Role Description We are looking for a savvy Machine Learning/Data Engineer to join our growing team of data experts. The hire will be primarily responsible for AI/ML projects on AWS, leveraging native services as well as custom-built models to deliver predictive insights to our customers. In addition, this hire will also support migrating to the cloud, optimizing our customers’ databases and data flows, and enriching our operational and functional data flow with AI/ML algorithms. The ideal candidate is confident in data in any form or scale and happy to learn and teach new data tools. The candidate enjoys optimizing data systems and building them from the ground up. The Machine Learning Engineer will support new system designs and migrate existing ones, working closely with solutions architects, project managers, and data scientists. They must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products. The right candidate will be excited by the prospect of optimizing or re-designing our customers’ data architecture to support our next generation of products and data initiatives, and machine learning systems. Responsibilities - Keep our customers’ data separated and secure to meet compliance and regulations requirements. - Design, Build and Operate the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and cloud (mainly AWS) migration and ‘big data’ technologies. - Optimize various RDBMS engines in the cloud and solve customers' security, performance, and operation problems. - Design, Build and Operate large, complex data lakes that meet functional / non-functional business requirements. - Optimize various data types ingestion, storage, processing, and retrieval from near real-time events and IoT to unstructured data as images, audio, video and documents, and in between. - Use Jupyter Notebooks to build and deploy ML models. - Leverage AWS AI/ML pre built solutions to accelerate work for customers. - Work with customers and internal stakeholders, including the Executive, Product, Data, Software Development, and Design teams, to assist with data-related technical issues and support their data infrastructure and business needs. Qualifications - 3+ years of experience in a Data Scientist/Machine Learning Engineer role. - Bachelor's (Graduate preferred) degree in Computer Science, Mathematics, Informatics, Information Systems, or another quantitative field. - Experience with big data tools: Spark, ElasticSearch, Hadoop, Kafka, Kinesis etc. - Experience with relational SQL and NoSQL databases, such as MySQL or Postgres and DynamoDB or Cassandra. - Experience with AWS cloud services: EC2, RDS, EMR, Redshift etc. - Experience with functional and scripting languages: Python, Java, Scala, etc. - Experience with various ML models for classification, scoring and more. - Experience with Deep Learning Neural Networks (Convolution, NLP etc.) - Experience with AWS AI/ML Services. - Experience with Python coding. - Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. - Experience building and optimizing ‘big data’ data pipelines, architectures and data sets. - Strong analytic skills related to working with unstructured datasets. - Build processes supporting data transformation, data structures, metadata, dependency and workload management. - Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores. - Experience supporting and working with external customers in a dynamic environment. Certifications - AWS Machine Learning Specialty (Strongly Preferred) - AWS Solutions Architect - Associate (Strongly Preferred) Benefits - Our team inspires progress in each other and in our customers through our relentless pursuit of excellence; you will work with leaders who promote learning and personal development. - AllCloud is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, provincial, or local law.

• Lead controls design and execution across multiple material handling projects • Develop electrical designs including field device layouts, control panel designs, and electrical schematics using AutoCAD Electrical or EPLAN • Select components, design control networks, develop BOMs, and validate equipment selections • Program PLCs and develop HMI/SCADA solutions • Commission and debug systems on-site; support testing, startup, and validation activities • Provide technical support during installation and perform field troubleshooting as needed • Deliver projects on time, within scope, and to customer expectations • Contribute to the development and maintenance of controls standards, templates, and reusable code libraries • Lead or support R&D efforts and internal initiatives to expand controls capabilities • Partner with vendors to evaluate and implement new technologies • Identify value-engineering opportunities without compromising system performance • Serve as a senior technical contributor on cross-functional project teams (Project Management, Mechanical, Field, etc.) • Mentor junior engineers and actively share knowledge across the Controls team • Participate in controls team initiatives, process improvements, and tool development • Support recruiting efforts and provide feedback on technology and software vendors • Communicate clearly and proactively with project teams and leadership • Represent DCS professionally during site visits, customer meetings, and supplier interactions • Contribute to a collaborative, accountable team culture • Participate in weekly controls meetings and internal training sessions

• Lead and manage ETL migration processes across multiple concurrent projects, ensuring robust data pipeline development and timely project delivery. • Develop and maintain efficient extraction, transformation, and loading scripts, utilizing Python, SQL, and related data engineering tools to ensure high-quality data migrations. • Implement feedback-driven improvements from clients and internal teams, enhancing data conversion quality, performance, and reliability. • Actively contribute to data quality assurance processes and review datasets for accuracy, completeness, and consistency. • Conduct in-depth analysis and profiling of diverse source database schemas (including relational and non-relational legacy systems) to accurately map and facilitate successful data extraction and migration. • Collaborate closely with the broader Client Experience team to seamlessly integrate client data into SpryPoint products, enabling smooth and timely go-live processes. • Work with the Data Conversion team to establish and promote best practices, create documentation, and drive continuous improvement in data migration processes, automation, and observability. • Actively participate in daily standups and weekly review sessions, clearly communicating progress, raising blockers, and incorporating feedback to continuously improve data engineering tasks and processes.

Role Description We’re looking for a Product Engineer to join our Accounting and Ledger team and work on core parts of the Xolo platform. You will help build and maintain systems that power our general ledger, VAT and tax reporting, regulatory submissions, period close and other key accounting activities. You will automate compliance so entrepreneurs across Europe stay penalty-free without getting buried in paperwork. This role suits someone who enjoys taking ownership, thinking through real-world problems, and building reliable systems in a product-focused startup environment. We are especially interested in engineers who have experience with accounting, tax, ledger, or other financial and compliance systems where correctness, reliability, and regulatory accuracy matter. As a Product Engineer at Xolo, you will: - Design, build, and maintain backend and frontend systems that power our core platform. - Deliver solutions via API to UX with workflow automation as the default mental model. - Take full ownership of end-to-end solutions from understanding the problem and success metrics to implementation, monitoring, and continuous improvement. - Work with Product, Design, and key stakeholders to translate accounting, tax, and regulatory requirements into scalable product experiences. - Build and maintain integrations with tax authorities and regulatory filing systems, while considering reliability, security, and operational constraints. - Build and maintain reconciliation and period-close workflows, ensuring ledgers stay balanced and books close accurately and on time. - Make technical decisions that balance security, performance, quality, and long-term maintainability. - Contribute to improving observability, system reliability, and engineering practices across the platform. - Stay curious about emerging technologies, including AI-assisted engineering workflows and developer tooling. Qualifications - Proven professional experience working with Java and the Spring Boot framework in production environments. - Experience with Python and React is a strong plus. - You have proven experience building products in accounting, tax, ledger, financial reporting, or other regulated financial environments. - Hands-on experience with accounting or ledger systems and designing and delivering regulatory or tax-authority filing integrations. - Solid understanding of double-entry accounting, VAT, and tax-reporting concepts, including their practical benefits, tradeoffs, and constraints (e.g. e-invoicing and SII-style filing). - You are confident with SQL and designing database schemas that perform well under real user load. Experience with PostgreSQL is a plus. - You enjoy working in startup and scale-up environments with evolving priorities and a high level of ownership. - You think beyond implementation details and care about how your work impacts customers and the business - you are outcome-oriented. - Interest in AI tools and how they can improve engineering workflows and products. Requirements - Exposure to AI, Machine Learning, or data science concepts in a product engineering environment is nice to have. - Experience building or experimenting with AI-powered features or automations is a plus. - Proven contributions to engineering excellence and developer experience. - Experience with AWS (or another major cloud provider) and are interested in deepening your understanding of infrastructure, networking, CI/CD, and containers. Benefits - A team of Mavericks: We aspire to challenge the norm by encouraging bold thinking and embracing the unconventional. - We run like Clockwork: Our processes are designed to be smart, efficient, and finely tuned. - Our Big-hearted nature: You’ll work alongside mission-driven individuals who lead with empathy.