in people management
• 8+ years of work experience in a production software development environment
• 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.
• Experience working on large-scale ML Systems serving 100s of millions of users
• Experience building self service platform enabling storage and sharing of large scale data and embeddings
• Experience with leading modelling teams powering the creation of foundational embeddings based on state of the art architectures
• Strong organizational & communication skills

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 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:

• 5+ 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

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

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

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

Team
The ML Indexing & Retrieval Platform team at Reddit is responsible for building and scaling the core infrastructure that powers machine learning driven recommendations. We design and maintain systems for ML data ingestion, low-latency retrieval services, and end-to-end lifecycle management of data. With a focus on performance, reliability, and scalability, we enable real-time access to high-quality data that supports a wide range of applications, including Content Understanding, Semantic, Lexical retrieval & GenAI applications. 

How You'll Have Impact

You’ll lead the development of next-generation ML Indexing & Retrieval systems, owning the full lifecycle from ideation to production and going beyond incremental improvements to reimagine core platform capabilities. As part of a high-impact, cross-functional team, you’ll solve complex technical challenges to build scalable, reliable platforms that empower developers to efficiently ship critical ML features.

Languages: Go, Java, Python, or any object oriented programming language

Frameworks: Flink, Airflow, Spark for large scale batch & stream processing 

Databases: Familiarity with Vector, Lexical & Key-Value Databases 

Tools: Kubernetes, Docker, AWS, GCP

What You’ll Do

• Lead the technical strategy, architecture, and implementation of Reddit’s next-generation ML Indexing & Retrieval engine, integrating capabilities across lexical and vector indexing, low-latency retrieval, and emerging GenAI applications.
• Partner closely with product engineers across Content Understanding, Search, Feeds, Ads, Growth, and Safety to deliver high-quality experiences.
• Define best practices for observability, reliability, and operational excellence in large-scale distributed systems.
• Mentor and guide engineers in designing scalable infrastructure and adopting robust DevOps and SRE principles.
• Collaborate with infrastructure, and ML teams to ensure the platform evolves to meet the needs of Reddit’s growing user base and diverse content ecosystem.

Who You Might Be:

• 10+ years of experience in software engineering, specializing in Indexing and Retrieval systems.
• 3+ years in technical leadership, architecting and scaling distributed systems in production environments.
• Deep expertise in large-scale data platforms, including batch indexing and stream processing.
• Proven experience designing and operating large-scale, low-latency retrieval services.
• Expertise in lexical and vector search retrieval technologies, such as Milvus, Vespa, or Elasticsearch. 
• Skilled in designing cloud-native architectures and managing containerized workloads using Kubernetes and AWS/GCP.
• Adept at translating complex technical challenges into clear, actionable strategies.
• Strong communicator and mentor who leads through collaboration, influence, and technical excellence.

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

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

The Ads Measurement Engineering team builds the systems that power advertiser outcomes and ads optimization across Reddit’s Ads platform. The team owns critical infrastructure and products spanning conversion signal ingestion, attribution, lift measurement, reporting, and the reliable delivery of measurement data to downstream ML and ads systems.

We are looking for a Director of Engineering to lead this organization. This leader will drive the technical strategy and execution for scalable measurement systems that improve advertiser performance and enable effective optimization across the ads stack.

This role requires strong technical depth in ads measurement and distributed systems, as well as the ability to lead complex cross-functional initiatives across Engineering, Product, Data Science, Product Marketing, and Business Development. The ideal candidate combines organizational leadership with a hands-on engineering mindset and can effectively operate across strategy, architecture, and execution.

Responsibilities

• Lead and grow a high-performing organization of engineering managers and engineers focused on Ads Measurement infrastructure and products
• Define and execute the technical roadmap for key measurement capabilities including conversion ingestion, attribution, signal quality, lift measurement, and downstream ML signal delivery
• Drive engineering execution across scalability, reliability, latency, and data quality requirements for critical measurement systems
• Partner closely with Product, Data Science, ML Engineering, Product Marketing, and Business Development to align technical investments with advertiser and business priorities
• Improve the quality, usability, and trustworthiness of measurement signals used across reporting, optimization, and ads delivery systems
• Establish strong engineering practices around system design, operational excellence, experimentation, and long-term platform maintainability
• Identify architectural gaps, technical risks, and scaling bottlenecks, and drive solutions across organizational boundaries
• Hire, mentor, and develop engineering leaders and senior engineers while fostering a culture of technical rigor, accountability, and execution velocity
• Stay current with industry trends in ads measurement, attribution, and signal resilience in a rapidly evolving ecosystem

Qualifications

• 10+ years of software engineering experience, including experience leading engineering teams and organizations in the ads or measurement domain
• Experience leading engineering managers and senior engineers in building large-scale distributed systems and data-intensive platforms
• Strong technical understanding of ads measurement systems and technologies such as conversion APIs, pixel infrastructure, attribution systems, signal quality, and lift measurement
• Experience building or operating systems that support ML optimization, ads delivery, reporting, or experimentation use cases
• Proven ability to drive cross-functional initiatives across engineering, product, data science, and go-to-market teams
• Strong systems thinking with the ability to balance long-term architecture, execution speed, and operational reliability
• Excellent communication and organizational leadership skills, with experience aligning teams around technical strategy and business priorities
• Familiarity with the evolving ads measurement ecosystem and industry trends impacting attribution and signal reliability

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 Community Builders organization exists to empower anyone, anywhere, to create and steer a thriving community. We do that by making community building intuitive, sustainable, and rewarding. That mission sits at the heart of Reddit's long-term health as a platform: a Reddit with more thriving communities is a better Reddit for everyone, and our job is to make sure the path to "thriving" is one any passionate person can actually walk.

The Engagement team is where we cultivate Reddit's community growth. We help new communities find their audience and build the kind of momentum that keeps them engaged long after the first few posts. We aim to connect users with content and conversations to which they want to contribute, no matter how niche the topic. 

Our north star is thriving communities. These are places where moderators are engaged, members keep returning, and content compounds on itself. Getting communities there requires a content flywheel that surfaces the right guidance and tools at the right moment to speed up organic engagement. We use data, ML-powered signals, and product experimentation to identify and remove every barrier standing between a community and sustainable, self-reinforcing growth.

This is a Growth team. We move with urgency, instrument everything, and treat a missed activation milestone as a signal to learn from, not a number to ignore. If you want to build systems that measurably change the trajectory of tens of thousands of communities, and improve the health of Reddit itself, this is your team.

What you'll do: 

 Foster and Guide the Technical Strategy for Growth 

Define and accelerate the backend architecture powering the team's core growth levers: the systems that get new communities in front of the right people across feeds, search, and onboarding surfaces, and the infrastructure that drives member participation to build sustained content momentum. You won't just be following a roadmap; you'll shape how we build these systems from the ground up.

🤝Partner With the EM to Cultivate a Growth Engineering Mindset

Growth teams operate differently than platform teams. We prioritize experimentation and iteration, which means sometimes we throw things away to move faster. You'll help the team internalize that operating model: what it means to build for learning, how to balance velocity with reliability, and how to stay rigorous when moving fast.

🤖Scale Impact Through Collaborative Engineering

Just as thriving communities don't succeed in isolation, neither does this team. You'll build and maintain deep partnerships with the engineering teams whose surfaces directly shape community growth: Relevance, Feeds, Search, and beyond. Many of these collaborations will touch ML-powered systems that surface the right communities to the right users. You'll be the bridge that ensures Community Builders has a technical representation for the team and a collaborative influence on their roadmaps.

📊Instrument, Measure, and Iterate

Establish the instrumentation and experimentation foundations that let the team run rigorous A/B tests on growth levers. Translate data from activation funnels, retention curves, and content engagement into architectural choices. Use metrics to make the case for the bets worth taking, and deprioritize efforts that don't meet goals.

🔗Guide Cross-Functional Alignment

Serve as the engineering voice in XFN partnerships with Product, Design, Data Science, and other Consumer platform teams. You'll align stakeholders on technical feasibility and tradeoffs, co-author roadmaps that bridge user experience goals with backend realities, and represent Community Builders Engineering in Reddit-wide technical forums.

⚡Raise the Bar on Engineering Excellence

Advocate for reliability, scalability, and maintainability across a complex, high-scale distributed system. Lead design reviews, establish patterns that the broader organization can learn from, and ensure that moving fast never becomes an excuse for accruing crippling tech debt. You'll define what "great" looks like on this team.

Who You Might Be

• At least 7 years of experience. You’ve steered cross-team projects that solved tangible business problems, rather than just hitting a 'ship' date.
• A strategic partner, not just a technologist. A systems thinker. You see how the code, the product, and the team dynamics all influence each other. You can plan for next year while still helping an engineer through a blocker today.
• You're a mentor who helps other engineers level up. You don't just assign tasks; you help the team work through complex problems more effectively. You're energized by the opportunity to build culture and craft on a team, not just software.
• You're deeply data-informed and logical. You ensure metrics are part of the design process, not just an afterthought in a dashboard. Your architectural directions are traceable back to product and business outcomes, and you're fluent in the language of experimentation, funnels, and retention.
• Comfortable with growth-team ambiguity. You navigate ambiguity with confidence when the goal is clear but the path is not. You're comfortable with growth-team speed—prototyping fast, moving on when the data doesn't back a bet, and keeping the team focused when the plan changes.
• A focus on clear, transparent communication. You can effectively distill complex technical trade-offs for any audience—whether you’re collaborating on a whiteboard with peers or presenting a roadmap review to executive stakeholders.
• Experience with ranking, recommendations, and personalization. You have a proven track record of working on ML-heavy products. You can design the backend architectures, retrieval systems, and inference pipelines required to scale them. You understand the nuances of candidate generation and scoring, and you can partner effectively with Machine Learning engineers to turn model outputs (such as Two-Tower models) into high-impact product features.

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 

We are seeking a Staff Software Engineer to lead the technical architecture of our media infrastructure. In this role, you will define the strategy for how we ingest, process, store, and deliver video and audio content at Reddit. You will tackle complex technical challenges while also helping shape our media product strategy to deliver high-quality media experiences globally.

Key Responsibilities

• Architect for Scale: Lead the design and evolution of our global media processing and delivery infrastructure, ensuring low-latency, high-availability media for millions of users.
• Accelerate product roadmap: Closely partner with XFNs to identify product opportunities to increase media consumption at Reddit.
• Optimize Media Pipelines: Build and optimize resilient backend services for video/audio ingestion, distributed transcoding, and CDN routing.
• Drive AI Integration: Partner with ML/AI teams to build a roadmap that supports media recommendation, content understanding, and GenAI.
• Set the Standard: Establish engineering best practices, design the next generation of our media services, define strict SLOs/SLAs for our media operations.
• Mentorship & Leadership: Guide and empower multiple engineering teams. Translate complex product requirements into actionable technical roadmaps and drive alignment across the company.
• Leverage Modern Tooling: Thoughtfully utilize AI-assisted development tools to accelerate prototyping, system design, and coding, while applying rigorous judgment to validate and own the final outputs. Evangelize AI as a tool.

Qualifications

• 8+ years of professional software engineering experience, with a proven track record as a Technical Lead or Staff Engineer.
• Distributed Systems Expertise: Proven track record of designing and operating large-scale distributed systems, event-driven architectures, and microservices.
• Communication: Exceptional written and verbal communication skills. Ability to influence technical direction and navigate tradeoffs between performance, reliability, and business impact without directly managing the engineers involved.
• Demonstrated ability to lead large, cross-functional engineering initiatives that balance technical excellence.

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 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

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

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

The Home Experience team is responsible for one of the highest traffic pages on the platform: the Home feed on the Reddit apps and website. Home is both a destination and entrypoint for almost all Reddit journeys, and we know a smooth, intuitive, and delightful experience is critical to Reddit’s success and appeal. You’ll be working with the immense scale of hundreds of millions of users to help them explore Reddit and provide them with excellent feeds.

This role can be remote within the United States, Canada, or Europe, or can be a hybrid model if near an office. Offices are located in San Francisco, Los Angeles, Chicago, New York City, Toronto, London, Amsterdam, Madrid and Berlin. 

What You’ll Do:

• Be the technical lead for a high-caliber, inclusive team of engineers across the organization.
• Work cross-functionally, collaborate and partner with product, design, and other engineering counterparts to design and build novel products and features that our users will love.
• Work alongside a team of thoughtful, fast-moving, and motivated engineers. Drive step-function improvements in developer workflows, implement best practices, and mentor engineers across the organization..
• Participate in the full development cycle: design, development, test, experimentation, analysis, and launch. You’ll be writing and reviewing code and design docs, giving feedback on product specs and mocks, and ensuring successful delivery of key projects.
• You will be a main driver in the planning, development, and implementation across Reddit’s Android architecture in conjunction with numerous partner teams, identifying and delivering on major opportunities.
• Enable a culture of metrics led execution, with a focus on operational excellence and system observability.
• Partner cross-functionally and with senior leadership on our strategic roadmap, driving engineering and product bets that will bring Home to the next level.

Who You Might Be:

• 8+ years of experience as a software engineer developing user-facing applications
• Fluency working with product metrics, designing and analyzing experiments with exposure to tools like BigQuery, HEX, Firebase, etc.
• Software development experience in Kotlin for Android, familiarity with GraphQL.
• Experience leveraging GenAI tools to increase software engineering productivity.
• Experience working with ML engineering teams and integrating ML solutions is a plus.
• Strong organizational skills, the ability to prioritize tasks and keep projects on schedule for the team.
• BS degree in Computer Science, similar technical field of study, or equivalent practical experience.
• Strong focus on user experience and usability. You are an undying advocate for the user, and you have a deep intuition for how people think and how they interact with software. Experience with social is a huge plus.
• Entrepreneurial spirit. You must be self-directed, innovative, and biased towards action. You live to build new things and thrive in ambiguity.
• Excellent communication skills. You must be able to collaborate with teams in a fully remote environment, and 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 

This is a remote role.

About Us
Reachdesk is the first truly end-to-end global SaaS gifting and swag platform, helping B2B companies create meaningful connections with prospects, customers, and employees, while driving measurable ROI.

We believe gifting is more than just a transaction: it’s about building genuine human connections that fuel business growth. Whether you’re engaging prospects, celebrating customers, or recognizing employees, our platform makes it easy to deliver personalized gifts, branded swag, and unforgettable event & brand experiences at scale through automated sourcing, storage, and global delivery.

We’re growing, and we’re currently looking for a Head of Business Systems & Operations to join us.

The Role

As the Head of Business Systems & Operations at Reachdesk, you will own and shape the systems and data architecture that underpin how the business operates. You will be responsible for connecting Finance, GTM, Product, and Customer teams through a single, trusted system landscape, ensuring data flows cleanly across Salesforce, NetSuite, Workato, and our BI layer. This is a high impact role where you will define how the business uses its systems, not just maintain them.

You will join at a critical stage as we complete our closed-loop architecture and transition ownership from product into the business. You will have full autonomy to design, govern, and evolve this ecosystem while embedding AI into core workflows and decision making. This role is particularly suited to someone who enjoys creating order from complexity: building a reliable, scalable foundation that the business trusts, enabling faster decisions, stronger financial control, and a step change in operational efficiency across Reachdesk.

Your Responsibilities

• Own the end-to-end systems and data architecture connecting Salesforce, NetSuite, Workato, the Reachdesk SaaS platform and the BI layer.
• Lead the transition of systems ownership into Business Operations and establish a clear operating model, governance framework, and roadmap that the business trusts and that can evolve as needs change, ensuring trusted, timely data flows across Finance, GTM, Product, and Customer teams.
• Lead from the front by setting technical direction from being in the systems alongside your team, not just reviewing their work. Define the go-forward BI architecture, ownership model, and roadmap.. 
• Complete and continuously evolve this architecture so every core process is underpinned by clean data and reliable automation.
• Establish an AI governance framework to embed AI into core workflows and decision-making, from forecasting and pipeline insights to customer health, billing, and operational automation, delivering measurable efficiency gains.
• Define and enforce master data management and integration standards across all systems.
• Partner closely with Finance, RevOps, Customer Operations, and Product to translate business priorities into scalable system solutions, balancing speed of delivery with long-term architectural integrity.
• Build, lead, and develop a small, high-performing team of systems and operations specialists, and manage external delivery partners where needed.
• Own vendor relationships, contracts, and roadmaps for our core SaaS stack, ensuring we get value, leverage, and influence over product direction, with a focus on finding efficiencies and cost savings.  
• Define and report on system health, data quality, and operational efficiency KPIs to the executive team and Board where relevant.

About You

You are a strategic systems leader with strong technical instincts and a pragmatic builder mentality. You see business systems as a competitive advantage, not a back-office function, and you are energized by the opportunity to shape the operating engine of a high-growth, PE-backed SaaS business. You understand the importance and value of data integrity and consistency, ensuring every department relies on the same core data and metrics. You are still in the system. You are as comfortable in a Salesforce flow, a NetSuite saved search, or a Workato recipe as you are in a strategy meeting. You believe leaders in this function lose their edge the moment they stop building, and you have no interest in becoming that person. You move comfortably between architecture decisions and detailed configuration, and you are equally at home in a conversation with the CFO, the CRO, or an engineer. You bring a hands-on operator mindset: you understand that great systems exist to make the business faster, sharper, and more accountable, and you measure your success by the decisions and outcomes they enable.

Must-have Qualifications

• 8+ years in Business Systems, RevOps, or BizTech leadership roles within B2B SaaS, with at least 3 years leading a function or team.
• Deep expertise across Salesforce and NetSuite, including a track record of designing and evolving the integration layer between them.
• Strong experience with iPaaS platforms (Workato strongly preferred) and modern BI tooling.
• Demonstrated ability to design and operate a closed-loop architecture, covering quote-to-cash, lead-to-revenue, and customer lifecycle, in a multi-entity, multi-currency environment.
• Demonstrably hands-on within the last 12 months and can speak in concrete detail about systems you have personally configured, automations you have built, or data models you have designed.
• Robust data governance and master data management discipline, with a clear point of view on ownership, lineage, and quality.
• Proven track record of leading complex, cross-functional systems programs end-to-end, on time and on budget.
• Excellent stakeholder management, particularly with Finance and GTM leadership, and the ability to translate technical decisions into commercial impact.
• People leadership experience with a coaching mindset, and the ability to build a small team that punches above its weight.

Preferred Qualifications

• Experience in a PE-backed, high-growth SaaS environment with tight financial control requirements.
• Familiarity with multi-stream revenue models (e.g. SaaS combined with services, marketplace, or fulfillment) and the revenue recognition complexity they bring.
• Experience embedding AI/ML or agentic automation into operational workflows, with named use cases, governance, adoption controls, and measurable business outcomes.
• NetSuite and/or Salesforce certifications.
• Experience transitioning systems ownership into a Business Operations function.
• Background working in a scaling SaaS business, comfortable operating across time zones and entities.

The Benefits

• Competitive salary with generous stock options
• 401(k) with employer match
• Medical, dental & vision insurance, including mental health support and fast access to care
• Flexible PTO that increases the longer you’re with us, plus extra flexibility for life’s unexpected moments
• A genuinely collaborative culture with innovative, fun, and ambitious people

Reachdesk believes that a diverse team helps us achieve our mission faster, and so we welcome applicants from all backgrounds. Compensation is based on standardised salary ranges by role, level, and location, benchmarked against similar-sized companies. Final offers are determined by a combination of experience, skills, and role fit, and may vary from the listed range.

Privacy Policy: We process personal information submitted as part of your application in accordance with the Reachdesk Candidate Privacy Notice. Please review Reachdesk’s Privacy Policy here: www.reachdesk.com/candidate-privacy-policy 

This is a remote role.

About Us
Reachdesk is the first truly end-to-end global SaaS gifting and swag platform, helping B2B companies create meaningful connections with prospects, customers, and employees, while driving measurable ROI.

We believe gifting is more than just a transaction: it’s about building genuine human connections that fuel business growth. Whether you’re engaging prospects, celebrating customers, or recognizing employees, our platform makes it easy to deliver personalized gifts, branded swag, and unforgettable event & brand experiences at scale through automated sourcing, storage, and global delivery.

We’re growing, and we’re currently looking for a Head of Business Systems & Operations to join us.

The Role

As the Head of Business Systems & Operations at Reachdesk, you will own and shape the systems and data architecture that underpin how the business operates. You will be responsible for connecting Finance, GTM, Product, and Customer teams through a single, trusted system landscape, ensuring data flows cleanly across Salesforce, NetSuite, Workato, and our BI layer. This is a high impact role where you will define how the business uses its systems, not just maintain them.

You will join at a critical stage as we complete our closed-loop architecture and transition ownership from product into the business. You will have full autonomy to design, govern, and evolve this ecosystem while embedding AI into core workflows and decision making. This role is particularly suited to someone who enjoys creating order from complexity: building a reliable, scalable foundation that the business trusts, enabling faster decisions, stronger financial control, and a step change in operational efficiency across Reachdesk.

Your Responsibilities

• Own the end-to-end systems and data architecture connecting Salesforce, NetSuite, Workato, the Reachdesk SaaS platform and the BI layer.
• Lead the transition of systems ownership into Business Operations and establish a clear operating model, governance framework, and roadmap that the business trusts and that can evolve as needs change, ensuring trusted, timely data flows across Finance, GTM, Product, and Customer teams.
• Lead from the front by setting technical direction from being in the systems alongside your team, not just reviewing their work. Define the go-forward BI architecture, ownership model, and roadmap.. 
• Complete and continuously evolve this architecture so every core process is underpinned by clean data and reliable automation.
• Establish an AI governance framework to embed AI into core workflows and decision-making, from forecasting and pipeline insights to customer health, billing, and operational automation, delivering measurable efficiency gains.
• Define and enforce master data management and integration standards across all systems.
• Partner closely with Finance, RevOps, Customer Operations, and Product to translate business priorities into scalable system solutions, balancing speed of delivery with long-term architectural integrity.
• Build, lead, and develop a small, high-performing team of systems and operations specialists, and manage external delivery partners where needed.
• Own vendor relationships, contracts, and roadmaps for our core SaaS stack, ensuring we get value, leverage, and influence over product direction, with a focus on finding efficiencies and cost savings.  
• Define and report on system health, data quality, and operational efficiency KPIs to the executive team and Board where relevant.

About You

You are a strategic systems leader with strong technical instincts and a pragmatic builder mentality. You see business systems as a competitive advantage, not a back-office function, and you are energized by the opportunity to shape the operating engine of a high-growth, PE-backed SaaS business. You understand the importance and value of data integrity and consistency, ensuring every department relies on the same core data and metrics. You are still in the system. You are as comfortable in a Salesforce flow, a NetSuite saved search, or a Workato recipe as you are in a strategy meeting. You believe leaders in this function lose their edge the moment they stop building, and you have no interest in becoming that person. You move comfortably between architecture decisions and detailed configuration, and you are equally at home in a conversation with the CFO, the CRO, or an engineer. You bring a hands-on operator mindset: you understand that great systems exist to make the business faster, sharper, and more accountable, and you measure your success by the decisions and outcomes they enable.

Must-have Qualifications

• 8+ years in Business Systems, RevOps, or BizTech leadership roles within B2B SaaS, with at least 3 years leading a function or team.
• Deep expertise across Salesforce and NetSuite, including a track record of designing and evolving the integration layer between them.
• Strong experience with iPaaS platforms (Workato strongly preferred) and modern BI tooling.
• Demonstrated ability to design and operate a closed-loop architecture, covering quote-to-cash, lead-to-revenue, and customer lifecycle, in a multi-entity, multi-currency environment.
• Demonstrably hands-on within the last 12 months and can speak in concrete detail about systems you have personally configured, automations you have built, or data models you have designed.
• Robust data governance and master data management discipline, with a clear point of view on ownership, lineage, and quality.
• Proven track record of leading complex, cross-functional systems programs end-to-end, on time and on budget.
• Excellent stakeholder management, particularly with Finance and GTM leadership, and the ability to translate technical decisions into commercial impact.
• People leadership experience with a coaching mindset, and the ability to build a small team that punches above its weight.

Preferred Qualifications

• Experience in a PE-backed, high-growth SaaS environment with tight financial control requirements.
• Familiarity with multi-stream revenue models (e.g. SaaS combined with services, marketplace, or fulfillment) and the revenue recognition complexity they bring.
• Experience embedding AI/ML or agentic automation into operational workflows, with named use cases, governance, adoption controls, and measurable business outcomes.
• NetSuite and/or Salesforce certifications.
• Experience transitioning systems ownership into a Business Operations function.
• Background working in a scaling SaaS business, comfortable operating across time zones and entities.

The Benefits

• Competitive salary with generous stock options
• 401(k) with employer match
• Medical, dental & vision insurance, including mental health support and fast access to care
• Flexible PTO that increases the longer you’re with us, plus extra flexibility for life’s unexpected moments
• A genuinely collaborative culture with innovative, fun, and ambitious people

Reachdesk believes that a diverse team helps us achieve our mission faster, and so we welcome applicants from all backgrounds. Compensation is based on standardised salary ranges by role, level, and location, benchmarked against similar-sized companies. Final offers are determined by a combination of experience, skills, and role fit, and may vary from the listed range.

Privacy Policy: We process personal information submitted as part of your application in accordance with the Reachdesk Candidate Privacy Notice. Please review Reachdesk’s Privacy Policy here: www.reachdesk.com/candidate-privacy-policy 

The role

We are seeking a highly skilled ML/AI Engineer to join our team to lead and support benchmarking of GPU platforms benchmarking of GPU platforms for machine learning and AI workloads. You will play a critical role in evaluating the performance of GPU-based hardware for various deep learning and AI frameworks, enabling data-driven decisions for platform optimisation and next-generation hardware development.

Your responsibilities will include:

• Work closely with hardware, development teams to profile and analyse GPU performance at the system and kernel level.
• Evaluate and compare GPU performance across different platforms, architectures, and software stacks (e.g.,CUDA, ROCm).
• Debug and optimise ML workloads to run efficiently on GPU hardware, identifying and resolving performance bottlenecks.
• Perform acceptance testing acceptance testing for new GPU clusters, ensuring hardware and software meet performance, stability, and compatibility requirements for AI workloads.
• Perform experiments across diverse GPU system configurations to assess the impact of varying interconnect strategies and system-level optimisations on performance and scalability.
• Develop tools and dashboards to visualise performance metrics visualise performance metrics, bottlenecks, and trends.
• Contribute to internal tooling, frameworks, and best practices

We expect you to have:

• A profound understanding of theoretical foundations of machine learning
• Deep understanding of performance aspects of large neural networks training and inference (data/tensor/context/expert parallelism, offloading, custom kernels, hardware features, attention optimisations, dynamic batching etc.)
• Deep experience with modern deep learning frameworks (PyTorch, JAX, Megatron-LM, Tensort-LLM)
• Good understanding of the GPU stack: CUDA,NCCL, drivers, and relevant libraries
• Familiarity with containerized environments (e.g., Docker, Kubernetes).
• Strong communication and ability to work independently

Ways to stand out from the crowd:

• Familiarity with modern LLM inference frameworks (vLLM, SGLang, TensorRT)
• Experience in Python and performance profiling tools (e.g., Nsight, nvprof, perf).
• Familiarity with cloud ML platforms like AWS, GCP, Azure ML
• Contributions to open-source ML benchmarking tools

About Sand

Sand Technologies is a global Physical AI company using data and AI to make critical industries work better. We partner with governments, cities and enterprises to improve how essential systems operate across healthcare, water, energy, telecommunications and infrastructure.

Our work delivers proven real-world impact. We have built AI systems that help manage London’s water supply, supported telecom network planning across hundreds of cities, and developed digital healthcare platforms serving tens of millions of people across Africa. From intelligent command centers to AI-powered infrastructure platforms, we help organizations sense, analyze and act in complex environments.

Our people are ambitious, curious and relentlessly practical. Our teams work alongside clients in the field, solving hard problems and deploying solutions that last. With colleagues across Africa, Europe, the UK and the US, we operate across the full stack - from research and engineering to deployment and capability building.

Our mission is simple: to harness AI to solve humanity’s most pressing challenges.

About the role

Forward Deployed Engineers (FDEs) are Sand’s frontline inside our most strategic customers; embedding directly within client teams to unlock data, building lightweight production solutions, and compressing time-to-value from months to weeks. This is not staff augmentation. This is a value-engineering role: hands-on, deeply technical, fast, and focused on proving ROI in real operational environments.

As an FDE, you will sit inside one of our US industries—Energy, Utilities, or Public Sector—and be deployed full-time on-site with a client. You will work shoulder-to-shoulder with operators, engineers, analysts, and executives to identify opportunities, access and shape data, prove value through rapid prototyping, and deploy solutions that drive measurable financial and operational outcomes.

Your work directly shapes commercial expansion, platform evolution, and the credibility of Sand in the most complex asset-heavy environments.

This role is ideal for a technically strong engineer or scientist who thrives in ambiguity, loves solving real-world problems in the field, and has the communication and resilience needed to earn trust inside demanding customer environments.

Specific Responsibilities

1. Value Engineering & Rapid Solution Delivery

• Embed directly inside the client to unlock data, map value streams, and build lightweight production-grade solutions.
• Execute rapid analysis, prototyping, and iterative validation using wrangling tools, secure sandboxes, and proven patterns.
• Deliver measurable outcomes within weeks—fast deployments, clear ROI proof points, and visible operational value.

2. Technical Execution & On-site Delivery

• Deploy models, dashboards, optimizers, and operational tools that solve high-value client problems in Energy, Utilities, or Public Sector.
• Troubleshoot friction: data access, workflows, security constraints, stakeholder blockers—removing obstacles in real time.
• Maintain a production mindset: reliability, iteration, and continuous improvement of deployed solutions.

3. Client Engagement & Trust Building

• Build deep trust with operators, engineers, and senior stakeholders through hands-on delivery—not slides.
• Translate complex technical problems into simple, actionable insights that drive adoption and operational use.
• Train users, institutionalize capabilities, and transfer knowledge so the client can sustain value.

4. Pattern Capture & Platform Feedback

• Document field patterns, reusable components, and validated workflows that feed into Sand’s product roadmap.
  Work with Product Managers and Platform Engineering to generalize what works and escalate gaps in product capability.
• Ensure every deployment contributes to reusability, pattern libraries, and cross-vertical knowledge.

5. Growth Contribution (non-sales, but commercial)

• Identify expansion opportunities through on-the-ground insights and signal them to the MD and Solutions Director.
• Help shape new enterprise AI propositions with real-world field intelligence from Energy/Utilities/Public Sector operations.
• Support the Solutions Director in scoping high-value follow-on work.

Requirements - Essential

• 2–6 years of experience as a Data Scientist, Data Engineer, ML Engineer, or Software Engineer working with real datasets and operational environments.
• Experience deploying solutions in Energy (Oil & Gas, Power), Utilities (Water/Gas/Electric), or Public Sector strongly preferred.
• Proven ability to build prototypes and production-grade tools quickly, with minimal dependencies.
• Experience working directly with customers, operators, or business stakeholders in fast-paced environments.
• Comfort working independently on-site with high ambiguity and high accountability.

Technical Skills

• Strong coding ability (Python preferred) plus SQL, wrangling, and modern data tooling.
• Experience with APIs, cloud environments, data ingestion patterns, and analytical tooling.
• Ability to turn messy, real-world data into operational insights and deployed tools.
• Understanding of ML modeling, optimisation, or operations research is a plus (but not required).
• Experience with visualization tools and rapid prototyping frameworks.

Why this role matters

FDEs are the spearhead of Sand Technologies’ expansion in the US. They compress time-to-value, generate trust, and turn initial projects into multi-year strategic partnerships. Their insights directly shape the roadmap of our Industry Operating Systems and Co-Pilot Suites.

If you want to work on the frontier of enterprise AI—inside the most complex operational environments in the world—this is the role.

Personal Attributes

• Client Centricity & Integrity: We let Our Clients Run the Company, Surf Like Yvon to stay true to our values, and Play the Long Game with integrity.
• Collaboration and Inclusion: We live by Each One, Teach Ten and ensure Everybody is Welcome.
• Operational Excellence and Simplicity: We K.I.S.S. by keeping things simple while always striving to Raise the Bar.
• Action, Ownership, and Execution: We Decide, Get Stuff Done, and Do Hard Things with accountability.
• Growth, Innovation, and Resilience: We Choose Growth, Pioneer boldly, and remember There is No Failure.

Due to the considerable amount of virtual work and interaction with colleagues and customers in different physical locations internationally, it is essential that the successful applicant has the drive and ethic to succeed in working in small teams physically but in larger efforts virtually. Self-drive to communicate constantly using web collaboration and video conferencing is essential.

About the role

The Command Center Manager is responsible for overseeing real-time operations of the autonomous fleet, ensuring safe, efficient, and reliable execution of all missions.

This role leads the Command Center team, including Dispatch and Remote Assistance, and serves as the central point of coordination for operational decision-making, incident response, and cross-functional alignment.

At Applied Intuition, you will:

• Lead and Program manage the command center operations 
• Oversee the entire fleet dispatch and remote assistance process
• Incident management and escalation process development and management
• Develop processes and procedures and support development of tooling that enables future scale
• Coordinate cross-functionally within operations and among all other stakeholders to ensure mission success and continuity.

We're looking for someone who has:

• 5+ years in autonomy operations, logistics, fleet management, or similar field
• Experience leading real-time operations or control centers
• Strong decision-making and problem-solving skills
• Ability to manage multiple workflows simultaneously
• Experience in autonomous vehicles, robotics, or transportation
• Experience with dispatch systems or fleet operations platforms
• Able to travel up 35%

Nice to have:

• Experience leading teams in high-pressure environments
• Experience working cross-functionally with engineering teams

Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment.

Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position.

Please reference the job posting’s subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the location listed is: $137,000 - $177,000 USD annually.

About the role

At Applied Intuition, you will:

• Conduct role-by-role competency analyses across all global operations functions to identify knowledge gaps and define what “good” looks like at each career stage
• Design learning journeys for each operations role, from onboarding through ongoing professional development, ensuring alignment with business objectives and safety-critical standards
• Build, curate, and maintain a scalable curriculum of instructor-led courses, e-learning modules, simulations, hands-on labs, and assessments tailored to ADAS/AD and autonomy operations
• Partner with engineering, product, customer success, and field operations leaders to translate technical subject matter into accessible, high-impact training content
• Stand up and manage a Learning Management System (LMS) or equivalent platform to deliver, track, and report on training across all global sites
• Develop certification and credentialing frameworks that validate readiness for safety-critical operations tasks
• Establish measurement frameworks (Kirkpatrick or similar) to evaluate training effectiveness, drive continuous improvement, and report ROI to leadership
• Recruit, mentor, and manage a small team of instructional designers, facilitators, and training coordinators as the function grows
• Adapt and localize training programs for international teams across multiple languages, time zones, and regulatory environments

We're looking for someone who has:

• Bachelor’s degree in Instructional Design, Organizational Development, Education Technology, or a related field; Master’s degree preferred
• 7+ years of experience designing, building, and deploying training programs at scale, with at least 3 years in the autonomous vehicle, ADAS, robotics, or a comparable safety-critical industry
• Proven track record of conducting role-based competency analyses and translating them into structured learning journeys and curricula
• Deep expertise in instructional design methodologies (ADDIE, SAM, or similar) and adult learning principles
• Experience selecting, implementing, and administering LMS platforms and digital learning tools
• Strong program management skills with the ability to manage multiple concurrent curriculum builds across geographies
• Exceptional stakeholder management and communication skills, with a demonstrated ability to influence technical and non-technical leaders
• Willingness to travel domestically and internationally to support global training deployments

Nice to have:

• Experience building training programs specifically for vehicle operations, test operations, fleet management, or field deployment teams
• Familiarity with ADAS/AD toolchains, simulation platforms, data labeling pipelines, or HIL/SIL testing workflows
• Experience with blended and immersive learning formats including VR/AR-based training simulations

Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment.

Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position.

Please reference the job posting’s subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the location listed is: $148,000 - $173,000 USD annually.

Your Impact  

In this hands-on role, the Manufacturing Operator will identify, prioritize, and simultaneously accomplish multiple tasks using time management. You will perform tasks and motions ranging from basic in nature to complex. Repetitive to non-repetitive production assembly operations on electronic and/or mechanical assemblies and sub-assemblies such as modules, boards, and panels. You will follow process flows, work instructions, standardized techniques, and sequence of operations in assembling parts, component installation, hand soldering, and sub-assemblies and units.  
 
Your Day-to-Day  

• Maintain a safe work environment by following Axon safety policies 

• Maintains quality standards according to process flows and work instructions 

• Must be able to demonstrate a mathematical aptitude in addition, subtraction, multiplication, and division 

• Good written and verbal communication skills  

• Takes initiative and elevates accurate information to technicians and maintenance when needed 

• Knowledge of materials and production processes  

• An excellent understanding of equipment sequence and the impact and effects it has in the production process 

• The ability to evaluate and complete quality checks 

• Always maintains housekeeping in areas to 7-S standards. 

• Serve as a resource to others in the resolution of problems and issues 

• Ability to read and follow written procedures related to tooling / equipment changeover(s), checklists, tooling maintenance, tooling repair, tooling storage and retrieval and tool shop housekeeping. 

• Must be self-directed and reliable  
• Looks for process errors and brings them forward to supervisor 

  Basic Qualifications 

• High School Diploma or Equivalent Years of Work Experience 

• Basic Computer Literacy  

• Able to follow instructions and production schedules 

• Adaptable and able to act quickly when problems arise 

• Attention to detail 
• Good coordination, motor skills and dexterity 
• Ability to stand for upwards of 10 hours a day; as well as lift, carry, move packages and materials up-to-40 lbs. on a regular basis; with or without special accommodations, is required 

• Prior Manufacturing experience 

• IPC Certification 

• Basic Microsoft Suite 

• Manufacturing Machine Operations 
• Strong Communication and Organizational Skills  

Physical Requirements:   

• Spend Time Standing and sitting. 

• Spend Time Using Your Hands to Handle, Control, or Feel Objects, Tools, or Controls. 

• Ability to stand for upwards of 12 hours a day; as well as lift, carry, move packages and materials up-to-50 lbs on a regular basis; with or without special accommodations, is required 
• Spend Time Making Repetitive Motions. 

Benefits that Benefit You

• Competitive salary and 401k with employer match
• Discretionary paid time off
• Paid parental leave for all
• Medical, Dental, Vision plans
• Fitness Programs
• Emotional & Mental Wellness support
• Learning & Development programs
• And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work

Your Impact  
In this hands-on role, the Manufacturing Operator will identify, prioritize, and simultaneously accomplish multiple tasks using time management. You will perform tasks and motions ranging from basic in nature to complex. Repetitive to non-repetitive production assembly operations on electronic and/or mechanical assemblies and sub-assemblies such as modules, boards and panels. You will follow process flows, work instructions, standardized techniques, and sequence of operations in assembling parts, component installation, hand soldering, and sub-assemblies and units.  
 
Your Day-to-Day  

• Maintain and promote a safe working environment by adhering to all safety requirements 

• Responsible for working in a manufacturing environment with exposure to elements such as; odor, noise, dust, heat, cold, chemicals and other elements 

• Responsible for adhering to strict safety and environmental guidelines to include wearing appropriate Personal Protective Equipment (PPE) 

• Ability to perform detailed tasks and follow standard work instructions 

• Use computers to perform tests, download information or record test data 

• Use hand tools, machine tools and various types of equipment to assemble and test products 

• Ability to work and communicate with others in a professional and effective manner, within a team-oriented environment. 

Basic Qualifications 

• High School Diploma or Equivalent Years of Work Experience 

• Ability to use hand tools, soldering iron, other industrial tools 

• Able to follow instructions and production schedules 

• Adaptable and able to act quickly when problems arise 

• Attention to detail 

• Good coordination, motor skills and dexterity 

• Applicable ADA Verbiage or Driving/Travel Requirements (percentage) 
• Ability to stand for upwards of 12 hours a day; as well as lift, carry, move packages and materials up-to-50 lbs on a regular basis; with or without special accommodations, is required 

Benefits that Benefit You

• Competitive salary and 401k with employer match
• Discretionary paid time off
• Paid parental leave for all
• Medical, Dental, Vision plans
• Fitness Programs
• Emotional & Mental Wellness support
• Learning & Development programs
• And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work