Machine Learning Solutions Architect in Provectus

Provectus helps companies adopt AI to transform how they operate, compete, and drive value. The company focuses on building ML Infrastructure to drive end-to-end AI transformations, assisting businesses in adopting suitable AI use cases, and scaling their AI initiatives organization-wide in such industries as Healthcare & Life Sciences, Retail & CPG, Media & Entertainment, Manufacturing, and Internet businesses.Join us if you have the same passion for making products using AI/ML technologies, cloud services, and data engineering. Join us if you value a friendly corporate environment and almost a family-driven approach to every employee.Join us if you want to grow professionally and be ready to learn new things constantly.As an ML Solution Architect, you’ll be provided with all opportunities for development and growth.Responsibilities:Provide technical support on pre-sales and sales calls with new customers, including investigating business problems, representing Provectus technical expertise, and offering solutions. Conduct and drive technical workshops for new and existing customersCreate machine learning solutions, including problem framing, exploratory data analysis, dataset preparation, model & algorithm development, model training & evaluation, model deployment, monitoring, and maintenanceImplement architecture to deploy machine learning pipelines and CI/CD processesEstimate development, maintenance, and other costs for the proposed solutionsAct as a technical liaison between customers and teams to provide customer-driven product improvement feedbackStay abreast of new tools, packages, and Machine Learning techniques while consistently pushing the limit of what is possible to deliver the best solutions for clientsEvangelize ML services and share best practices through blogs, white papers, reference architectures, public-speaking events, etcRequirements:Experience in designing and implementing models or machine learning algorithms in production, including problem framing, exploratory data analysis, dataset preparation, model & algorithm development, model training & evaluation, model deployment, integration, monitoring, and maintenanceConsulting experience and track record of helping customers with their AI needsAbility to lead exploratory data analysis within new subject matter experts or new data sourcesStrong knowledge of Python – able to write production-level code that is well-written and explainableExperience with SQL, NumPy, pandas, scikit-learn, HuggingFace transformers, and MLFlowKnowledge of MLOps or CI/CD best practicesPreferred skills:Industrial experience with LLM and related frameworks (LangChain, LLamaIndex, etc.)Practical experience with AWS (or alternatives from other major clouds): Amazon SageMaker Amazon Redshift, EMR, or Glue Core services: S3, networking, IAM, ECRKnowledge of Apache Spark or Ray frameworkPractical experience with at least one deep learning framework like PyTorch or TensorFlow Show more Show lessPosition level Not applicable Type of employment Full-time Job responsibilities Finance and Consulting Industries Financial services and Hospitals and health care