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A leading AI marketing platform is seeking a Machine Learning Engineer II to enhance its personalization capabilities. The role involves building and maintaining ML models and pipelines, working closely with product managers and senior engineers. Candidates should have a minimum of 3 years in software engineering, with at least 2 years in machine learning. The position offers a competitive salary range of $212,000 - $280,000 annually, alongside equity and benefits, in an inclusive workplace focused on collaboration and innovation.

Sr. Machine Learning Engineer, Monetization Engineering Join to apply for the Sr. Machine Learning Engineer, Monetization Engineering role at Pinterest Sr. Machine Learning Engineer, Monetization Engineering Join to apply for the Sr. Machine Learning Engineer, Monetization Engineering role at Pinterest Get AI-powered advice on this job and more exclusive features. About Pinterest Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. About Pinterest Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace the flexibility to do your best work. Creating a career you love? It's Possible. With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you'll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won't find anywhere else. Within the Monetization ML Engineering team, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. In this role, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack within Ads. What You'll Do Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas Use data driven methods and leverage the unique properties of our data to improve candidates retrieval Work in a high-impact environment with quick experimentation and product launches Keep up with industry trends in recommendation systems Leverage LLMs to enhance content understanding What We're Looking For 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning) Degree in computer science, statistics, or related field End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark) Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems Nice to have: M.S. or PhD in Machine Learning or related areas Publications at top ML conferences Expertise in scalable realtime systems that process stream data Passion for applied ML and the Pinterest product Background in computational advertising Relocation Statement: This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model. At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise. Information regarding the culture at Pinterest and benefits available for this position can be found here. US based applicants only $177,309-$310,291 USD Our Commitment To Inclusion Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support. Seniority level Seniority levelMid-Senior level Employment type Employment typeFull-time Job function Job functionEngineering and Information Technology IndustriesTechnology, Information and Internet, Software Development, and IT Services and IT Consulting Referrals increase your chances of interviewing at Pinterest by 2x Sign in to set job alerts for "Machine Learning Engineer" roles.Software Engineer III, AI/ML Recommendations, Rankings, Predictions, YouTube San Francisco, CA $130,000.00-$230,000.00 5 months ago Staff Software Engineer, AI/ML Recommendations, Rankings, Predictions, YouTubeMachine Learning Engineer (I, II, or Sr.) San Francisco, CA $140,000.00-$180,000.00 5 months ago San Francisco, CA $140,000.00-$160,000.00 5 months ago San Francisco, CA $140,000.00-$215,000.00 1 month ago Machine Learning Engineer (I, II, or Sr.)Research Engineer - Machine Learning (ML) San Francisco, CA $140,000.00-$160,000.00 4 months ago San Francisco, CA $130,000.00-$238,000.00 2 weeks ago San Francisco, CA $100,000.00-$180,000.00 1 year ago San Francisco, CA $150,000.00-$250,000.00 2 weeks ago San Francisco, CA $150,000.00-$260,000.00 4 months ago San Mateo, CA $140,000.00-$210,000.00 2 weeks ago San Francisco, CA $140,000.00-$290,000.00 7 months ago Machine Learning Engineer, GenAI Applied ML San Francisco, CA $176,000.00-$220,000.00 2 weeks ago San Francisco, CA $140,000.00-$200,000.00 3 days ago San Francisco, CA $88,000.00-$140,000.00 1 month ago San Francisco, CA $157,000.00-$193,000.00 1 day ago San Francisco, CA $100,000.00-$300,000.00 2 weeks ago Machine Learning Engineers (Open-Endedness) - Open Level San Francisco, CA $175,000.00-$250,000.00 6 days ago San Francisco, CA $175,000.00-$225,000.00 7 months ago Machine Learning Engineer, Identity Product We're unlocking community knowledge in a new way. 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San Francisco, CA; Sunnyvale, CA About the Team DashPass is DoorDash's subscription loyalty program that delivers lower delivery fees and a host of additional benefits and value to a large subscriber base of both paid and sponsored subscriptions. DashPass subscribers enjoy lower delivery fees, faster ETAs, 3rd party partnerships, and special discounts and promotions to get maximum value of their membership. Several teams are part of the DashPass org including Growth, Habituation, Member Experience, Exclusive Offers, and Partnerships. All of these teams require personalized targeting of offers and promotions to entice active Doordash consumers to sign up for DashPass and actively engage with their subscription in a personalized way, as well as reduce churn by offering personalized incentives to DashPass subscribers to keep using their subscription. We are forming a new team that will leverage AI and advanced ML to power decision making in real-time - from personalized sign up promotions to progressive reward systems, and to pre-cancel offers that retain subscribers. DashPass is continuously building new benefits and offerings to drive more value for our subscribers, and personalization is our next big bet to help efficiently grow our subscriber base to 2030 and beyond. About the Role We're looking for a Staff Machine Learning Engineer to drive the design and development of large-scale ML/optimization systems to target personalization efforts across the DashPass Subscriber journey. Responsibilities Contribute to Causal inference modeling to measure the incremental impact of DashPass Subscriber acquisition and retention strategies. Incentive optimization frameworks that personalize progressive rewards to improve spend efficiency. Budget allocation and forecasting models that identify optimal spend across acquisition, referrals, and retention. Partner closely with Product, Data Science, and Engineering teams to design experiments, model frameworks, and production ML systems that directly impact DashPass subscriber growth metrics. Provide technical mentorship and guidance to engineers and cross functional partners - leading through influence, not management. Build and deploy 0 1 ML systems that improve subscriber outcomes and marketplace health. Set best practices for model training, evaluation, deployment, and monitoring. This is a highly impactful IC role for someone who enjoys combining economic intuition, large scale ML modeling, and system design to solve complex real world optimization problems. Qualifications M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, or a related field. 8+ years of industry experience building production scale ML systems. Strong understanding of probability theory, statistics, and machine learning fundamentals. Strong programming skills in Python, Java, or C++, and experience with ML frameworks such as TensorFlow, PyTorch, or XGBoost. Interest in building and leading a new team that has broad impact across a wide range of problem spaces to support a critical business line. Proven ability to lead cross functional initiatives and drive complex technical projects end to end. Excellent communication skills - able to explain technical concepts to product, business, and engineering audiences. Experience in subscriptions growth or marketplace systems is a plus. Compensation The successful candidate's starting pay will fall within the pay range listed below and is determined based on job related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee's work location. Ranges are market dependent and may be modified in the future. In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information. Benefits DoorDash cares about you and your overall well being. That's why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family forming assistance, and a mental health program, among others. See below for paid time off details: For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year. For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week). National base pay ranges for this position within the United States, including Illinois and Colorado: $137,100 - $201,600 USD $167,800 - $246,800 USD $203,500 - $299,300 USD About DoorDash At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users-from Dashers to merchant partners to consumers. We are a technology and logistics company that started with door to door delivery, and we are looking for team members who can help us go from a company that is known for delivering food to a company that people turn to for any and all goods. DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their unique perspectives, solve new challenges, and own their careers. We're committed to supporting employees' happiness, healthiness, and overall well being by providing comprehensive benefits and perks including premium healthcare, wellness expense reimbursement, paid parental leave and more. Our Commitment to Diversity and Inclusion We're committed to growing and empowering a more inclusive community within our company, industry, and cities. That's why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel. Statement of Non Discrimination: In keeping with our beliefs and goals, no employee or applicant will face discrimination or harassment based on: race, color, ancestry, national origin, religion, age, gender, marital/domestic partner status, sexual orientation, gender identity or expression, disability status, or veteran status. Above and beyond discrimination and harassment based on "protected categories," we also strive to prevent other subtler forms of inappropriate behavior (i.e., stereotyping) from ever gaining a foothold in our office. Whether blatant or hidden, barriers to success have no place at DoorDash. We value a diverse workforce - people who identify as women, non binary or gender non conforming, LGBTQIA+, American Indian or Native Alaskan, Black or African American, Hispanic or Latinx, Native Hawaiian or Other Pacific Islander, differently abled, caretakers and parents, and veterans are strongly encouraged to apply. Thank you to the Level Playing Field Institute for this statement of non discrimination. We provide

San Francisco, CA; Sunnyvale, CA About the Team DashPass is DoorDash's subscription loyalty program that delivers lower delivery fees and a host of additional benefits and value to a large subscriber base of both paid and sponsored subscriptions. DashPass subscribers enjoy lower delivery fees, faster ETAs, 3rd party partnerships, and special discounts and promotions to get maximum value of their membership. Several teams are part of the DashPass org including Growth, Habituation, Member Experience, Exclusive Offers, and Partnerships. All of these teams require personalized targeting of offers and promotions to entice active Doordash consumers to sign up for DashPass and actively engage with their subscription in a personalized way, as well as reduce churn by offering personalized incentives to DashPass subscribers to keep using their subscription. We are forming a new team that will leverage AI and advanced ML to power decision making in real-time - from personalized sign up promotions to progressive reward systems, and to pre-cancel offers that retain subscribers. DashPass is continuously building new benefits and offerings to drive more value for our subscribers, and personalization is our next big bet to help efficiently grow our subscriber base to 2030 and beyond. About the Role We're looking for a Staff Machine Learning Engineer to drive the design and development of large-scale ML/optimization systems to target personalization efforts across the DashPass Subscriber journey. Responsibilities Contribute to Causal inference modeling to measure the incremental impact of DashPass Subscriber acquisition and retention strategies. Incentive optimization frameworks that personalize progressive rewards to improve spend efficiency. Budget allocation and forecasting models that identify optimal spend across acquisition, referrals, and retention. Partner closely with Product, Data Science, and Engineering teams to design experiments, model frameworks, and production ML systems that directly impact DashPass subscriber growth metrics. Provide technical mentorship and guidance to engineers and cross functional partners - leading through influence, not management. Build and deploy 0 1 ML systems that improve subscriber outcomes and marketplace health. Set best practices for model training, evaluation, deployment, and monitoring. This is a highly impactful IC role for someone who enjoys combining economic intuition, large scale ML modeling, and system design to solve complex real world optimization problems. Qualifications M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, or a related field. 8+ years of industry experience building production scale ML systems. Strong understanding of probability theory, statistics, and machine learning fundamentals. Strong programming skills in Python, Java, or C++, and experience with ML frameworks such as TensorFlow, PyTorch, or XGBoost. Interest in building and leading a new team that has broad impact across a wide range of problem spaces to support a critical business line. Proven ability to lead cross functional initiatives and drive complex technical projects end to end. Excellent communication skills - able to explain technical concepts to product, business, and engineering audiences. Experience in subscriptions growth or marketplace systems is a plus. Compensation The successful candidate's starting pay will fall within the pay range listed below and is determined based on job related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee's work location. Ranges are market dependent and may be modified in the future. In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information. Benefits DoorDash cares about you and your overall well being. That's why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family forming assistance, and a mental health program, among others. See below for paid time off details: For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year. For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week). National base pay ranges for this position within the United States, including Illinois and Colorado: $137,100 - $201,600 USD $167,800 - $246,800 USD $203,500 - $299,300 USD About DoorDash At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users-from Dashers to merchant partners to consumers. We are a technology and logistics company that started with door to door delivery, and we are looking for team members who can help us go from a company that is known for delivering food to a company that people turn to for any and all goods. DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their unique perspectives, solve new challenges, and own their careers. We're committed to supporting employees' happiness, healthiness, and overall well being by providing comprehensive benefits and perks including premium healthcare, wellness expense reimbursement, paid parental leave and more. Our Commitment to Diversity and Inclusion We're committed to growing and empowering a more inclusive community within our company, industry, and cities. That's why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel. Statement of Non Discrimination: In keeping with our beliefs and goals, no employee or applicant will face discrimination or harassment based on: race, color, ancestry, national origin, religion, age, gender, marital/domestic partner status, sexual orientation, gender identity or expression, disability status, or veteran status. Above and beyond discrimination and harassment based on "protected categories," we also strive to prevent other subtler forms of inappropriate behavior (i.e., stereotyping) from ever gaining a foothold in our office. Whether blatant or hidden, barriers to success have no place at DoorDash. We value a diverse workforce - people who identify as women, non binary or gender non conforming, LGBTQIA+, American Indian or Native Alaskan, Black or African American, Hispanic or Latinx, Native Hawaiian or Other Pacific Islander, differently abled, caretakers and parents, and veterans are strongly encouraged to apply. Thank you to the Level Playing Field Institute for this statement of non discrimination. We provide

Overview Ready to make a serious impact? Millions of people already rely on Calendly, and we're still in the midst of exciting product growth - it's a fantastic time to join us. Everything you'll work on here will accelerate your career to the next level. If you want to learn, grow, and do the best work of your life alongside the best people you've ever worked with, then we hope you'll consider allowing Calendly to be a part of your professional journey. About the team & opportunity What's so great about working on Calendly's Data Science & Machine Learning team? We make things possible for our customers through innovation in data, analytics and AI. Why do we need you? We are looking for a Machine Learning Engineer who will deliver business value by executing the full machine learning lifecycle hands-on, from problem discovery through model deployment and monitoring. You will report to the head of Data Science & Machine Learning and will be responsible for building and operating ML-powered features that create magical experiences for our customers. Our team: Drives business insights, strategic decision making, executive level and cross organizational business growth, and magical customer experiences for our end customers through impactful innovation. Works closely with product, design, marketing, customer success, and engineering teams to implement ML models that improve the customer journey in service to growth and efficiency (for example, understanding the relationships among customers' behavior and business performance). Has a strong product focus and passion for using machine learning to solve real world problems, and understands that being an effective MLE is about collaborating with people as much as it is about writing code. You will join a high performing AI team and be an integral part of building new, machine learning based experiences for internal and external customers alike. What you'll do On a typical day, you'll own features end to end within our ML ecosystem, with growing independence and impact. Own ML powered features from design through deployment, partnering with product, design, and engineering to scope work and define success metrics. Understand and share domain knowledge, answering domain specific questions for your product area and documenting what you learn for the team. Prioritize your work independently, balancing feature development, quality, and maintenance, and communicating tradeoffs clearly. Proactively seek and offer support to teammates pairing, reviewing, and collaborating to move projects forward. Understand and troubleshoot our deployment pipelines, including build, test, and release steps for ML services and data pipelines. Use our monitoring and observability tools to effectively triage alerts and incidents, collaborating with partners to restore service and prevent recurrence, and participate in the team's on-call rotation and incident response. Serve as a subject matter expert for the features and services you own, including their data contracts, SLAs, and dependencies. Be a frequent user of AI Tools and champion of adoption to the rest of the company. What do we need from you? 4+ years of industry experience in applied Machine Learning or closely related fields (or equivalent combination of education and experience) with a demonstrated track record of shipping and operating ML models in production. Deep and demonstrated ability to traverse the full spectrum of ML life cycle: exploratory data analysis, feature engineering, data visualization, feature and algorithm selection, model experimentation, model training and validation, model serving, monitoring and retraining Experience developing and implementing statistical and ML models to uncover patterns, trends, and predictions in areas such as revenue forecasting, churn analysis, personalization and recommendation, anomaly detection, or natural language processing. Hands-on experience implementing ML models using a managed service (for example, Vertex AI or SageMaker) for high-traffic, low-latency, large-data applications that produced tangible impact for end users. Understanding of foundation models and the open-source ecosystem, including model fine-tuning and prompt engineering for real product use cases. Strong programming (Python / Scala / Java / SQL etc) and data engineering skills Proficiency in ML frameworks such as: Keras, Tensorflow and PyTorch and ETL and ML workflow frameworks like Apache Spark, Beam, Airflow and VertexAI Experience working with time series data and related machine learning problems. Working knowledge of semantic search and embeddings Recognize when to seek assistance and willing to learn whatever is needed to get the job done; curiosity and growth mindset are essential. You have strong verbal and written communication skills. Ability to communicate complex technical concepts to both technical and business stakeholders. You are comfortable working remotely and with enabling tools like Slack, Confluence, etc. Authorized to work lawfully in the United States of America as Calendly does not engage in immigration sponsorship at this time What's in it for you? Ready to make a serious impact? Millions of people already rely on Calendly's products, and we're still in the midst of our growth curve - it's a fantastic time to join us. Everything you'll work on here will accelerate your career to the next level. If you want to learn, grow, and do the best work of your life alongside the best people you've ever worked with, then we hope you'll consider allowing Calendly to be a part of your professional journey. Our Hiring Process: We aim to provide an inclusive and equitable candidate experience to everyone who expresses interest in working at Calendly. To learn more about our hiring process, please visit our careers page at . Once selected for an opportunity, the recruiter assigned to the role will keep you informed every step of the way. Have questions? Let your recruiter know! Want to share your experience? We are passionately committed to improving and building on our process, and we consider feedback a gift. If you are an individual with a disability and would like to request a reasonable accommodation as part of the application or recruiting process, please contact us at . Calendly is registered as an employer in many, but not all, states. If you are located in Alaska, Alabama, Delaware, Hawaii, Idaho, Montana, North Dakota, South Dakota, Nebraska, Iowa, West Virginia, and Rhode Island, you will not be eligible for employment. Note that all individual roles will specify location eligibility. All candidates can find our Candidate Privacy Statement here Candidates residing in California may visit our Notice at Collection for California Candidates here: Notice at Collection This role may require occasional travel for company events, team collaboration, or offsites.

Overview Join to apply for the Machine Learning Engineer role at Scribd, Inc.. About The Company At Scribd (pronounced "scribbed"), our mission is to spark human curiosity. Join our team as we create a world of stories and knowledge, democratize the exchange of ideas and information, and empower collective expertise through our three products: Everand, Scribd, and Slideshare. We support a culture where our employees can be real and be bold; where we debate and commit as we embrace plot twists; and where every employee is empowered to take action as we prioritize the customer. When it comes to workplace structure, we believe in balancing individual flexibility and community connections. It's through our flexible work benefit, Scribd Flex, that employees - in partnership with their manager - can choose the daily work-style that best suits their individual needs. A key tenet of Scribd Flex is our prioritization of intentional in-person moments to build collaboration, culture, and connection. For this reason, occasional in-person attendance is required for all Scribd employees, regardless of their location. So what are we looking for in new team members? Well, we hire for "GRIT". The textbook definition of GRIT is demonstrating the intersection of passion and perseverance towards long term goals. At Scribd, we are inspired by the potential that this can unlock, and ask each of our employees to pursue a GRIT-ty approach to their work. In a tactical sense, GRIT is also a handy acronym that outlines the standards we hold ourselves and each other to. Here's what that means for you: we're looking for someone who showcases the ability to set and achieve Goals, achieve Results within their job responsibilities, contribute Innovative ideas and solutions, and positively influence the broader Team through collaboration and attitude. About The Team Our Machine Learning team builds both the platform and product applications that power personalized discovery, recommendations, and generative AI features across Scribd, Slideshare, and Everand. ML teams works on the Orion ML Platform - providing core ML infrastructure, including a feature store, model registry, model inference systems, and embedding-based retrieval (EBR). MLE team also works closely with Product team - delivering zero-to-one integrations of ML into user-facing features like recommendations, near real-time personalization, and AskAI LLM-powered experiences. Role Overview We are seeking a Machine Learning Engineer II to help design, build, and optimize high-impact ML systems that serve millions of users in near real time. You will work on projects that span from improving our core ML platform to integrating models directly into the product experience. Tech Stack Our Machine Learning team uses a range of technologies to build and operate large-scale ML systems. Our regular toolkit includes: Languages: Python, Golang, Scala, Ruby on Rails Orchestration & Pipelines: Airflow, Databricks, Spark ML & AI: AWS SageMaker, embedding-based retrieval (Weaviate), feature store, model registry, model serving platforms, LLM providers like OpenAI, Anthropic, Gemini, etc. APIs & Integration: HTTP APIs, gRPC Infrastructure & Cloud: AWS (Lambda, ECS, EKS, SQS, ElastiCache, CloudWatch), Datadog, Terraform Key Responsibilities Design, build, and optimize ML pipelines, including data ingestion, feature engineering, training, and deployment for large-scale, real-time systems. Improve and extend core ML Platform capabilities such as the feature store, model registry, and embedding-based retrieval services. Collaborate with product software engineers to integrate ML models into user-facing features like recommendations, personalization, and AskAI. Conduct model experimentation, A/B testing, and performance analysis to guide production deployment. Optimize and refactor existing systems for performance, scalability, and reliability. Ensure data accuracy, integrity, and quality through automated validation and monitoring. Participate in code reviews and uphold engineering best practices. Manage and maintain ML infrastructure in cloud environments, including deployment pipelines, security, and monitoring. Qualifications Must Have 3+ years of experience as a professional software or machine learning engineer. Proficiency in at least one key programming language (preferably Python or Golang; Scala or Ruby also considered). Hands-on experience building ML pipelines and working with distributed data processing frameworks like Apache Spark, Databricks, or similar. Experience working with systems at scale and deploying to production environments. Cloud experience (AWS, Azure, or GCP), including building, deploying, and optimizing solutions with ECS, EKS, or AWS Lambda. Strong understanding of ML model trade-offs, scaling considerations, and performance optimization. Bachelor's in Computer Science or equivalent professional experience. Nice to Have Experience with embedding-based retrieval, recommendation systems, ranking models, or large language model integration. Experience with feature stores, model serving & monitoring platforms, and experimentation systems. Familiarity with large-scale system design for ML. Compensation and Benefits At Scribd, your base pay is one part of your total compensation package and is determined within a range. Our pay ranges are based on the local cost of labor benchmarks for each specific role, level, and geographic location. San Francisco is our highest geographic market in the United States. In the state of California, the reasonably expected salary range is between $126,000 minimum salary in our lowest geographic market within California to $196,000 maximum salary in our highest geographic market within California . In the United States, outside of California, the reasonably expected salary range is between $T103,500 minimum salary in our lowest US geographic market outside of California to $186,500 maximum salary in our highest US geographic market outside of California . In Canada, the reasonably expected salary range is between $131,500 CAD minimum salary in our lowest geographic market to $174,500 CAD maximum salary in our highest geographic market . We carefully consider a wide range of factors when determining compensation, including but not limited to experience; job-related skill sets; relevant education or training; and other business and organizational needs. The salary range listed is for the level at which this job has been scoped. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package. Working at Scribd Are you currently based in a location where Scribd is able to employ you? United States: Atlanta, Austin, Boston, Dallas, Denver, Chicago, Houston, Jacksonville, Los Angeles, Miami, New York City, Phoenix, Portland, Sacramento, Salt Lake City, San Diego, San Francisco, Seattle, Washington D.C. Canada: Ottawa, Toronto, Vancouver Mexico: Mexico City Benefits, Perks, And Wellbeing At Scribd Benefits/perks listed may vary depending on the nature of your employment with Scribd and the geographical location where you work. Healthcare Insurance Coverage (Medical/Dental/Vision): 100% paid for employees 12 weeks paid parental leave Short-term/long-term disability plans 401k/RSP matching Onboarding stipend for home office peripherals + accessories Learning & Development allowance Learning & Development programs Quarterly stipend for Wellness, WiFi, etc. Mental Health support & resources Free subscription to the Scribd Inc. suite of products Referral Bonuses Book Benefit Sabbaticals Company-wide events Team engagement budgets Vacation & Personal Days Paid Holidays (+ winter break) Flexible Sick Time Volunteer Day Company-wide Employee Resource Groups and programs that foster an inclusive and diverse workplace. Access to AI Tools: We provide free access to best-in-class AI tools, empowering you to boost productivity, streamline workflows, and accelerate bold innovation. Want to learn more about life at Scribd? We want our interview process to be accessible to everyone. You can inform us of any reasonable adjustments we can make to better accommodate your needs by emailing about the need for adjustments at any point in the interview process. Scribd is committed to equal employment opportunity regardless of race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. We encourage people of all backgrounds to apply, and believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful. Position Details Seniority level: Mid-Senior level Employment type: Full-time Job function: Engineering and Information Technology Industries: Software Development