[Hiring] Sr. AI/ML Engineer @CloudWerx, Inc.

Role Description

As a Senior AI/ML Engineer, you will lead the design and deployment of high-impact AI solutions, expertly bridging traditional predictive modeling with next-generation Agentic AI.

• Collaborate directly with clients to understand their needs and translate business challenges into technical solutions.
• Oversee dataset quality for model training and leverage GCP for efficient model deployment and scaling.
• Utilize the Google AI ecosystem (Vertex AI, Google ADK) and orchestration frameworks like LangChain/LangGraph.
• Architect and implement sophisticated multi-agent systems and autonomous workflows leveraging the Google AI SDK, LangGraph, and LangChain.
• Lead the design and construction of cloud-native solutions using Terraform, Kubernetes, and Docker.
• Apply rigorous statistical evaluation frameworks to model performance, including uncertainty estimation, calibration, and robust hypothesis testing.
• Lead the development of custom predictive models and deep learning solutions using frameworks like PyTorch and Scikit-Learn.
• Design and implement state-of-the-art generative models for NLP and multimodal tasks.
• Champion MLOps best practices within the team, building validated data pipelines and CI/CD/CT workflows using Kubeflow and Vertex AI Pipelines.
• Personally tackle difficult engineering challenges, identifying technical risks and optimizing hyperparameters.

Qualifications

• 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, self-reflection, and multi-step reasoning architectures.
• Deep proficiency in the modern Python AI stack, including extensive experience with core libraries (NumPy, Pandas, PyTorch).
• Proven track record of building AI/ML solutions for users, including experience with GenAI common solutions.
• Strong foundation in probabilistic modeling, Bayesian statistics, and experimental design.
• Excellent verbal and written communication skills, with the ability to articulate complex AI concepts to various stakeholders.

Requirements

• Google Cloud: Professional Machine Learning Engineer certification.
• Industry certifications such as Databricks Certified Machine Learning Professional or DeepLearning.AI Generative AI Specialization.
• Education in Computer Science, Mathematics, or Machine Learning/Data Science.

Benefits

• Competitive Compensation – Market-aligned salary reflecting your expertise and impact.
• Remote Work Flexibility – Work in a remote-first organization with global collaboration opportunities.
• 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 talented engineers.
• 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.