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largest sources of information. For more information, visit www.redditinc.com.

Job Duties: Design, develop, and train advanced machine learning models, including deep neural networks, transformer-based

architectures, and reinforcement learning systems, to power large-scale online advertising ranking and optimization platforms.

Lead the development and optimization of complex feature representations, including high-dimensional embeddings, contextual and

temporal signals, and cross-session user behavior modeling. Drive end-to-end model lifecycle execution, including system

architecture design, large-scale experimentation, model deployment, performance monitoring, and iterative infrastructure

improvements in production environments. Collaborate closely with product, data, and infrastructure engineering teams to translate

business objectives into scalable, statistically rigorous modeling solutions. Conduct advanced experiment design and causal

analysis to evaluate model impact and inform strategic decisions. Provide technical leadership and mentorship to machine learning

engineers and contribute to organization-wide modeling standards, best practices, and long-term technical strategy. Shape the

long-term modeling vision across multiple advertising domains, including conversion optimization, application advertising,

shopping, and brand advertising. Full-time telecommuting is an option.

Requirements: Master’s degree in Computer Science, Engineering (any field) or related quantitative discipline and (3) three years

of experience in the job offered or related occupation.

Special Skill Requirements: 1) Python, Java, and Scala; 2) C++, Go, or Rust; 3) major machine learning frameworks and libraries;

4) applied statistics, hypothesis testing and experiment design for online machine learning systems; 5) large-scale data

processing and analytics frameworks; 6) deployment and operation of production systems in containerized and distributed

environments; 7) Designing and training advanced models, including deep neural networks, transformer-based architectures, and

reinforcement learning models; 8) marketplace dynamics, such as real-time bidding (RTB) or pacing control systems; 9) developing

and optimizing online advertising systems, including ad ranking, targeting, and market place; 10) providing technical leadership,

mentorship, or guidance to other machine learning engineers. Any suitable combination of education, training and/or experience is

acceptable. Full-time telecommuting is an option.

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

Submit a resume with references using the apply button on this posting or by email at: applicationsreview@reddit.com at Req.#

1016.83.2.

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

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To provide greater transparency to candidates, we share base pay 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.

The base pay range for this position is: $230,000.00 - $322,000.00 USD

#LI-DNI

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Roll

Staff Machine Learning Engineer

Kategori

Data/IT

Plats

San Francisco

Publicerad

13 juli

Sista ansökningsdag

16 augusti

Källa

Arbetsgivarens hemsida

Liknande jobb

Staff Machine Learning Engineer

Databricks•San Francisco

P-1504 The Applied AI team at Databricks sits at the forefront of advancing GenAI-powered products. Over the past years, we’ve launched Databricks Assistant, AI/BI Genie, and Agent Bricks working with product teams, and made significant strides in LLM quality for these products. These products are used by 100s of thousands of Databricks users every day. We are tackling challenging problems like code suggestion, error detection and correction, text-to-sql generation, automatic pipeline generation, knowledge QA and many others. As our GenAI products continue to evolve, we are seeking multiple GenAI Engineers from junior levels to more senior levels to drive the next phase of development. In 2025, we will focus on enhancing LLM quality, expanding GenAI capabilities across Databricks products, and strengthening our platform architecture to enable seamless AI interactions at scale. Key Responsibilities * Shape the direction of our applied AI areas and intelligence features in our products. Drive the development and deployment of state-of-the-art AI models and systems that directly impact the capabilities and performance of Databricks' products and services (e.g., Databricks Assistant and AI/BI Genie). * Develop novel data collection, fine-tuning, and LLM technologies that achieve optimal performance on specific tasks and domains. * Design and implement ML pipelines for data preprocessing, feature engineering, model training, hyperparameter tuning, and model evaluation, enabling rapid experimentation and iteration. * Work closely with cross-functional teams, including AI researchers, ML engineers, and product teams, to deliver impactful AI solutions that enhance user productivity and satisfaction. * Build scalable, reusable backend systems to support GenAI products across the company. Develop robust logging, telemetry, and evaluation harnesses to ensure reliable model performance. What We’re Looking For * 2-8 years of machine learning engineering experience in high-velocity, high-growth companies. Alternatively, a strong background in relevant ML research in academia will be considered as an equivalent qualification. * Strong track record of working with language modeling technologies. This could include the following: Developing generative and embedding techniques, modern model architectures, fine tuning / pre-training datasets, and evaluation benchmarks. * Proficiency in Python, TensorFlow/PyTorch, and scalable ML architectures. * Ability to drive end-to-end model development, from research and prototyping to deployment and monitoring. * Strong analytical and problem-solving skills, with a passion for improving AI-driven user experiences. * Strong coding and software engineering skills, and familiarity with software engineering principles around testing, code reviews and deployment. * Experience with LLM fine-tuning, prompt engineering, and retrieval-augmented generation (RAG) is a bonus. Why Join Us? At Databricks, we are building state-of-the-art AI solutions that redefine how users interact with data and our products. You’ll have the opportunity to shape the future of AI-driven products at Databricks, work with cutting-edge models, and collaborate with a world-class team of AI and ML experts. If you're excited about pushing the boundaries of AI in real-world applications, we’d love to hear from you! Please note we are open to employees working from our Mountain View, CA office for this position. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here. Local Pay Range $190,000—$285,000 USD About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Sista ansökan: 16 aug.Publicerad: 17 juli

Staff Machine Learning Engineer

Taskrabbit•San Francisco

ABOUT TASKRABBIT: Taskrabbit is a marketplace platform that conveniently connects people with Taskers to handle everyday home to-do’s, such as furniture assembly, handyman work, moving help, and much more. At Taskrabbit, we want to transform lives one task at a time. As a company we celebrate innovation, inclusion and hard work. Our culture is collaborative, pragmatic, and fast-paced. We’re looking for talented, entrepreneurially minded and data-driven people who also have a passion for helping people do what they love. Together with IKEA, we’re creating more opportunities for people to earn a consistent, meaningful income on their own terms by building lasting relationships with clients in communities around the world. Taskrabbit is a hybrid company with employees distributed across the US and EU and a Built In — Best Places to Work (2022, 2023, 2024, 2025) continually ranked across multiple national and regional categories. Join us at Taskrabbit, where your work will be meaningful, your ideas valued, and your potential unleashed! Prior to applying please note: * We are currently unable to provide visa sponsorship for this position (including H-1B, OPT, or other employment-based visas). Candidates must be legally authorized to work in the United States without employer sponsorship now or in the future. * This role is hybrid requiring 2 days in office at our San Francisco hub every Tuesday & Wednesday (located at 130 Sutter St). ABOUT THE ROLE Machine Learning is a cornerstone at Taskrabbit, and we’re looking for a Staff Machine Learning Engineer to take technical ownership of our core ranking system. Every job request on the platform flows through it, making this one of the most consequential ML systems we run. This is a hands-on technical leadership role. You’ll operate as the primary architect and engineer for the ranking system — defining the system direction, driving the roadmap, solving the hardest problems, and creating leverage for the engineers around you. You’ll also serve as the primary technical interface for Product, Data Science, Risk, and Commerce on all things matching. What we need is a single technical owner who can hold the architecture, translate strategy into engineering action, and mentor the team as the system scales. WHAT YOU’LL WORK ON: * Ranking System Ownership: Own the architecture, model design, experiment strategy, and production reliability of the core ranking system end-to-end. You are the system’s primary technical decision-maker. * Cross-functional Technical Leadership: Serve as the primary technical point of contact for Product, Data Science, Risk, and Commerce on matching and ranking questions. Actively participate in architecture reviews; give clear, well-reasoned recommendations and convince stakeholders on technical tradeoffs. * Model Reliability: Build automated retraining pipelines, rollback capability, and skew detection — the foundations that enable safe experimentation at speed and eliminate silent model drift. * Ranking Quality & Debiasing: Address position bias and other systemic biases in the ranking pipeline to produce cleaner training data and unlock downstream experimentation. * Client Intent Signals: Leverage filter-based signals from high-booking user cohorts (69–72% higher booking rate) to drive direct conversion lift from untapped behavioral data. * Personalization: Surface return-client signals, prior Tasker preferences, and preference modeling to improve IAR for the highest-value booking segment. * Platform Thinking: Identify where ML can add value beyond the ranking system and scope those opportunities for the broader team. Make build-vs-buy recommendations and contribute to long-term ML architecture at Taskrabbit. * Team Development & Thought Leadership: Mentor the junior engineer, elevate seniors through code and design reviews, and raise the technical bar across the team. Beyond day-to-day guidance, you bring a transformational perspective — introducing new methodologies, challenging existing patterns, and shaping how the team thinks about ML problems. You’re a sought-out guide and a catalyst for how the team evolves. WHO YOU ARE: We welcome applicants from a variety of backgrounds and experiences. Below gives you a sense of how we’re thinking about what you’ll need to be successful in the role. * BS, MS, or PhD in Computer Science, Statistics, Operations Research, or a related quantitative field. * 8+ years of industry experience building and deploying production-grade ML systems, with a track record of owning a system end-to-end — not just contributing to one. * Deep expertise in ranking, recommender systems, or two-sided marketplace ML. Experience with debiasing, A/B experimentation at scale, and the subtleties of feedback loops in production systems. * You think architecturally. You can hold the full picture of a complex system — data pipelines, feature stores, training infrastructure, serving, monitoring — and make principled decisions about how they fit together. * You write and review code at a high standard. Your code reviews are insightful and educational; your implementations set the bar for quality and maintainability on the team. * You can do critical R&D. When a problem is novel and the solution is unclear, you have the depth to explore it systematically and the judgment to know when to go deeper vs. ship. * You have a vision for how state-of-the-art advances in ML — from large language models to modern deep ranking architectures — can transform what a traditional ranking system is capable of, and the judgment to chart a practical path toward that future. * You’re an effective cross-functional partner. You communicate technical tradeoffs clearly to non-technical stakeholders, proactively identify upstream and downstream implications, and build trust with partners through reliability and transparency. * You motivate and elevate the people around you. You give kind, direct feedback, mentor with generosity, and help others grow without creating dependency. * Strong proficiency in Python and SQL. Hands-on experience with ML libraries (PyTorch, TensorFlow, scikit-learn, LightGBM/XGBoost) and modern data infrastructure (Kafka, Airflow, Snowflake/BigQuery, Docker/Kubernetes). Familiarity with dbt is a plus. * Experience with Infrastructure as Code (Terraform) and CI/CD pipelines. * Proficiency in using AI coding tools (e.g., Claude Code, Augment, or similar) across the full software development lifecycle — from designing and generating code to testing, monitoring, and releasing software. COMPENSATION & BENEFITS: At Taskrabbit, our approach to compensation is designed to be competitive, transparent, and equitable. Total compensation consists of base pay + bonus + benefits + perks. The base pay range for this position is $170,000 - $225,000. This range is representative of base pay only, and does not include any other total cash compensation amounts, such as company bonus or benefits. Final offer amounts may vary from the amounts listed above and will be determined by factors including, but not limited to, relevant experience, qualifications, geography, and level. YOU’LL LOVE WORKING HERE BECAUSE: * Taskrabbit is a Hybrid Company. We value flexibility and choice but also stay committed to regular in-person connection. * The People. You will be surrounded by some of the most talented, supportive, smart, and kind leaders and teams -- people you can be proud to work with! * The Diverse Culture. We believe that we make better decisions when our workforce reflects the diversity of the communities in which we operate. Women make up half of our leadership team and our diversity representation is above that of the tech industry average. * The Perks. Taskrabbit offers our employees with employer-paid health insurance and a 401k match with immediate vesting for our US based employees. We offer all of our global employees generous and flexible time off with 2 company-wide closure weeks, Taskrabbit product stipends, wellness + productivity + education stipends, IKEA discounts, reproductive health support, and more. Benefits vary by country of employment. TASKRABBIT’S COMMITMENT TO DIVERSITY AND INCLUSION: An Active Commitment to Equity within our Company and Platform. We are an inclusive community where all who share our mission and values belong. Our diverse team represents the communities we serve, breaking down systemic barriers, and transforming lives- one action at a time. Taskrabbit is an equal opportunity employer and values diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, ancestry, citizenship, sex, gender, gender identity, sexual orientation, age, marital status, military/veteran status, or disability status. Taskrabbit is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Taskrabbit will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law.

Sista ansökan: 16 aug.Publicerad: 25 juni

PythonDockerKubernetes

Staff Machine Learning Engineer, Community Support Engineering

Airbnb•San Francisco

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: Machine Learning and Artificial Intelligence are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb. The Community Support Products (CSP) Machine Learning team is the core team responsible for driving CSxAI (Customer Support x Artificial Intelligence) initiatives by adopting the Generative AI technologies to enable an intelligent, scalable and exceptional service experience. The team develops and enhances various AI models, ML services and tools including LLM fine-tuning and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb. The richness of Airbnb's data, the complexity of its marketplace and the variety innate in our product mean that we need to operate at the state of the art of AI practice. We are committed to investing in long term innovation to solve the complex problems we face, and to do that we need the very best experts in ML and AI to join us. The Difference You Will Make: We believe our current customer experiences in these domains are only scratching the surface of the innovations that are possible, and that science is at the heart of delivering a step-function change for our Guest and and Host on Airbnb. You will build and leverage cutting edge AI technologies to transform Airbnb’s customer service by delivering personalized, easy-to-use and proactive customer service experience. Many of the initiatives you’ll tackle are in their early conceptual stages. You will have the opportunity to shape these ideas from inception to production, turning visionary concepts into impactful realities. A Typical Day: * Envision, champion, and support the development of novel ML systems, product integrations, and performance optimizations to solve real-world problems * Work cross-functionally with product, design, and other engineering counterparts to design and build efficient AI solutions for Airbnb CS products * Learn and share the latest AI/ML technologies with the team. Your Expertise: * PhD/Master’s degree, preferably in CS, or equivalent experience * 9+ years of ML engineering experience, with ownership responsibility over large-scale software systems * Background in the design and development of AI and ML systems and services, and a deep passion for building efficient and scalable ML-powered products * Experience with LLM driven chatbot and Agentic AI products would be a big plus * Excellent communication skills and the ability to work well within a team and with teams across the engineering, product & design organizations Your Location: This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list. If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from. Our Commitment To Inclusion & Belonging: Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply. We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process. We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application. How We'll Take Care of You: Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits. Pay Range $212,000—$260,000 USD

Sista ansökan: 16 aug.Publicerad: 8 juli