Senior AI/ML Engineer

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🕒 April 1

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Cloudwerx

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2018

🔌 API

🤖 Artificial Intelligence

☁️ SaaS

API • Artificial Intelligence • SaaS

Cloudwerx is a technology consulting firm that specializes in Salesforce services, customer data solutions, and generative AI. They focus on transforming businesses by creating technology strategies that align with their clients' objectives. With a strong emphasis on a human-centered design methodology, Cloudwerx helps organizations unlock the potential of their data and enhance customer experiences through innovative CRM solutions and managed services.

📋 Description

• Architect and implement sophisticated multi-agent systems and autonomous workflows leveraging the Google AI SDK, LangGraph, and LangChain to solve complex, non-linear business processes. • Lead the design and construction of cloud-native solutions, using Terraform, Kubernetes, and Docker to ensure that AI models are deployed on scalable, reliable infrastructure. • Apply rigorous statistical evaluation frameworks to model performance, moving beyond standard metrics to include uncertainty estimation, calibration, and robust hypothesis testing during model optimization (LoRA, QLoRA). • Lead the development of custom predictive models and deep learning solutions, utilizing frameworks like PyTorch and Scikit-Learn to select suitable architectures—whether decision trees, neural nets, or ensembles—based on performance and client criteria. • Design and implement state-of-the-art generative models for NLP and multimodal tasks, leveraging tools like OpenCV for image preprocessing and Stable Diffusion concepts where applicable. • Champion MLOps best practices within the team, building validated data pipelines and CI/CD/CT workflows using Kubeflow and Vertex AI Pipelines to ensure model quality and integrity. • Collaborate directly with clients to understand their unique needs, translating business challenges into technical solutions and providing expert guidance on dataset management best practices. • Personally tackle the most difficult engineering challenges, identifying technical risks such as overfitting or latency issues, and optimizing hyperparameters to ensure precision and interpretability.

🎯 Requirements

• 7+ years of technical experience, with at least 3+ years focused on ML/AI and 1 year in a consulting capacity. • Experience building and evaluating agentic loops, including tool-use (function calling), self-reflection, and multi-step reasoning architectures. • Deep proficiency in the modern Python AI stack, including extensive experience with core libraries (NumPy, Pandas, PyTorch) and specialized LLMOps/Agentic tools for monitoring and evaluation (e.g., LangSmith, Braintrust, AgentOps, or HoneyHive). • Proven track record of building AI/ML solutions for users, including experience with GenAI common solutions like Vertex AI, OpenAI API, and vector database technologies. • Strong foundation in probabilistic modeling, Bayesian statistics, and experimental design (A/B testing for AI) to ensure model reliability and groundedness. • Excellent verbal and written communication skills, with the ability to confidently articulate complex AI concepts to business, technical, and non-technical stakeholders.

🏖️ Benefits

• Competitive Compensation – Market-aligned salary reflecting your expertise and impact • Remote Work Flexibility – Work in a remote first organization, but can still collaborate at multiple offices globally. • Comprehensive Health Benefits – Medical, dental, vision, and wellness coverage for you and your family. • Flexible Paid Time Off – Take the time you need with a results-focused approach • Professional Development – Work with industry leaders, and learn from the most talented engineers in the industry. • Google Cloud Training & Certifications – Access to leading cloud education resources. • High-Impact Client Work – Enterprise engagements shaping the future of Cloud, Data Platforms, and Agents • Collaborative Culture – Professional, transparent, and team-oriented environment.