New college grad (2026) position building ML and AI systems for circuit design and design automation (VLSI/ASIC/EDA). Work includes silicon data analysis, SPICE correlation, circuit optimization, design-space exploration, and integrating models with ML and visualization tools. Requires a Master's or PhD (or equivalent experience) and proficiency in Python and C++.

Work on integrating communication-library features (NCCL, NVSHMEM, GPUDirect) into AI frameworks and toolchains, perform workload and performance analysis on multi-GPU clusters, author compute/communication kernels, and influence communication-library roadmaps. Requires 5+ years of software engineering and HPC/AI experience; role based in US locations (with remote option) and includes specified salary ranges.

Lead hands-on design and prototyping of AI Agent applications (data flow, orchestration, prompts) and work with engineering, UX, and application PMs to deliver production solutions that accelerate clinical trials, regulatory submissions, or pharmacovigilance. Requires 5+ years in enterprise software product management/engineering/consulting with at least 2 years focused on AI/ML, plus Python and experience with AI frameworks, model integration, and prompt engineering.

Upwork invites candidates to join its Talent Community to hold resumes for future openings. The company is remote-first and notes it currently hires full-time employees in 34 U.S. states. Roles span areas including AI & machine learning, software development, sales & marketing, customer support, and finance & accounting. Benefits mentioned include comprehensive medical coverage, unlimited PTO, a 401(k) with matching, 12 weeks paid parental leave, and an Employee Stock Purchase Plan.

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.

Reddit is hiring a Senior Machine Learning Engineer to own end-to-end ML systems including model development, scalable data and model pipelines, model serving, and monitoring. The role focuses on recommendations, search/ranking, advertising systems, representation learning and LLM/Gen AI techniques, and requires production ML experience, strong software engineering skills, and familiarity with modern ML frameworks and large-scale data processing tools.

Reddit seeks a Senior Machine Learning Engineer to own end-to-end ML systems—from problem definition and feature engineering to training, deployment, and monitoring—focusing on recommendations, search/ranking, advertising systems, representation learning, and LLM/GenAI techniques. Requires production ML experience (3+ years), strong programming skills, and familiarity with ML frameworks and large-scale data/serving infrastructure.

Lead the Embeddings Platform team at Reddit to design, implement, and maintain large-scale embedding systems (graph neural networks, transformer/sequence models, foundational models). Responsibilities include platform architecture, enabling ML engineers and data scientists, driving scalable and reliable production ML systems, and growing a high-performing team through hiring and mentorship.

Senior Data Scientist role on the Ads Data Science team at Reddit (remote, US). Responsibilities include designing and applying ML and statistical models, analyzing large-scale datasets, defining metrics, running experimentation (A/B testing/causal inference), and mentoring junior data scientists. Qualifications call for an advanced quantitative degree and multiple years of applied data science experience; platform and large-scale data tools experience (Spark/Hadoop/Hive/BigQuery), plus proficiency in Python/R, SQL, and ML libraries are emphasized.

Lead the Ads Data Science strategy and roadmap, design large-scale statistical, econometric, causal and ML solutions (e.g., LTV, auction/auctioning, targeting, full-funnel models), partner with Product/Engineering/Analytics Engineering, and mentor senior data scientists. Requires an M.S. (12+ years) or Ph.D. (8+ years) in a quantitative field and advanced proficiency in Python or R and SQL.

Ramp's Applied AI team seeks a full-stack engineer to ship end-to-end AI projects and build infrastructure for production LLM inference and fine-tuning. Work includes AI Agents, RAG, structured extraction (jsonformer), internal tools for customer-facing teams, and scaling AI solutions across the platform.

The Data Platform Software Engineer will build infrastructure and tools that support the data science and ML development lifecycle, partnering with applied scientists, AI engineers, and risk engineers. Responsibilities include developing components of Ramp's Analytics and Machine Learning Platforms, improving tooling and data workflows, and building reliable, scalable, maintainable, and cost-efficient systems across the stack. Required skills include Python, SQL, workflow orchestration (Airflow/Dagster/Prefect), cloud experience (AWS/GCP/Azure), and experience with data warehouses (Snowflake/Redshift/BigQuery).

Join Calendly's Data Science & Machine Learning team to own end-to-end ML features: from problem discovery, experimentation, and model training to deployment, monitoring, and on-call incident response. The role requires hands-on experience shipping production ML (including managed services like Vertex AI or SageMaker), strong programming and data engineering skills, familiarity with frameworks such as TensorFlow/PyTorch, and experience with time series, embeddings/semantic search, and NLP. Annual base salary ranges listed between USD 168,785 and USD 245,434 depending on location/tier.

NVIDIA seeks a Manager for GPU Accelerated Data Analytics to drive research and development of performance optimizations across CPU and GPU platforms. Responsibilities include technical leadership, driving innovation in algorithms and low-level optimizations (CUDA, C/C++), building and mentoring a distributed team of performance engineers, and collaborating with cross-functional partners. Requires MS/PhD or equivalent, 7+ years relevant experience with 3+ years in engineering leadership, and strong expertise in CPU/GPU architecture and performance engineering.

Sardine is hiring a remote Machine Learning Engineer (US or Canada) to build and own model serving infrastructure, low-latency real-time inference, feature retrieval/pipelines, deployment paths for data scientists, and production monitoring (drift detection, retraining, incident response). The role involves Python and Go, Kubernetes and containers, cloud (primarily GCP), CI/CD, infrastructure-as-code, and occasional model development (~20% of time).

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.

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.

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.

Work with science and research institutes in Japan to promote and deploy NVIDIA GPU-accelerated solutions for machine learning and generative AI. Responsibilities include leading research collaborations, designing architectures and demos, creating and running proofs of concept, onboarding developers to NVIDIA AI platforms (NIMs, NeMo), and presenting technical topics. Requires 5+ years' experience in generative AI/deep learning, strong coding skills (Python, C/C++, Bash, Linux), and excellent Japanese and business-level English communication.