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.

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.

The Applied AI Engineer will ship end-to-end full-stack AI projects, build and integrate AI infrastructure for production inference and fine-tuning, develop internal tools and platforms, and improve engineering processes to scale AI solutions. Role is based in Ramp's New York (HQ) or San Francisco offices; relocation support to NYC or SF is offered as needed.

Forward Deployed Engineer on an agent-first team who will scope and build internal and external agents, work directly with customers and cross-functional teams (Sales, Solutions, Customer Success), and drive product engineering priorities within a domain. Role prefers 2+ years of software engineering experience and experience building with and for agents.

Join Ramp's Growth Platform team to build and scale internal platforms and customer-facing applications that power growth. Responsibilities include designing and maintaining high-volume data ingestion and activation pipelines, applying AI/LLMs to unstructured data and automation, and driving metric-driven experiments. Role requires a minimum of 3 years of software development experience. Relocation support to NYC or SF is offered as needed.

The role focuses on building and integrating components of Ramp's Analytics and Machine Learning Platform, enabling applied scientists, AI engineers, and risk engineers to develop and productionize ML applications. Required skills include Python, workflow orchestrators (Airflow/Dagster/Prefect), cloud infrastructure (AWS/GCP/Azure), and SQL/databases such as Snowflake, Redshift, or BigQuery. Position is based at Ramp's HQ in New York, with relocation support to NYC or SF noted in the posting.

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.

Remote Senior Machine Learning Engineer based in the United States or Canada. Requires 5+ years in software engineering with strong backend experience (Go or Python), hands-on applied ML with large datasets (PyTorch, Scikit-learn), strong SQL and database familiarity, and end-to-end ML systems experience (feature pipelines, deployment, monitoring). Responsibilities include building data pipelines and backend services, developing and deploying production ML models for fraud detection, and collaborating on integration, security, and observability.

Hands-on senior data science position to design, prototype, and productionize machine learning and graph analytics solutions for fraud and risk. Responsibilities include client engagement, building metrics and dashboards, conducting EDA and cohort analyses, collaborating with engineering to scale models, and driving data-driven risk strategies. Remote-first role covering specified countries in Europe and North America; requires 7+ years experience.

Role involves researching and developing techniques to accelerate deep learning, machine learning, and other AI workloads on modern CPU/GPU architectures, performing in-depth analysis and optimization of parallel algorithms, and publishing/presenting results to the developer community. Requires a Masters (or equivalent), 8+ years' relevant experience, programming fluency in C/C++, and expertise in parallel programming models (CUDA, OpenACC, OpenMP, MPI, pthreads) and CPU/GPU architecture fundamentals. Locations listed include multiple U.S. sites and remote options.

Responsible for designing, implementing, and optimizing high-performance dense linear algebra software on GPUs, leading projects and mentoring engineers. Requires 8+ years experience, a degree in CS/Applied Math or equivalent, strong C++ skills, expertise in kernel generation and JIT, and experience with GPU-related technologies (CUDA) and performance optimization. Base salary range shown: $184,000–$356,500 depending on level.

Role involves partnering with NVIDIA engineering, product, and sales to secure design wins; performing proof-of-concepts and in-depth profiling/optimization of ML/DL models on GPU architectures; working with client ML researchers and engineers; and producing collateral (notebooks, blogs) for finance use-cases. Requires 12+ years of relevant experience and strong Python/C++ and ML/DL framework knowledge.

Lead architecture and development of vehicle and sensor abstraction layers (VAL/SAL), design plugin frameworks and interfaces to sensors and actuators, and improve integration across vehicle and sensor configurations. Responsible for developing production-quality C++ code (including GPGPU/CUDA), validating through real-world and synthetic testing, following automotive safety/quality standards (e.g., MISRA), and managing teams. Requires MS (or equivalent), 12+ years relevant experience and 8+ years of management experience.

Work on design and implementation of GPU-accelerated libraries and SDKs for unstructured sparsity in deep learning and HPC. Responsibilities include developing a C++ system for sparse tensor computations, DSL specifications for sparse storage formats, on-demand code generation, enabling frameworks like Python/PyTorch, and performance evaluation and optimization. Required: BS/MS/PhD (or equivalent), 6+ years developing and optimizing high-performance C++ software, strong Python and CUDA skills, and experience with parallel programming (MPI/OpenMP) and sparse compilers (MLIR or TACO).

NVIDIA seeks a Solutions Architect for its AI Software Segment to develop end-to-end AI solutions, support LLMs and multimodal models, and guide customers through data processing, training, evaluation, RL, and model optimization. Requires 5+ years with AI frameworks (PyTorch, JAX, TensorFlow), Python, Linux, experience with distributed training tools (Kubernetes, SLURM), and expertise in GPU-based model training. Location noted as US (remote) and Santa Clara; salary range stated.

Role to partner with NVIDIA engineering, product, and sales to drive design wins in banking and consumer finance by performing proofs-of-concept, profiling and optimizing ML/DL models on NVIDIA GPUs, and building industry-specific collateral. Requires 12+ years as an ML/Software Engineer, BS/MS/PhD or equivalent experience, strong coding in Python and C++, and experience with ML/DL frameworks (TensorFlow, JAX, PyTorch, Spark, Dask). Base salary range stated: 224,000 USD - 356,500 USD per year.