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Job Description Summary: We are seeking a skilled Machine Learning Engineer with approximately three years of hands-on experience designing, deploying, and maintaining production-grade machine learning systems. In this…
Designs and trains ML/SLMs to probe and harden AI systems against adversarial attacks like jailbreaks, prompt injection, and data poisoning, then translates findings into actionable remediation steps.
The Lead Data Scientist oversees end-to-end ML/data science projects, ensuring scalable, production-ready solutions aligned with business goals. Core work includes technical leadership, model deployment, standards enforcement, and mentoring across Python/SQL, cloud platforms (AWS/GCP/Azure), and ML techniques like time-series forecasting.
The Lead Data Scientist at Gymshark oversees technical leadership for data science and ML solutions, ensuring scalable, production-ready models aligned with business goals. Core work includes designing, deploying, and optimizing ML systems using cloud platforms (GCP/AWS/Azure) and mentoring teams in Python/SQL.
*Note: this is contract position through the end of 2026, with possibility of extension. Candidates based in San Diego are preferred. Remote candidates will also be considered based on qualifications.* Job Summary: As…
About the role Applied AI Engineer will play a key role in designing, implementing, and scaling Mission's enterprise AI platform and intelligent automation capabilities as part of our AI transformation strategy.…
Build and improve generative AI models for image creation, working with deep learning and production ML pipelines to enhance Recraft’s creative tools.
Build statistical and ML models on large pharma datasets in Databricks/AWS to inform business decisions, partnering with cross-functional teams.
Build and deploy ML and GenAI models for security, anomaly detection, and developer tools at a DevSecOps platform company.
Build and operate scalable ML inference platforms for an AI-native cloud startup, designing GPU-powered serving systems, deployment pipelines, and observability for real-time AI applications.
Build and operate scalable ML inference platforms using vLLM/TGI/Triton to serve AI models with low latency and high GPU efficiency for a next-gen cloud startup.
Builds causal inference and ML solutions to measure business impact, design experiments, and deploy production-ready models using Python, SQL, and MLOps.
Lead AI and lab product strategy for a biotech company using generative AI to design novel therapeutics, coordinating cross-functional teams of AI researchers, engineers, and scientists.
A senior engineer embedded with enterprise clients to advise on AI governance, scope AI projects, and build production-ready solutions using LLMs and agentic workflows.
Lead the design, development, and deployment of recommender systems and personalization models for Penguin Random House’s digital platforms to improve book discovery and customer engagement.
Build and own back-end systems and ML pipelines for AI-powered cybersecurity threat detection, using Python/Go/Node.js on Kubernetes and deploying generative AI workflows.
Build and scale ML pipelines to normalize telematics data, detect anomalies, and forecast routes for logistics and insurance customers using time-series and geospatial models.
Build and deploy ML models and pipelines that power Adyen’s data products, from research to production monitoring and business impact measurement.
Design and ship cloud-native AI solutions (RAG, agents, LLM integrations) in Python, owning architecture and client delivery for global enterprises.
Build and deploy ML models for search, pricing, routing, and generative-AI features that power Trainline’s travel platform, collaborating with data scientists and engineers.
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