Primer is hiring a Senior Machine Learning Engineer to be the first senior ML hire, working with engineering, data, and product to identify high-impact ML use cases and ship production ML features. Responsibilities include end-to-end model research, training, deployment, monitoring, building ML infrastructure (versioning, CI/CD, observability), experimentation and A/B testing, and mentoring others. Required: senior ML engineering/data science experience with production deployments, strong Python and ML library skills, solid software engineering and MLOps understanding, and familiarity with reinforcement learning concepts. Cloud experience (AWS preferred) and exposure to payments/e-commerce are advantages.

Primer seeks a Senior ML Engineer to own the full ML lifecycle: research, training, deployment and monitoring of production models (API/batch/streaming). The role involves building ML infrastructure (versioning, CI/CD, observability), partnering with product, data and engineering, applying experimentation and A/B testing, and working on payments-related use cases. Strong Python and experience with ML libraries and cloud (AWS preferred) are highlighted. Remote-first, distributed company.

Lead design and delivery of AI-powered products and foundational AI platform initiatives including foundation model training, LLM inference, similarity search, guardrails, and observability. Role requires significant hands-on experience (Bachelor's +10 years or Master's +8 years) with languages such as Python, Go, Scala, CUDA, or Java and experience architecting scalable AI systems on cloud platforms; visa sponsorship may be considered.

Capital One is hiring a Staff AI Engineer (remote-eligible, US) to partner with cross-functional teams to design, develop, deploy, and optimize foundation models and production AI systems (LLM inference, agents, VectorDBs, model routing/orchestration, observability, and governance). Requires advanced experience in AI/ML system design, cloud deployment (AWS/GCP/Azure), and programming (Python, Go, Scala, Java, C++, CUDA). Minimum experience: Bachelor's + 8 years or Master's + 6 years (posting supports a 6-year minimum). Salary ranges are listed by location in the posting; posting indicates Capital One may sponsor employment authorization.

Supports data science projects by designing and developing algorithms and models, conducting analysis on large datasets, and communicating insights to technical and non-technical stakeholders. Role emphasizes predictive and prescriptive modeling, familiarity with Python, SQL/BigQuery, and visualization tools like Tableau; no travel required.

Remote Senior Machine Learning Engineer role targeting LATAM candidates. Requires 5+ years building and deploying production ML solutions: end-to-end ML pipelines, data ingestion and feature engineering, model training/evaluation/deployment, monitoring and lifecycle management. Hands-on with Python, SQL, PySpark, Scikit-learn, PyTorch, TensorFlow, XGBoost, MLflow, Databricks, cloud platforms (AWS/Azure/GCP), Kubernetes and MLOps practices. Collaboration with data scientists, engineers and product teams; experience with CI/CD, containerization and distributed computing is expected.

Nagarro seeks an Associate/Staff Engineer to build, configure and deploy conversational AI/chatbot solutions using Kore.ai (XO10, XO11, Artemis). Requires 4+ years total experience, 3+ years on Kore.ai, strong hands-on experience with JavaScript, Node.js, Python, REST APIs and JSON, and experience with LLMs, prompt engineering, RAG and vector databases. Responsibilities include building integrations, multi-agent orchestration, AI observability, troubleshooting production issues, and ensuring security and governance. Banking/financial services domain and Kore.ai/Artemis certification are preferred.

Lead Discord's Safety ML team building real-time and batch detection systems for content understanding, account integrity, and platform abuse. Requires 5+ years in ML roles, 3+ years managing engineering teams, hands-on experience shipping production ML systems, and domain experience such as abuse/fraud detection, content classification, behavioral or graph-based modeling, or LLM-based classification. US base salary range $272,000–$340,000 (base only).

Join Elastic's Context Engine team to lead end-to-end improvement of agentic behavior in production: implement and ship TypeScript/Python production code, design telemetry and evaluations, iterate on prompts/skills/tools safely, and partner with data scientists, backend engineers and product. The role requires 10+ years of software engineering experience with recent experience shipping and operating AI-driven products and services.

Lead engineering role owning end-to-end improvement of Elastic's Context Engine (knowledge layer for AI agents). Responsibilities include designing telemetry and evaluations, iterating on prompts/skills/automations safely, partnering with data scientists, and shipping production code (TypeScript/Python). Requires 10+ years of software engineering experience shipping AI-driven products, experience with agents with state/memory, telemetry-driven decisions, and familiarity with MCP and public APIs.

Lead end-to-end improvement of Elastic's Context Engine used by AI agents: implement and iterate on extraction automations, retrieval and memory, design telemetry and evaluations, define safe rollout/versioning for prompts/skills/tools, and collaborate with data scientists, backend engineers and product. Requires 10+ years of software engineering experience shipping AI-driven products, experience with agents, telemetry, evaluation, and backend development in TypeScript or Python. Elasticsearch and MCP familiarity are listed as beneficial.

Own end-to-end improvement loop for the Context Engine that serves AI agents from Elasticsearch: design telemetry and evaluation, iterate on prompts/skills/automations safely, and ship production code. Requires 10+ years of software engineering experience shipping AI-driven production products, strong backend skills in TypeScript or Python, familiarity with agent frameworks, retrieval/memory, MCP, and practical Elasticsearch experience. Typical starting salary range: €104,800–€165,700 EUR.

Capital One seeks a Staff AI Engineer to partner with cross-functional teams to design, develop, deploy, and support AI components including foundation model training, LLM inference, agents/multi-agent workflows, similarity search/VectorDBs, guardrails, evaluation, and observability. The role emphasizes optimization for scalability, cost, latency, and throughput, adopting open-source and cloud tools (e.g., PyTorch, Hugging Face, AWS). Basic qualifications require a related Bachelor's plus 8 years experience or a related Master's plus 6 years experience. Position is remote-eligible and also listed for specific US locations.

Role involves researching and developing techniques to GPU-accelerate deep learning, machine learning, and AI workloads; performing in-depth analysis and optimization of complex AI and HPC algorithms on CPU and GPU architectures; collaborating with industry and academic experts; publishing or presenting optimization techniques; and influencing hardware and software design. Requires an advanced degree (or equivalent), 8+ years' relevant experience, programming fluency in C/C++, expertise in parallel programming (CUDA, OpenACC, OpenMP, MPI, pthreads), low-level performance optimization, and CPU/GPU architecture knowledge.

Senior role focused on engineering end-to-end analytics systems: building and maintaining BigQuery and MariaDB pipelines, writing advanced SQL, developing internal tools and APIs in Python/FastAPI, and applying AI/ML capabilities (LLMs, embeddings) to augment analytics. Requires 7+ years experience, strong data architecture knowledge, and a public GitHub profile. Location: Bulgaria (hybrid, Sofia); MariaDB does not sponsor visas or relocation.

Lead development of production recommendation and targeting ML systems (Shop, Nitro, Server Subscriptions, Gifting) with responsibility for model architecture, distributed training, and large-scale data pipelines. Requires 8+ years of applied ML experience, expertise in deep learning and recommender architectures, strong Python and ML-framework skills (PyTorch/JAX/TensorFlow), and experience building ML platforms and taking systems from 0→1 to production at scale.

Seeq seeks a Staff/Principal AI Software Engineer to provide architectural leadership and hands-on implementation of backend platforms and agentic AI systems. Responsibilities include designing scalable services, agent routing/orchestration, runtime and sandboxing infrastructure, observability and evaluation strategies, and integrations with internal and third-party systems. Requires 10+ years professional software engineering experience, substantial recent work on generative AI/agentic systems, deep Python and backend expertise, experience with Kubernetes and SaaS production systems. Salary range listed: 187,500 - 220,000 USD/year. Seeq does not sponsor US F1 or H-1B visas.

The Home Depot is hiring a Principal Cybersecurity Engineer (Domain Architecture & Data Science) to design and implement AI-powered security solutions that improve threat detection, incident response, automation, and overall SOC effectiveness. Requires 10+ years' experience, technical leadership, and collaboration across threat detection, red teaming, and engineering teams. Travel is not required; candidate must be legally permitted to work in the United States.

Join the NVIDIA DRIVE team to design, implement, and scale synthetic-data generation and sensor-simulation workflows (NuRec and Cosmos) for autonomous driving. Responsibilities include developing lidar/radar/camera simulation, world-model improvements, dataset quality assessments and sim-to-real evaluation, and operating large-scale simulation pipelines. Requires a B.S./M.S. (or equivalent), 8+ years' relevant experience, strong Python and C++ skills, and familiarity with Linux, GPU workloads, and modern scalable engineering tooling (Git, Docker, Kubernetes, CI/CD).

NVIDIA is hiring a senior perception engineer to design and productize end-to-end deep learning solutions for traffic signal understanding (traffic lights, signs, road markings, construction objects, text) to enable autonomous driving without HD maps. Requires strong deep learning and computer vision experience (PyTorch, Python/C++), data-driven development with large labeling efforts, and experience deploying DNNs to embedded/real-time platforms. Location indicates US (Santa Clara) and remote options.