Thrive Market is seeking a Senior Data Scientist to own end-to-end analytics and ML projects—from problem definition and experimentation to model building, productionization, and monitoring—working closely with Product, Engineering, and Analytics. The role requires 5+ years of experience, proficiency in Python and SQL, hands-on experience with cloud ML tooling (e.g., AWS SageMaker, Lambda, S3, ECR) and containerized workflows (Docker, Kubernetes), and will require biannual travel to the Los Angeles HQ.

Join a team bridging research and production to build ML infrastructure (feature stores, model serving, real-time inference) and deploy models at scale. The role embeds with product engineering teams to translate experimental models into production-ready systems and solve domain problems like pricing optimization, demand forecasting, and fraud detection. Requires strong software engineering and production ML experience.

Design, implement, and operate end-to-end production ML systems including large-scale data pipelines, model training, serving, monitoring, and automated retraining. Work cross-functionally to improve ranking, recommendation, search relevance, advertising systems, and LLM-powered products. Requires 3+ years building and deploying ML systems, strong software engineering skills (Python/Java/Go), experience with ML frameworks (PyTorch/TensorFlow), and familiarity with large-scale data and real-time systems.

Work involves designing, building, and deploying production-grade ML models and infrastructure (recommendation, search/ranking, ads, content/user understanding, LLM applications). Requires 3+ years building and operating ML systems, strong programming (Python/Java/Go), experience with ML frameworks (PyTorch/TensorFlow), ML algorithms (XGBoost, Transformers, GNNs), and large-scale data/pipeline tooling. Base salary range listed: $216,700–$303,400 USD per year.

Responsible for architecting and evolving Reddit's embeddings platform (graph neural networks, transformer/sequence models, foundational models), driving high-impact projects, and building a high-performing team. Requires experience managing people (4+ years), and substantial production software and large-scale ML systems experience (8+ years).

Join Reddit's Ads Data Science team as a Senior Data Scientist (US-remote). You'll develop and apply machine learning and statistical methods to improve advertiser experience and ad platform performance, analyze large-scale datasets (Spark/Hadoop/Hive/BigQuery), design experiments and causal analyses, build ML models (scikit-learn, TensorFlow, PyTorch), communicate findings to stakeholders, and mentor junior data scientists. Requires an advanced quantitative degree (MS/PhD) with 4+ years (PhD) or 5+ years (MS) of industry experience. Base salary range: $190,800–$267,100 USD/year.

Lead the design and long-term evolution of Ads Data Science solutions, leveraging statistics, econometrics, machine learning and causal inference to optimize Reddit's ads marketplace. Partner with Analytics Engineering, Product, and Engineering to drive measurement, prediction, optimization, and mentorship across the organization. Requires an M.S. (12+ years) or Ph.D. (8+ years) in a quantitative field and strong proficiency in Python or R and SQL.

Join Ramp's Applied AI team to develop full-stack AI applications (AI Agents, RAG, structured extraction), build infrastructure for LLM inference and fine-tuning, and create internal tools to scale AI across the company. Role is based in Ramp's New York (HQ) or San Francisco offices; relocation support to NYC or SF is available.

The role focuses on building infrastructure and tools for Ramp's Analytics and Machine Learning Platform, partnering with applied scientists, AI engineers, and risk engineers to productionize ML applications. Key technical expectations include strong Python skills, experience with workflow orchestrators (Airflow/Dagster/Prefect), cloud infrastructure (AWS/GCP/Azure), SQL and modern data warehouses (Snowflake/Redshift/BigQuery), and familiarity with infrastructure tooling (Terraform, Datadog) and feature/online ML systems.

Discord is hiring a Staff Data Engineer focused on advertising products to architect and own ads data models, conversion measurement and attribution pipelines, identity resolution, and ML feature infrastructure. The role requires designing batch and near-real-time pipelines (BigQuery + dbt + Dagster), building data quality and monitoring systems, and leading cross-functional initiatives with Data Science, ML, Product, and GTM teams.

Calendly is hiring a Machine Learning Engineer to execute the full ML lifecycle: problem discovery, feature engineering, model experimentation, training, deployment, monitoring, and retraining. Role expects hands-on use of managed ML services (e.g., Vertex AI or SageMaker), ML frameworks (Keras, TensorFlow, PyTorch), data engineering and ETL tools (Spark, Beam, Airflow), experience with time series, semantic search/embeddings, and foundation model fine-tuning/prompt engineering. Remote (US) role, 4+ years industry experience required, occasional travel may be needed; employer does not sponsor immigration.

Senior Machine Learning Engineer role focused on end-to-end ML systems for fraud detection: building data pipelines and backend services, producing production-ready features, deploying and monitoring models, and collaborating with platform/backend teams. Requires 5+ years software engineering experience with strong backend skills (Go or Python), applied ML experience (PyTorch, scikit-learn), and strong SQL knowledge. Remote role for candidates in the US or Canada.

Sardine is hiring a Senior Data Scientist to design, prototype, and productionize machine learning and graph analytics solutions for fraud and risk use cases. The role involves client-facing problem solving, metrics definition, dashboard automation, collaboration with engineering to scale models, and requires 7+ years of relevant data science or quantitative experience with strong Python/R and SQL skills.

Sardine is hiring a Senior Data Scientist to design, prototype, and deploy machine learning and graph analytics solutions to detect and prevent fraud. The role involves client-facing problem solving, production model deployment, metrics design and tracking, creating BI dashboards, and partnering with engineering and product teams. Location: remote (USA or Canada). Minimum 7 years of relevant data science or quantitative experience, with strong Python/R and SQL skills.

Quora is hiring a remote Staff Machine Learning Engineer to work on recommendation systems (feed, notifications, digest emails, A2A) for the Quora product. The role requires taking end-to-end ownership of ML systems (data pipelines, candidate extraction, feature engineering, model training, production integration) and collaborating with other engineers. Minimum requirements include 5+ years professional software development experience in ML and 3+ years working on recommendation systems; US salary range provided: $219,989 - $320,613 USD per year.

Quora is hiring a Senior Machine Learning Engineer (remote) for its distribution team to improve ranking models and recommendation systems (feed, notifications, digest emails, A2A). Responsibilities include end-to-end ownership of ML systems (data pipelines, candidate extraction, feature engineering, model training, production integration). Minimum: 3+ years working on recommendation models, strong ML mathematical foundations, and experience building end-to-end ML systems. Coordination hours are Mon–Fri 9am–3pm PT. US applicants: salary range listed as $189,507–$274,603 USD per year.

Prezi is hiring a Senior Data Analyst to join the Data Science & Analytics team (remote across listed European countries). The role involves end-to-end analyses (requirements, data processing, presentation), building dashboards and data products, defining metrics, quantifying impact, fostering self-service analytics, and collaborating with data engineering. Required: 5+ years in data/business analytics, proficiency in SQL and Python (or other scripting), experience with statistical analyses (funnel analysis, clustering, forecasting, recommender systems), dashboard building, strong English communication, and interest/experience in AI tools. Bonus experience: AWS, ETL pipelines, SaaS analytics, personalization/recommendation work.

Join NVIDIA Research Singapore to research, design and accelerate generative AI models (including LLMs, visual generation, and robotics). Responsibilities include publishing research, collaborating across teams, mentoring interns and transferring technology to product groups. Requires 2 years' experience, strong research record (publications at top conferences), proficiency in Python (prototype), and familiarity with ML frameworks such as PyTorch; C++/CUDA and parallel programming are a plus.

Lead research and technical collaborations to advance quantum algorithms and applications, contribute to NVIDIA quantum products (including AI methods, simulations, and digital twins), drive partnerships with supercomputing centers and QPU builders, and publish/represent work at conferences. Requires PhD or equivalent and 5+ years' experience.

Work on a performance-oriented, low-level inference infrastructure using hardware offloads (GPU kernels, CUDA) and RDMA network cards. Requirements include ~8 years in modern C++/C/Rust development, ~3 years in Linux development, deep knowledge of TCP/IP, computer architecture and OS concepts. Advantages include experience with LLM inference stacks, distributed storage, Linux internals, low-level optimizations, parallel programming, HPC and RDMA.