ML Solution Architect

October 25

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Provectus

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Mobile applications • DevOps • Enterprise Software • R&D • eCommerce

501 - 1000

Description

• Provectus helps companies adopt ML/AI to transform their operations. • Focus on building ML Infrastructure for AI transformations across various industries. • Responsible for designing and implementing scalable cloud-based data and ML architectures. • Collaborate with teams to build solutions in Big Data, machine learning, and real-time analytics. • Deliver innovative solutions while adhering to best practices in architecture and security. • Provide strategic technical leadership on high-impact customer engagements. • Design advanced technical solutions and manage technical risks. • Drive innovation, optimize customer KPIs, and mentor technical leaders.

Requirements

• 7+ years of experience in solutions architecture, with a strong focus on Big Data and cloud platforms (AWS, GCP, Azure). • Excellent communication and problem-solving skills, with the ability to work across multiple projects and the ability to articulate complex technical concepts to both technical and non-technical audiences. • Technical sales or pre-sales experience with cloud and big data and ML solutions. • Strong leadership and team collaboration abilities. • Strategic thinking with a focus on delivering measurable business value. • Proven ability to build strong relationships with customers and act as a trusted advisor. • Proficiency in data engineering and analytics, designing data pipelines and architectures using AWS, GCP or Azure data stack • Strong understanding of AI/ML concepts and experience integrating AI/ML components into solutions. • Proven experience with data lakes, data warehouses, and real-time data analytics. • Proficiency in Java, Python, and modern data technologies like Snowflake and Databricks. • Solid understanding of machine learning and MLOps tools (TensorFlow, PyTorch, SageMaker). • Demonstrated ability to lead and mentor cross-functional teams. • Familiarity with agile methodologies. Nice to Have: • Experience in Generative AI implementations. • Proficiency with graph databases (Neo4j, AWS Neptune). • Hands-on experience with Kubernetes, Docker, and containerized applications. • Knowledge of data mesh principles and data contracts. • Operational knowledge of infrastructure deployment tools like AWS CDK, CloudFormation, and Terraform.