• Implements tactical and operational goals focused on software build, release, deployment, and configuration management, ensuring seamless application delivery. • Contributes to the implementation of new automation frameworks, CI/CD pipelines, testing methodologies, and deployment standards. • Manages software deployment projects and operational processes, coordinating release schedules, dependency tracking, and integration workflows. • Works on diverse, multifaceted challenges where analysis requires evaluating software performance, system compatibility, and implementation risks. • Derives solutions based on limited precedent, applying best practices in release engineering, infrastructure automation, and software quality assurance to maintain stability and efficiency. • Communicates regularly with internal stakeholders, including development, QA, IT operations, and product teams, as well as external vendors and cloud service providers to ensure timely implementation and support. • Act as a subject matter expert for Tulip and HighByte within the organization. • Design and implement end-to-end data flows – to and from shop floor to ERP’s and Digital Manufacturing Platforms (Tulip) • Troubleshoot and resolve integration issues, including Industrial Data Ops platform (Highbyte) • Ensure compliance with security and data governance standards • Provide training, documentation, and ongoing support to operations and engineering teams. • Partner with manufacturing teams to identify opportunities for digital process improvements. • Stay current with Industry 4.0 trends, low-code MES platforms, and edge integration technologies. • Support the deployment and configuration of the Tulip platform across manufacturing sites. • Configure and manage Tulip connectors for system integrations (ERP, PLM, QMS, etc.). • Support process engineers in charge of the development of the Tulip apps, dashboards, and workflows to support operations, quality, and maintenance. • Support end users in leveraging Tulip for day-to-day activities. • Configure and manage data models, pipelines, and contextualization in HighByte. • Set up and maintain connectors for OT and IT systems (PLC, SCADA, historians, ERP, MES). • Ensure secure, reliable, and scalable data flows between the Tulip platform and the enterprise applications and the UNS layer. • Collaborate with operations and engineering teams to identify new integration use cases.

• Model Li-ion battery-based energy storage subsystems, including state machines, closed-loop controls, and related building blocks. • Collaborate with systems and controls engineering teams to develop physics-based models, simulate system performance, and validate lab and field data. • Support DevOps in packaging and deploying system models for customer-facing applications. • Analyze large volumes of time-series data to identify patterns, validate assumptions, and derive actionable insights. • Participate in Agile software development practices, contributing to design reviews, sprint planning, and iterative releases. • Produce high-quality documentation and communicate effectively across technical and non-technical teams.

• design, implementation, and support of SailPoint IdentityIQ (IIQ) solutions • lead complex integration and automation initiatives across enterprise environments • troubleshoot production issues effectively • collaborate with internal teams to ensure successful implementation of solutions • ensure compliance with all policies and standards

Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves While each project involves unique tasks, contributors may: - Design graduate- and industry-level automotive engineering problems grounded in real practice; - Evaluate AI-generated solutions for correctness, assumptions, and engineering logic; - Validate analytical or numerical results using Python (NumPy, SciPy, Pandas); - Improve AI reasoning to align with first principles and accepted engineering standards; - Apply structured scoring criteria to assess multi-step problem solving. What we look for This opportunity is a good fit for automotive engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  - Degree in Automotive Engineering or related fields, e.g. Mechatronics, Manufacturing Engineering, Mechanical Engineering, Aerospace Engineering, etc. - 3+ years of professional automotive engineering experience - Strong written English (C1/C2) - Strong Python proficiency for numerical validation - Stable internet connection  Professional certifications (e.g., PE, CEng, PMP) and experience in international or applied projects are an advantage. How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $55 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.