Maneva

AI Engineer

• Develop and train vision-based AI applications for manufacturing, including classification, object detection, and segmentation tasks
• Build and manage pipelines for deploying AI/ML models in production environments
• Set up and integrate new tools to streamline and support MLOps workflows
• Monitor and optimize the performance of deployed models, ensuring they meet operational requirements
• Debug, troubleshoot, and update AI models as needed to maintain high reliability and performance
• Collaborate with cross-functional teams to align AI applications with manufacturing requirements
• Leverage cloud platforms (AWS, Azure, GCP) for scalable training compute and deployment solutions
• Maintain and document processes to ensure reproducibility and operational excellence
• May occasionally require to travel to customer sites to support integration and deployment efforts

Technical Project Manager

• As an Engineering Project Manager at Maneva, you'll be the strategic orchestrator ensuring optimal utilization of our engineering resources across multiple concurrent AI vision system deployments. You will drive engineering prioritization, manage project timelines, and serve as the critical bridge between our technical teams and customer success organization. Your deep understanding of industrial engineering and machine vision systems will enable you to make informed resource allocation decisions while maintaining technical credibility with both internal teams and external customers.
• Key Responsibilities:
• Optimize engineering resource allocation across multiple concurrent customer projects, balancing team capacity, skill sets, and project priorities
• Develop and maintain engineering capacity planning models to forecast resource needs and identify potential bottlenecks across the project portfolio
• Lead weekly engineering resource allocation meetings with technical leads to review project status, adjust priorities, and resolve resource conflicts
• Create and manage engineering project roadmaps with clear dependency mapping, critical path analysis, and resource requirements
• Implement resource utilization tracking and metrics to continuously improve team efficiency and project delivery performance
• Coordinate cross-functional engineering teams including vision engineers, software developers, hardware specialists, and field technicians
• Establish realistic project timelines based on technical complexity, resource availability, and customer requirements
• Monitor and track project milestones across all active deployments, proactively identifying and mitigating schedule risks
• Facilitate project planning sessions with engineering teams to break down complex deployments into manageable work packages
• Manage project interdependencies and coordinate sequencing across multiple customer implementations
• Conduct regular project health assessments and implement corrective actions to keep projects on track
• Maintain project documentation including scope changes, timeline adjustments, and lessons learned
• Partner closely with Customer Success team to translate technical project status into clear customer communications
• Provide technical expertise for customer discussions around timeline expectations, milestone definitions, and project scope
• Participate in customer calls to discuss project progress, address technical concerns, and manage expectation alignment
• Prepare executive-level project dashboards showing portfolio health, resource utilization, and delivery forecasts
• Escalate and resolve project issues that impact customer satisfaction or delivery commitments
• Support pre-sales technical discussions by providing realistic delivery timeline estimates and resource requirements
• Develop and refine project management processes specifically tailored for AI vision system deployments
• Analyze project data to identify patterns, bottlenecks, and opportunities for process improvement
• Lead retrospectives and post-project reviews to capture learnings and optimize future project execution
• Build forecasting models for engineering capacity planning and project pipeline management
• Collaborate with leadership on strategic resource planning and team scaling decisions

Engineering Project Manager

Engineer

• About Maneva: Maneva, a startup founded by an ex-Google Deepmind researcher, is an AI service provider revolutionizing manufacturing operations with cutting-edge AI solutions for autonomous factory operation and optimization.
• What You'll Do: As a Mechatronics Engineer at Maneva, you'll be the full-stack technical leader driving the complete integration of AI-powered systems into manufacturing environments, designing, installing, and integrating machine vision systems and owning production software implementation.
• Travel: Up to 50% (35%+ in territory, 15%+ out-of-territory), including travel across North America.
• Key Responsibilities:
• Take project ownership and architect end-to-end customer projects from design proposal through implementation and ongoing software maintenance, ensuring seamless integration of hardware and software systems
• Design and orchestrate AI vision system implementations by analyzing application requirements and generating hardware BOM for camera, lens, lighting, and compute component sourcing
• Develop, deploy, and maintain production software applications on Linux-based edge devices, including AI inference pipelines, image processing workflows, and system monitoring solutions
• Design and integrate AI vision systems with PLCs and existing industrial automation infrastructure, implementing robust software interfaces for real-time communication and control
• Communicate regularly with customers and internal stakeholders throughout the entire project lifecycle, providing technical leadership on both hardware and software aspects
• Deploy and maintain containerized applications using Docker, manage software updates, and ensure system reliability in production environments
• Navigate onsite networking, configure edge computing infrastructure, and implement secure, scalable software architectures
• Design signal integration and wiring for communication with sensors, I/O, and control systems while developing corresponding software drivers and interfaces
• Implement and maintain AI model deployment pipelines, including data preprocessing, real-time inference, and post-processing workflows using computer vision and machine learning frameworks
• Support plant walk-throughs and site assessments to identify high-impact AI use cases in the pre-sales process, providing technical expertise on both feasibility and implementation approaches
• Provide onsite support for data collection efforts in live production environments and develop software tools for training data management and model iteration
• Troubleshoot complex hardware-software integration issues and rapidly iterate on deployments based on real-world operational results
• Deliver comprehensive training to plant operators and managers on both system operation and software interfaces
• Document deployment configurations, software architectures, system performance metrics, and maintain technical documentation for internal use and customer value stories