Design and deploy agentic LLM solutions to detect and prevent fraud, abuse, and security threats at scale. Collaborate with cross-functional teams to integrate these systems into production and identify product vulnerabilities.
Remote Machine Learning Engineer Jobs (505)
Search = Machine Learning Engineer
Design and deploy agentic LLM solutions to detect and prevent fraud, abuse, and security threats at scale. Build production-grade ML systems on cloud platforms and collaborate with cross-functional teams to safeguard the GitHub platform.
Develop and implement AI/ML techniques and architectures to transform large datasets into meaningful business information. Create functional prototypes and custom scalable solutions using cloud services to drive organizational innovation.
Develop and scale AI-powered experiences focusing on NLP and Large Language Models. Design evaluation frameworks and safety guardrails to ensure model reliability and performance in production.
Architect and maintain high-performance backend systems and MLOps pipelines for AI simulations at scale. Develop responsive frontends and optimize data infrastructure to support synthetic data generation and model evaluation.
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Design and implement next-generation ML systems and scalable interfaces to power Reddit's personalization and discovery. Train, evaluate, and deploy sophisticated models while participating in the full software development lifecycle.
Design and implement enterprise machine learning products, platforms, and pipelines to meet organizational objectives. Collaborate with stakeholders and cross-functional teams to translate business requirements into technical ML solutions and analyze model performance.
Build, deploy, and monitor AI/ML models to automate processes and transform data into meaningful information. Collaborate with stakeholders and technical teams to design custom algorithms and report data findings to leadership.
Design and build scalable systems for real-time fraud detection, including data pipelines and backend services in Go. Develop and deploy ML models while ensuring high standards of security, privacy, and observability.
Design and implement robust AI/ML applications to drive innovation and business insights. Collaborate with cross-functional teams to integrate scalable ML capabilities into products and services.
Design and build scalable ML data pipelines and translate R&D outputs into reusable libraries and products. Collaborate with customers and simulation engineers to embed AI models into practical engineering tools.
Design and engineer AI-powered features to extract meaning from voice and messaging data at scale. Implement end-to-end ML pipelines and monitor production inference services to ensure operational health.
Design and engineer AI-powered features to extract meaning from voice and messaging data at scale. Implement end-to-end ML pipelines and monitor production inference services to ensure operational health.
Design and engineer AI-powered features to extract meaning from voice and messaging data at scale. Implement end-to-end ML pipelines and monitor production inference services to ensure operational health.
Design and develop AI-powered features to extract meaning from voice and messaging data at scale. Implement end-to-end ML pipelines and monitor production inference services to ensure operational health.
Machine Learning Engineer
Comprehensive Rehab Consultants
·
Full Time
·
1 Week Ago
Comprehensive Rehab Consultants
Design, optimize, and productionize scalable ML, NLP, and LLM systems to power clinician tools and financial analytics. Build and maintain AI-driven products including an analytics chatbot and private LLMs trained on internal healthcare documentation.
Design, train, and productionize deep learning models for speech, audio, and computer vision domains. Own the end-to-end lifecycle from dataset curation and architecture design to deployment and performance monitoring.
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The role involves building and deploying ML models to automate workflows, predict treatment delays, and manage the intelligence layer of the platform. Responsibilities include architecting LLM-powered workflows and maintaining data pipelines for structured and unstructured data.
Collaborate with Data Science teams to implement and integrate ML algorithms into production code. Focus on ensuring performance, scalability, and the application of coding best practices within Scrum teams.
Analyze banking transactions to detect and prevent fraud using graph-based transactional analysis and ML models. Develop production-ready Python code and integrate fraud detection algorithms into the company's protection platform.
Design, train, and deploy machine learning models across multimodal domains for safety, security, and intelligence applications. Build agentic systems and evaluation pipelines to measure model reliability and safety in production environments.
The role focuses on productionalizing machine learning models for rich media experiences and building scalable ML systems. Responsibilities include owning data pipelines, establishing CI/CD for model deployment, and collaborating with scientists to optimize model performance.
Design and operate AWS-based infrastructure for data extraction, transformation, and loading to deliver predictive insights. Build and optimize complex data lakes and ML models to support customer data architecture and business needs.
The role involves researching and implementing novel ML-based solutions for Cyber Defense and developing agentic solutions for Cyber Incident Response. The engineer will solve complex security architecture challenges with a focus on real-time performance and scalability.
Design and optimize AI models for image search and online content monitoring using computer vision and NLP. Build scalable data pipelines and continuously monitor production model performance to improve accuracy.
Design and optimize advanced algorithms for workflow automation, computer vision, and signal processing. Collaborate with cross-functional teams to integrate these algorithms into the software ecosystem and optimize them for edge devices and GPUs.
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Develop and scale high-performance ML prediction models for real-time adtech environments, owning the full pipeline from raw data to online serving. Design and refine complex bidding algorithms and conduct offline simulations and online A/B tests to optimize business metrics.
Design, develop, and deploy Machine Learning models and ML pipelines for a healthcare client. Focus on optimizing models for document classification, segmentation, and data extraction in production environments.
Design and optimize machine learning models for medical image analysis to improve prostate cancer diagnosis and treatment. Build scalable data pipelines and integrate AI models into clinical software solutions while ensuring regulatory compliance.
Lead the design and optimization of scalable cloud-based data pipelines and engineering solutions. Implement AI-driven initiatives using LLM and RAG frameworks to enhance intelligent data solutions.
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