AI / ML Solutions Engineer
The AI / ML Solutions Engineer at Anyscale is responsible for designing, implementing, and scaling machine learning and AI workloads using Ray and Anyscale directly with customers. This includes implementing production AI / ML workloads such as distributed model training, scalable inference and serving, and data preprocessing and feature pipelines. The role involves working hands-on with customer codebases to refactor or adapt existing workloads to Ray. The engineer advises customers on ML system architecture including application design for distributed execution, resource management and scaling strategies, and reliability, fault tolerance, and performance tuning. They guide customers through architectural and operational changes needed to adopt Ray and Anyscale effectively. Additionally, the engineer partners with customer MLE and MLOps teams to integrate Ray into existing platforms and workflows, supports CI/CD, monitoring, retraining, and operational best practices, and helps customers transition from experimentation to production-grade ML systems. They also enable customer teams through working sessions, design reviews, training delivery, and hands-on guidance, contribute feedback to product, engineering, and education teams, and help develop reference architectures, examples, and best practices based on real customer use cases.
Enterprise Account Executive - Italy
The AI Outcomes Manager will partner with executive sponsors and end users to identify high-impact use cases and turn them into measurable business outcomes on Glean. They will lead strategic reviews and advise customers on their AI roadmap to ensure maximum value from Glean's platform. The role involves translating business needs into clear problem statements, success metrics, and practical AI solutions while collaborating with Product and R&D to shape priorities. They will conduct discovery workshops, scope pilots, and guide rollouts to drive broad and deep adoption of the Glean platform. Additionally, they will design and build AI agents with and for customers, including rethinking and redesigning underlying business processes to maximize impact and usability. The manager will proactively identify expansion opportunities and drive engagement across teams and functions.
Senior AI Engineer - San Mateo, CA
The role involves training, evaluating, and monitoring new and improved LLMs and other algorithmic models. The engineer will test and deploy content moderation models in production and iterate based on real-world performance metrics and feedback loops. They are expected to develop medium to long-term vision for content understanding-related R&D, collaborating with management, product, policy & operations, and engineering teams. The position requires taking ownership of results delivered to customers, advocating for changes in approach where needed, and leading cross-functional execution.
Customer Success Solution Architect (Brazil)
The Solution Architect is responsible for developing detailed and scalable architectural designs to address client needs using Articul8 products and third-party libraries and tools. They run pilot programs with customers to demonstrate the feasibility and advantages of proposed solutions, including introducing new product features or building prototypes. The role requires working closely with clients to understand business challenges and technical requirements through workshops, meetings, and presentations. They optimize solutions for performance, reliability, and cost-effectiveness, selecting appropriate instance types, auto-scaling configurations, and storage options. Ensuring solutions comply with security best practices and regulatory requirements is necessary, including implementing identity and access management, data encryption, and other security measures. The architect also creates comprehensive documentation and provides training on solution implementation and management. Collaboration with cross-functional teams such as Applied Research, Engineering, Quality Assurance, and Customer Success is required to incorporate innovation and maintain product leadership. Additionally, the role involves mentoring and guiding junior team members and helping to build a culture of rapid innovation.
Backend Engineer - (Python) Brazil
Design, develop, test, deploy, maintain, and improve scalable, secure, and high-performance backend systems with a focus on high availability, low latency, and cost-effectiveness. Serve as the subject matter expert in infrastructure for designing new products and introducing new technology to existing product lines. Collaborate closely with engineering and research teams to integrate infrastructure components with product features, ensuring optimal system performance and user experience. Design event-driven architectures and develop APIs and microservices to support real-time processing and analytics. Ensure system reliability, performance, and scalability through monitoring, logging, and error handling mechanisms. Stay updated with emerging trends, technologies, and methodologies to enhance infrastructure capabilities. Participate in code reviews, contribute to open-source projects, and mentor junior engineers.
Staff AI/Machine Learning Engineer
Act as a technical reference for the team, supporting engineers through design reviews, technical discussions, and hands-on problem-solving. Design, guide, and evolve LLM- and GenAI-based systems such as AI agents, RAG pipelines, and decision-support tools, balancing performance, cost, reliability, and user impact. Influence the architecture and implementation of ML systems across the stack, including data pipelines, experimentation, deployment, and monitoring in production. Define and promote best practices and standards for model evaluation, experimentation, observability, and iteration across ML initiatives. Partner closely with product and engineering teams to shape ML-driven solutions, clarify trade-offs, and ensure alignment with business goals. Lead technically complex or ambiguous initiatives, unblocking teams and driving clarity where requirements or approaches are not well-defined. Improve the maturity of ML infrastructure and workflows to support multiple contributors and use cases over time. Stay current with advancements in GenAI, LLM tooling, and ML systems, and selectively introduce new approaches that provide clear value. Share knowledge through documentation, mentoring, and collaborative problem-solving to raise the technical bar across the organization.
Member of Technical Staff - ML Research Engineer; Multi-Modal - Audio
Invent and prototype new model architectures that optimize inference speed, including on edge devices; build and maintain evaluation suites for multimodal performance across a range of public and internal tasks; collaborate with the data and infrastructure teams to build scalable pipelines for ingesting and preprocessing large audio datasets; work with the infrastructure team to optimize model training across large-scale GPU clusters; contribute to publications, internal research documents, and thought leadership within the team and the broader ML community; collaborate with the applied research and business teams on client-specific use cases.
Finance Platform Engineer
Use proprietary software applications to provide input and labels on defined projects. Support and ensure the delivery of high-quality curated data. Contribute to the training of new tasks by working closely with the technical staff to develop and implement cutting-edge initiatives and technologies. Interact with technical staff to improve the design of efficient annotation tools. Choose problems from economics fields that align with expertise, focusing on macroeconomics, microeconomics, and behavioral economics. Regularly interpret, analyze, and execute tasks based on given instructions. Provide services including labeling and annotating data in text, voice, and video formats to support AI model training, sometimes involving recording audio or video sessions.
Data Engineer – Spark Specialist
Help users discover and master the Dataiku platform through user training, office hours, demos, and ongoing consultative support. Analyse and investigate various kinds of data and machine learning applications across industries and use cases. Provide strategic input to the customer and account teams that help make customers successful. Scope and co-develop production-level data science projects with customers. Mentor and help educate data scientists and other customer team members to aid in career development and growth.
Product Marketing Manager, Developer Platform
As Product Marketing Manager, you drive go-to-market strategies for OpenAI’s developer platform, focusing on adoption, strategic launch planning, and growth of APIs among developers and businesses. You collaborate closely with Product, Engineering, and GTM teams to develop product positioning, messaging, marketing plans, post-launch campaigns, and customer/market insights.
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