As a Senior Machine Learning Engineer on the Ranking team, you will be responsible for enhancing the quality of our ranking systems, ensuring that search, browse, and autocomplete experiences are highly relevant, personalized, and diverse.

Responsibilities

• Design and develop ML-based ranking solutions to drive improvements in key business metrics such as conversion, engagement, and user satisfaction.
• Analyze ranking performance and identify gaps in search, browse, and autocomplete experiences, focusing on relevance, personalization, attractiveness, diversification, and other quality signals.
• Innovate and optimize ranking algorithms to advance the ranking pipeline, improve ranking quality, and meet evolving business needs.

Requirements

• At least 4 years of experience with Python for machine learning and backend development.
• At least 4 years of experience developing, deploying, and maintaining machine learning models with a strong focus on ranking systems for search, recommendations, or similar applications.
• Experience in large-scale ML model training, evaluation, and optimization, with a focus on real-time inference and serving.
• Experience with big data frameworks such as Spark for processing large datasets and integrating them into ML pipelines.
• Proficiency in using tools like SQL, PySpark, Pandas, and other frameworks to extract, manipulate, and analyze data.
• Experience with data pipeline orchestration tools like Airflow or Luigi to manage and automate workflows for ML training and signal delivery.

Benefits

• Unlimited vacation time.
• Fully remote team.
• Work from home stipend.
• Apple laptops provided for new employees.
• Training and development budget for every employee.
• Maternity & Paternity leave for qualified employees.
• Base salary: $80k–$120k USD, depending on knowledge, skills, experience, and interview results.
• Stock options.
• Regular team offsites to connect and collaborate.

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Our team works on high-impact systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes. You'll work on complex, real-world ML problems at massive scale, and contribute to technical strategy, architecture, and long-term ML roadmap.

Responsibilities:

• 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

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

Pay Transparency:

This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base salary range for this position is: $185,800-$260,100 USD

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Your responsibilities will include:

• Designing, building, and deploying production-grade machine learning models and systems at scale
• Owning the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring
• Building scalable data and model pipelines with strong reliability, observability, and automated retraining
• Working with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems
• Partnering cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions

You'll work on a wide range of high-impact problems across the Reddit ecosystem, including recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, and multimodal embedding systems.

To be successful in this role, you'll need:

• 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

Preferred qualifications include 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, and experience working with real-time systems and low-latency production environments.

At Reddit, we're committed to building a workforce representative of the diverse communities we serve. We're proud to be an equal opportunity employer and are committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures.

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A typical day for this role will involve envisioning, championing, and supporting the development of novel ML systems, product integrations, and performance optimizations to solve real-world problems. You will lead, mentor, challenge, and grow enthusiastic, collaborative software engineers and applied scientists across the organization. You will also raise the AI/ML skillset within the organization, which requires a passion for teaching and mentoring.

To be successful in this role, you will need 12+ years of software engineering experience, with 2+ years of experience in a Principal or Senior Staff Engineer role having ownership responsibility over large-scale software systems. You should have a background in the design and development of scalable AI and ML systems and services, and a deep passion for building ML-powered products.

As a Senior Staff Machine Learning Engineer, you will be an inspiring colleague, a coach, and mentor with experience owning and fostering engineering maturity in multiple organizations. You will be a builder, and implementer, who seeks out high-impact work, and who is proactive, curious, and an excellent communicator.

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Our team is responsible for building systems that operate at internet scale and directly influence user experience, advertiser value, and business outcomes. You will work on high-impact systems that improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems.

As a Senior Machine Learning Engineer, you will:

• 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

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

Pay Transparency:

This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/. To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is $216,700-$303,400 USD

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This team's work touches every single booking decision on a platform that facilitates hundreds of millions of trips and an incredibly diverse global inventory. You will ship and iterate on AI-powered features that help guests make more confident booking decisions , synthesizing signals from reviews, ratings, and listing data into quality information that is clear, personalized, and trustworthy.

This means working hands-on with Data Science to evaluate model performance and translate outputs into better product decisions, not just defining requirements and handing them off. This role requires close partnership with the Policy, Privacy, and Legal teams , particularly on review integrity, AI-generated content, and trust-related guest-facing features.

You will work especially closely with the quality data platform team to generate and consume accurate quality signals that foster a trusted marketplace, as well as across Design, Engineering, and Data Science to ship and iterate at scale.

This is a critical role that spans the end-to-end guest experience around listing quality information, and the features you build will be part of the experience for every guest who considers booking on Airbnb.

As a Product Manager, you will:

• Develop and execute the product roadmap for Trip Quality Merchandising and AI, with a focus on shipping AI-powered features that improve how guests evaluate listing quality.
• Define product requirements for generative AI features (e.g. listing summaries, quality highlights) and ML ranking systems, including evaluation criteria, guardrails, and iteration plans.
• Partner with Data Science to assess model performance , understanding where outputs are accurate and trustworthy, and where they fall short , and translate those assessments into concrete product improvements.
• Craft the product narrative that inspires teams, leadership, and the company and builds alignment on the quality merchandising strategy.
• Partner with design, engineering, and customer support to deliver features that improve both guest and host experiences.
• Collaborate closely with our Policy, Privacy, and Legal teams on topics that are essential to making Airbnb one of the most trusted marketplaces in the world.

You will need to have:

• 10+ years of product management experience.
• Hands-on track record shipping AI/ML-powered features on consumer products , including generative AI features (LLM-based summarization, content generation) and ML ranking or personalization systems , with direct involvement in defining evaluation criteria and improving model outputs.
• Expert ability to use data and business analysis to inform product strategy and drive decisions.
• Domain familiarity with marketplace trust/quality, search/ranking/relevance, or content/feedback systems is strongly preferred.
• Experience creating product messaging and delivering to customers.
• Demonstrated track record of building cross-functional and executive leadership alignment.
• Experience working on consumer products with marketplace dynamics on a global scale.
• Entrepreneurial track record of taking an idea to reality.
• Excited to lead cross-functional execution, from strategy through shipped product in a fast-paced environment.
• Desire to do individual contributor product management work.
• Excellent written and verbal communication; adept at simplifying complex AI/ML and data concepts for diverse audiences.

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Microsoft AI are looking for a talented Member of Technical Staff - Principal Backend Engineer, Copilot Memory and Personalization at their Mountain View office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.

About the Role

As a Principal Backend Engineer, you will design and evolve large-scale data architectures that support Copilot memory and personalization, spanning batch, streaming, and serving paths. You will build and operate high-quality personalization and memory data pipelines, including signal ingestion, normalization, enrichment, aggregation, memory generation, and full lifecycle management. You will enable memory and personalization features by exposing well-designed datasets, APIs, and feature interfaces for downstream product and ML consumers. You will work closely with PMs, applied ML, and product engineering to translate product intent into robust data systems and measurable outcomes. You will act as a technical leader for memory and personalization data systems, influencing architecture and standards across multiple teams. You will lead design reviews, unblock complex technical problems, and make principled trade-offs in ambiguous spaces.

Accountabilities

• Design and evolve large-scale data architectures that support Copilot memory and personalization, spanning batch, streaming, and serving paths.
• Build and operate high-quality personalization and memory data pipelines, including signal ingestion, normalization, enrichment, aggregation, memory generation, and full lifecycle management.

The Candidate we're looking for

Experience:

• 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.

Technical skills:

• Experience building and deploying machine learning or large language model (LLM) applications at scale.
• Experience designing and implementing large-scale embedding, retrieval, and ranking systems.

Personal attributes:

• Thrive in a fast-paced, collaborative environment and are comfortable making progress in ambiguity.

Benefits

• Software Engineering IC5 – The typical base pay range for this role across the U.S. is USD $139,900 – $274,800 per year.
• Software Engineering IC6 – The typical base pay range for this role across the U.S. is USD $163,000 – $296,400 per year.

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Microsoft AI are looking for a talented Member of Technical Staff - Principal Platform Engineer, Copilot Memory and Personalization at their Mountain View office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.

About the Role

As a Principal Platform Engineer, you will design and build large-scale Copilot memory and personalization systems leveraging search, embeddings, retrieval, ranking, and Retrieval-Augmented Generation (RAG). You will apply subject-matter expertise in cross-product features, collaborating with appropriate stakeholders to drive project plans, release plans, and deliverables across multiple groups. You will hold accountability as a Designated Responsible Individual (DRI), mentoring engineers across products/solutions, working on-call to monitor system/product/service for degradation, downtime, or interruptions.

Accountabilities

• Design and build large-scale Copilot memory and personalization systems leveraging search, embeddings, retrieval, ranking, and Retrieval-Augmented Generation (RAG).
• Apply subject-matter expertise in cross-product features, collaborating with appropriate stakeholders to drive project plans, release plans, and deliverables across multiple groups.

The Candidate we're looking for

Experience:

• Bachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.

Technical skills:

• Experience building and deploying machine learning or large language model (LLM) applications at scale.
• Experience designing and implementing large-scale embedding, retrieval, and ranking systems.

Personal attributes:

• Thrive in a fast-paced, collaborative environment and are comfortable making progress in ambiguity.

Benefits

• Software Engineering IC5 – The typical base pay range for this role across the U.S. is USD $139,900 – $274,800 per year.
• Software Engineering IC6 – The typical base pay range for this role across the U.S. is USD $163,000 – $296,400 per year.

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