Lead, Finance Analytics & Enablement AI/ML responsible for data warehouse strategy and governance for the finance ledger, building a reporting Center of Excellence, implementing a Finance AI automation roadmap, establishing data pipelines and AI foundations, and optimizing GCP costs. Manages a team (4 engineers and 1 finance/strategy manager) and reports to the CFO. Engagement is offered as an Independent Contractor in Ireland. Requires ~15+ years' experience.

Build, prototype, and ship AI/LLM- and agent-powered features for analytics and data workflows in Grafana Cloud. Work involves context engineering, handling large datasets, integrating agentic components with internal tools (e.g., Slack, alerting), using cloud-native environments and observability tools, and collaborating across the team to deliver production-grade, user-facing software.

Grafana Labs seeks a Staff AI Engineer to design, develop, test, and ship AI-powered features (LLM/GenAI and agent workflows) for analytics and observability. The role emphasizes rapid prototyping, production-grade software delivery, cloud-native environments (AWS/GCP/Azure), and integration with observability and internal tooling. This is a remote position considering candidates located in Germany, Ireland, Sweden, Spain, and the United Kingdom. Listed Spain base compensation: €94,000–€117,000.

Grafana Labs seeks a Staff AI Engineer for the 2nd Horizon skunkworks team to design, develop, test, and ship AI-driven analytics features that operate on large datasets. The role focuses on building production-grade, high-performance features using LLMs/GenAI and agentic components, rapid prototyping and iteration with real users, cloud-native deployment, and observability for troubleshooting. Candidates should have practical experience with LLMs/context engineering, delivering software to production, and familiarity with cloud environments (AWS/GCP/Azure).

Grafana Labs seeks a Staff AI Engineer for a skunkworks 2nd Horizon team to design, develop, test, and ship AI-powered, production-grade features (LLM/agent-driven) focused on analytics and large datasets. The role involves rapid prototyping, cloud-native development (AWS/GCP/Azure), observability, integrations (e.g., Slack/alerts), and collaborating with internal data teams. Position is remote with candidates considered in Germany, Ireland, Sweden, Spain, and the UK; Germany base compensation range provided.

Remote EMEA role within Forward Deployed Engineering focused on AWS-based ML/GenAI architectures (including Amazon Bedrock and SageMaker), cloud cost/reliability/security optimization, MLOps, and converting field work into reusable patterns and DCI product contributions. Requires 4+ years architecting, deploying, and managing cloud-based AI/ML solutions and hands-on AWS experience.

Senior Cloud Architect in DoiT's Forward Deployed Engineering Delivery team responsible for designing, deploying, and optimizing production ML/GenAI workloads on AWS (including Amazon Bedrock and SageMaker). Focus areas include cost efficiency, reliability, security, MLOps, and converting field work into reusable patterns and product feedback (DCI). Requires 4+ years of relevant cloud AI/ML experience and strong hands-on AWS expertise.

DoiT seeks a Senior Cloud Architect (Forward Deployed Engineering, Delivery) to lead hands-on design and implementation of ML/GenAI workloads on AWS, drive cloud optimizations (cost, reliability, security), convert field work into reusable patterns and DCI product feedback, and operate as an embedded technical partner on account teams. Requires 4+ years architecting and managing cloud-based AI/ML solutions and hands-on experience with AWS services such as SageMaker and Bedrock.

Embedded in Forward Deployed Engineering, this role leads architecture and hands-on delivery of ML/GenAI workloads on AWS (including Bedrock and SageMaker), focuses on cost, reliability, security and observability, converts field work into reusable patterns and contributions to DoiT Cloud Intelligence, and partners with account teams to improve customer outcomes and platform adoption. Requires 4+ years architecting and operating cloud AI/ML solutions.

Join DoiT as a Senior Cloud Architect within the Forward Deployed Engineering (FDE) Delivery team. The role focuses on hands-on design and implementation of production ML/GenAI workloads on AWS (with multi-cloud awareness), improving cost, reliability, security, and observability, and converting field work into reusable patterns and product feedback. Requires 4+ years architecting and managing cloud-based AI/ML solutions and strong experience with AWS services such as Amazon Bedrock and SageMaker. Remote in the UK, Ireland, Estonia, Sweden, the Netherlands, Israel; contractor options in Eastern Europe and Portugal.

Join the Forward Deployment Engineering team as a Senior Cloud Architect delivering hands-on design and implementation of ML and Generative AI solutions on AWS. You will work with customer account teams to improve product adoption and cloud health through cost optimization, reliability, security, automation and observable architectures. The role requires 4+ years of experience architecting, deploying, and managing cloud-based AI/ML solutions and expertise with AWS services such as SageMaker and Bedrock, plus strong skills in MLOps, CI/CD, infrastructure as code, and cross-functional collaboration.

This remote Senior Cloud Architect role within DoiT's Forward Deployed Engineering team leads design and implementation of ML/GenAI workloads on AWS, advises customers on cost, reliability, security and performance, and turns field solutions into reusable patterns and product feedback. The position supports customers across the UK, Ireland, Estonia, Sweden, the Netherlands, Israel and contractors in parts of Europe, and requires hands-on AWS and ML/GenAI expertise (4+ years).

Hiring a Principal Software Engineer to lead development of vector search and vector database capabilities in Elasticsearch. The role involves designing and implementing vector search features, improving search relevance and performance, working with Lucene, contributing to open-source, and collaborating with a distributed engineering team. Strong Java, algorithms, and prior experience with vector similarity/HNSW/IVF and search platforms are emphasized.

As a Machine Learning Engineer you will build and optimize real-time data pipelines and backend services, develop and deploy ML models for fraud detection, and turn raw data into production-ready features. Collaborate with platform and backend engineers (Go), maintain security/privacy/compliance standards, and champion testing, documentation, and observability. Required: applied ML experience (PyTorch/Scikit-learn), strong SQL, experience with feature pipelines and model deployment/monitoring, and excellent English communication.

Twilio seeks a Machine Learning Engineer to develop and deploy end-to-end ML solutions for conversation intelligence, including data ingestion, feature engineering, model development, validation, and production inference. The role requires 2+ years in ML engineering or applied ML, strong Python skills, experience with at least one ML framework (PyTorch, TensorFlow, or JAX), familiarity with NLP libraries and cloud-based infrastructures, and experience using or deploying LLMs. Responsibilities include instrumentation and monitoring of ML services, participating in on-call rotations, and collaborating across product and engineering teams.

Parexel seeks an AI Strategy and Implementation Lead to drive Medical Communications AI strategy and deliver end-to-end implementation of AI-driven solutions (including AI agents on LLM platforms). The role requires demonstrable experience in medical communications or medical affairs, hands-on AI/LLM development and deployment, project and change management, and stakeholder engagement; it is a remote role based in select EMEA countries (listing includes Ireland and the United Kingdom).

Senior data science leader role requiring 10+ years in data science/ML engineering and 4+ years managing teams. Responsibilities include setting multi-team roadmaps, mentoring, overseeing statistical modeling, experiment design, classifier implementation, LLM/AI work, improving data pipelines, and ensuring privacy-aware analytics across product and revenue areas. Position is remote with listed country eligibilities and includes an annual compensation figure disclosed for the US.

Hands-on role focused on building and deploying machine learning and graph analytics solutions for fraud and risk. Responsibilities include client-facing problem solving, prototyping and productionizing models, designing and tracking performance metrics, conducting EDA and cohort analyses, and creating automated BI dashboards. Remote-first role open to candidates in UK, Germany, Ireland, Spain, Poland, Bulgaria, and Lithuania. Requires 7+ years experience and proficiency with Python or R and SQL; BI tools (Tableau, Sigma, Metabase) and Spark are highlighted.

Responsible for designing and implementing automated training pipelines, ETL and feature engineering, and deploying real-time ML pricing solutions. Role involves monitoring production systems for latency, drift and training-serving skew, running champion-challenger tests, and partnering with data science, engineering and product teams to deliver scalable pricing models. Ideal candidate has 5+ years' experience with production ML systems, proficiency in Python, Scala and SQL, and experience with distributed data processing.

Join DuckDuckGo's Data Science team to drive product and business impact via statistical modeling, experiment design, Bayesian marketing analysis, classifier implementation, and production ML/NLP/LLM work. Role requires 7+ years' experience, production-grade Python, advanced SQL and familiarity with columnar databases (BigQuery, ClickHouse, Redshift, Druid). Position is remote with expected ~40 hours/week and at least two company travel events per year. Compensation is $178,500 USD annually plus stock options.