Own and evolve three production analytics platforms (data warehouse ~20PB; event ingestion 6–7B events/day; Airflow orchestration). Deliver three net-new systems: a production cost-attribution pipeline, forecast-driven autoscaling for Trino/dbt, and a production Gen AI (RAG / natural-language-to-SQL) system. Hands-on IC role (~70% coding) requiring experience with large-scale data/traffic, Kafka, Trino, dbt, Airflow, AWS, containers, SQL/Python and production Gen AI.

Capital One is hiring a Distinguished AI Engineer to design, develop, deploy, and support foundation model training, LLM inference, similarity search, guardrails, model evaluation, and observability at scale. The role requires deep engineering and ML expertise (Python, Go/Scala/Java/C++/C#), experience with cloud platforms (AWS/GCP/Azure), and demonstrated ability to optimize training and inference for scalability, latency, throughput and cost. The position is remote-eligible and Capital One may sponsor employment authorization.

Hudl seeks Senior Engineers to join cross-functional product teams in London (with flexible remote options) to develop hardware‑agnostic ingestion layers and time‑series architectures fusing live video with biomechanical data, addressing real‑time data sync and ML inference challenges. The role involves full‑stack web development, collaboration with Product/Design/QA, mentoring, and delivering large‑scale applications. Preferred tech: C#/Node, React, TypeScript, MongoDB/SQL/Elasticsearch, and AWS.

Role to design, implement, and harden production AI agents: multi-step reasoning pipelines, LLM orchestration and planning, tool and data integration, RAG/embedding pipelines, and monitoring. Requires 5+ years software engineering (TypeScript/Node, Go, or Python), hands-on LLM experience (prompting, function calling, model selection, evaluation), experience with LangChain/OpenAI Agents SDK or similar, and knowledge of CI/CD, containerization, GPU/AI infra, and security/PII guardrails. English proficiency (B2).

Udacity (an Accenture company) is hiring independent contractors to update and maintain School of AI course content and cloud/workspace environments. Responsibilities include updating Python exercises and project starter code, maintaining LLM libraries and APIs (e.g., LangChain, OpenAI, Hugging Face), troubleshooting student issues, updating Udacity Workspaces and Cloud Labs, and ensuring compatibility with current tooling. Minimum two years of Python development experience required.

Reddit is hiring a Senior Machine Learning Systems Engineer to build scalable offline ML experimentation platforms, production training orchestration, experiment tracking, model registries, and agentic AI execution infrastructure for Ads ML. The role requires experience in large-scale distributed systems, ML platform engineering, and workflow/orchestration technologies (e.g., Kubeflow, Argo, Airflow, Spark/Flink/Ray).

NVIDIA is hiring a Senior Deep Learning Inference Software Engineer to design, build, and optimize GPU-accelerated software and inference frameworks (vLLM, SGLang, FlashInfer). The role centers on performance tuning for LLMs, multimodal and generative AI across NVIDIA accelerators and requires strong C/C++ skills, 5+ years' software development experience, and GPU/CUDA experience. Salary ranges for Poland are provided.

NVIDIA seeks a Senior Solutions Architect for Industrial Engineering to advise CAE/CFD/FEA ISVs, simulation platforms, and OEMs. Role involves accelerating solvers on NVIDIA GPUs/HPC, applying physics-ML and surrogate models, using Omniverse for digital twins, analyzing application architectures, and delivering trainings and demos. Requires 8+ years in computational engineering or simulation, strong numerical methods background, and hands-on experience with tools like Ansys, OpenFOAM, and languages such as Python and C/C++.

Hands-on Solutions Architect role focused on designing, deploying, and operating Kubernetes-based platforms for distributed robotics and Physical AI workloads (simulation, synthetic data, training, inference). Requires experience with GPU acceleration, NVIDIA inference tooling, workflow orchestration (Airflow/Argo), DevOps practices (GitOps, IaC, observability), networking and storage systems, and customer-facing technical leadership.

Lead technical engagements with customers and partners to define and deliver solutions using NVIDIA platforms for AI, deep learning, HPC, and edge deployment. Requires BS/MS/PhD or equivalent and 8+ years' experience in robotics, humanoids, and AI domains, experience with GPU-based parallel computing, containerization (Docker, Kubernetes), deep learning frameworks (e.g., TensorFlow, PyTorch, TensorRT), and strong communication and customer-facing skills.

Hiring an Engineering Manager to lead and mentor a 4–6 engineer team responsible for the company’s internal data warehouse and full ML Ops lifecycle (experimentation, training pipelines, model deployment, monitoring). Requires hands-on experience across data infrastructure and ML systems, at least 5 years professional experience and a minimum of 2 years leading data/ML/platform teams. Technologies mentioned include ClickHouse, DataBricks, dbt, Prefect, DataHub, AWS SageMaker and other AWS cloud services.

Senior AI Engineer responsible for translating AI concepts into enterprise-ready products: developing scalable LLM/agent-based applications, orchestration layers, and cloud-native MLOps (Docker, Kubernetes/GKE, Terraform, CI/CD). Requires 6+ years experience, strong Python and production AI delivery skills. Role is remote with requirement to be legally permitted to work in the United States; travel typically 5–20%.

Lead technical strategy and execution for models powering Reddit Shopping Ads (Dynamic Product Ads, Product Listing Ads). Own end-to-end model work including data and label design, feature engineering, model selection, offline and online evaluation, deployment, monitoring, and iteration. Require substantial experience building large-scale, low-latency ML systems, ads or recommendation model experience, and demonstrated technical leadership/mentoring.

CrowdStrike seeks a hands-on Principal/Staff-level Data/AI Platform Engineer to architect, implement, and operate large-scale data platforms powering LLMs, RAG, and agentic systems. The role requires 5+ years in data/platform engineering (with 3+ years on AI/ML platforms), deep experience in LLM engineering, distributed systems, MLOps/DataOps, and production-grade tooling across cloud, streaming, and orchestration technologies. US base salary range: $195,000–$290,000/year.

Lead the design and delivery of full-stack internal AI applications that incorporate LLMs, agents, retrieval systems, workflow automation, enterprise integrations, and application-level identity/authorization. Partner with platform and business teams to instrument telemetry, ensure security and compliance, and convert prototypes into repeatable, production workflows. Requires 7+ years software engineering experience.

Lead a small, senior data engineering team responsible for Primer's data platform — real-time event streaming, data lakehouse/warehouse, modelling and pipelines — and own the emerging ML function. Accountable for end-to-end delivery, technical direction, data quality and incident response, cost control (FinOps), and partnering with Product and engineering leadership. Role is remote-first and covers candidates in the listed countries.

Role to design, harden, and scale deep learning infrastructure and libraries for large-scale GPU training (data loaders, distributed training, scheduling, monitoring). Requires 12+ years experience in high-performance distributed systems, strong Python skills, and deep knowledge of PyTorch, DDP/FSDP, NCCL, datacenter networking, parallel filesystems, and schedulers.

Join Sonatype's AI & Data Science team to prototype, validate, and help deploy ML and generative-AI solutions (malicious-behavior detection, anomaly/fraud detection, developer GenAI features). Requires 5+ years experience, strong Python skills, familiarity with LLM ecosystems and tools (Databricks, scikit-learn, LLM APIs, LangChain/LangGraph/Semantic Kernel), and experience taking models from research to production.

Join Sonatype's AI & Data Science team to operate as an internal AI consultant and technical lead: scope problems, design experiments, build and validate models (classical ML to LLMs/embeddings/RAG/agentic workflows), and translate research into scalable production APIs and workflows. The role emphasizes collaboration with product, engineering, security, and data-governance teams, strong Python and Databricks experience, and practical familiarity with modern LLM ecosystems and MLOps practices.

Work on extracting maximum performance from NVIDIA GPUs for AI inference by designing reproducible experiments, profiling with Nsight/CUPTI/PyTorch tools, and delivering fixes across serving frameworks (e.g., TensorRT-LLM, vLLM). Requires strong CUDA/C++ and Python skills, experience with benchmarking/profiling GPU workloads, and 3+ years of relevant engineering experience.