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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.</p>\n<p>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. 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This is a high-impact, cross-functional role where you will shape both foundational systems and user-facing capabilities.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Design, build, and productionize ML models for Search, Discovery, Ranking, Retrieval-Augmented Generation (RAG), and generative AI features.</li>\n<li>Build and maintain scalable data pipelines to collect high-quality training and evaluation datasets, including annotation systems and human-in-the-loop workflows.</li>\n<li>Collaborate with AI researchers to iterate on datasets, evaluation metrics, and model architectures to improve quality and relevance.</li>\n<li>Work with product engineers to define and deliver impactful AI features across Figma&#39;s platform.</li>\n<li>Partner with infrastructure engineers to develop and optimize systems for training, inference, monitoring, and deployment.</li>\n<li>Explore new ideas at the edge of what&#39;s technically possible and help shape the long-term AI vision at Figma.</li>\n</ul>\n<p>Requirements include:</p>\n<ul>\n<li>5+ years of industry experience in software engineering, with 3+ years focused on applied machine learning or AI.</li>\n<li>Strong experience with end-to-end ML model development, including training, evaluation, deployment, and monitoring.</li>\n<li>Proficiency in Python and familiarity with ML libraries like PyTorch, TensorFlow, Scikit-learn, Spark MLlib, or XGBoost.</li>\n<li>Experience designing and building scalable data and annotation pipelines, as well as evaluation systems for AI model quality.</li>\n<li>Experience mentoring or leading others and contributing to a culture of technical excellence and innovation.</li>\n</ul>\n<p>Preferred qualifications include:</p>\n<ul>\n<li>Familiarity with search relevance, ranking, NLP, or RAG systems.</li>\n<li>Experience with AI infrastructure and MLOps, including observability, CI/CD, and automation for ML workflows.</li>\n<li>Experience working on creative or design-focused ML applications.</li>\n<li>Knowledge of additional languages such as C++ or Go is a plus, but not required.</li>\n<li>A product mindset with the ability to tie technical work to user outcomes and business impact.</li>\n<li>Strong collaboration and communication skills, especially when working across functions (engineering, product, research).</li>\n</ul>\n<p>At Figma, one of our values is Grow as you go. 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In this role, you’ll collaborate with engineering teams to ensure smooth onboarding and adoption, act as a trusted advisor on best practices, and represent the voice of the customer internally.</p>\n<p>You will partner directly with leading AI teams to optimize workflows, share technical expertise, and influence our product roadmap based on real-world customer feedback.</p>\n<p>This is an ideal opportunity for ML practitioners who are customer-focused and eager to work with top AI companies globally.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Collaborate with engineering teams to ensure smooth onboarding and adoption of Weights &amp; Biases</li>\n<li>Act as a trusted advisor on best practices for implementing and scaling ML pipelines and agentic workflows</li>\n<li>Represent the voice of the customer internally and influence our product roadmap based on real-world customer feedback</li>\n<li>Partner directly with leading AI teams to optimize workflows and share technical expertise</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>3–5 years of relevant experience in a similar role</li>\n<li>Strong programming proficiency in Python</li>\n<li>Hands-on experience enabling production-grade ML systems, with a focus on training and inference pipelines, experiment tracking, deployment patterns, and observability using deep learning frameworks (TensorFlow/Keras, PyTorch/PyTorch Lightning) and MLOps tooling (e.g. Airflow, Kubeflow, Ray, TensorRT)</li>\n<li>Familiarity with cloud platforms (AWS, GCP, Azure)</li>\n<li>Experience with GenAI/LLMs and related tools (e.g. LangChain/LangGraph, HuggingFace Transformers, Pinecone, Weaviate)</li>\n<li>Strong experience with Linux/Unix</li>\n<li>Excellent communication and presentation skills, both written and verbal</li>\n<li>Ability to break down and solve complex problems through customer consultation and execution</li>\n</ul>\n<p><strong>Preferred</strong></p>\n<ul>\n<li>Background in robotics</li>\n<li>TypeScript experience</li>\n<li>Proficiency with Fastai, scikit-learn, XGBoost, or LightGBM</li>\n<li>Background in data engineering, MLOps, or LLMOps, with tools such as Docker and Kubernetes</li>\n<li>Familiarity with data pipeline tools</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_ca21d379-481","directApply":true,"hiringOrganization":{"@type":"Organization","name":"CoreWeave","sameAs":"https://www.coreweave.com","logo":"https://logos.yubhub.co/coreweave.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/coreweave/jobs/4651106006","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$165,000 to $242,000","x-skills-required":["Python","ML systems","deep learning frameworks","MLOps tooling","cloud platforms","GenAI/LLMs","Linux/Unix","communication and presentation skills"],"x-skills-preferred":["robotics","TypeScript","Fastai","scikit-learn","XGBoost","LightGBM","data engineering","Docker","Kubernetes"],"datePosted":"2026-04-18T15:50:58.312Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Livingston, NJ / New York, NY / Philadelphia, PA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, ML systems, deep learning frameworks, MLOps tooling, cloud platforms, GenAI/LLMs, Linux/Unix, communication and presentation skills, robotics, TypeScript, Fastai, scikit-learn, XGBoost, LightGBM, data engineering, Docker, Kubernetes","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":165000,"maxValue":242000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_fc38e24f-97e"},"title":"Senior Machine Learning Engineer","description":"<p>We&#39;re looking for a Senior Machine Learning Engineer to join our Ads Engineering team. As a key member of our team, you will design and build production ML systems that power core experiences across the platform, including personalized recommendations, search, and ranking systems, intelligent advertising systems, and large-scale machine learning pipelines.</p>\n<p>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.</p>\n<p>As a Senior Machine Learning Engineer, you will:</p>\n<ul>\n<li>Design, build, and deploy production-grade machine learning models and systems at scale</li>\n<li>Own the full ML lifecycle: from problem definition and feature engineering to training, evaluation, deployment, and monitoring</li>\n<li>Build scalable data and model pipelines with strong reliability, observability, and automated retraining</li>\n<li>Work with large-scale datasets to improve ranking, recommendations, search relevance, prediction, content/user understanding, and optimization systems</li>\n<li>Partner cross-functionally with Product, Data Science, Infrastructure, and Engineering teams to translate complex problems into ML solutions</li>\n<li>Improve system performance across latency, throughput, and model quality metrics</li>\n<li>Research and apply state-of-the-art machine learning and AI techniques, including deep learning, graph &amp; transformers based, and LLM evaluation/alignment</li>\n</ul>\n<p>Basic Qualifications:</p>\n<ul>\n<li>3-5+ years of experience building, deploying, and operating machine learning systems in production</li>\n<li>Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals</li>\n<li>ML Fundamentals: a strong grasp of algorithms, from classic statistical learning (XGBoost, Random Forests, regressions) to DL architectures (Transformers, CNNs, GNNs)</li>\n<li>Hands-on experience with modern ML frameworks (e.g., PyTorch, TensorFlow)</li>\n<li>Experience designing scalable ML pipelines, data processing systems, and model serving infrastructure</li>\n<li>Ability to work cross-functionally and translate ambiguous product or business problems into technical solutions</li>\n<li>Experience improving measurable metrics through applied machine learning</li>\n</ul>\n<p>Preferred Qualifications:</p>\n<ul>\n<li>Experience with recommender systems, search/ranking systems, advertising/auction systems, large-scale representation learning, or multimodal embedding systems</li>\n<li>Familiarity with distributed systems and large-scale data processing (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)</li>\n<li>Experience working with real-time systems and low-latency production environments</li>\n<li>Background in feature engineering, model optimization, and production monitoring</li>\n<li>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</li>\n<li>Advanced degree in Computer Science, Machine Learning, or related quantitative field</li>\n</ul>\n<p>Potential Teams:</p>\n<ul>\n<li>Ads Measurement Modeling</li>\n<li>Ads Targeting and Retrieval</li>\n<li>Advertiser Optimization</li>\n<li>Ads Marketplace Quality</li>\n<li>Ads Creative Effectiveness</li>\n<li>Ads Foundational Representations</li>\n<li>Ads Content Understanding</li>\n<li>Ads Ranking</li>\n<li>Feed Relevance</li>\n<li>Search and Answers Relevance</li>\n<li>ML Understanding</li>\n<li>Notifications Relevance</li>\n</ul>\n<p>Benefits:</p>\n<ul>\n<li>Comprehensive Healthcare Benefits and Income Replacement Programs</li>\n<li>401k with Employer Match</li>\n<li>Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support</li>\n<li>Family Planning Support</li>\n<li>Gender-Affirming Care</li>\n<li>Mental Health &amp; Coaching Benefits</li>\n<li>Flexible Vacation &amp; Paid Volunteer Time Off</li>\n<li>Generous Paid Parental Leave</li>\n</ul>\n<p>Pay Transparency:</p>\n<p>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</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_fc38e24f-97e","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Reddit","sameAs":"https://www.redditinc.com","logo":"https://logos.yubhub.co/redditinc.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/reddit/jobs/6960831","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$216,700-$303,400 USD","x-skills-required":["Python","Java","Go","PyTorch","TensorFlow","XGBoost","Random Forests","Regressions","Transformers","CNNs","GNNs","Spark","Kafka","Ray","Airflow","BigQuery","Redis"],"x-skills-preferred":["Recommender systems","Search/ranking systems","Advertising/auction systems","Large-scale representation learning","Multimodal embedding systems","Distributed systems","Large-scale data processing","Real-time systems","Low-latency production environments","Feature engineering","Model optimization","Production monitoring","LLM/Gen AI techniques","LLM evaluation","Alignment","Fine-tuning","Knowledge distillation","RAG/agentic systems"],"datePosted":"2026-04-18T15:45:58.533Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote - United States"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Java, Go, PyTorch, TensorFlow, XGBoost, Random Forests, Regressions, Transformers, CNNs, GNNs, Spark, Kafka, Ray, Airflow, BigQuery, Redis, Recommender systems, Search/ranking systems, Advertising/auction systems, Large-scale representation learning, Multimodal embedding systems, Distributed systems, Large-scale data processing, Real-time systems, Low-latency production environments, Feature engineering, Model optimization, Production monitoring, LLM/Gen AI techniques, LLM evaluation, Alignment, Fine-tuning, Knowledge distillation, RAG/agentic systems","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":216700,"maxValue":303400,"unitText":"YEAR"}}}]}