Maneva

Mechatronics Engineer

Maneva

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Job Level

Mid-LevelSenior

Tech Stack

ApacheAWSAzureCloudCyber SecurityDockerFlaskGoogle Cloud PlatformGrafanaIoTJavaScriptKafkaLinuxMongoDBNode.jsNumpyPandasPrometheusPythonPyTorchRabbitMQReactScikit-LearnSQLTensorflow

About the role

  • 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

Requirements

  • Degree in Mechatronics, Electrical Engineering, Computer Engineering, Robotics, or related field – or equivalent technical industry experience combining hardware and software expertise
  • Prior industry experience in industrial automation, machine vision, robotics, automotive, or related manufacturing technology fields
  • Proven ability to handle complex projects as both project owner and technical lead, with direct customer engagement for technical coordination and feedback
  • Strong programming skills in Python with experience in production software development and deployment
  • Hands-on experience with Linux systems, command line operations, and system administration
  • Experience with Docker containerization and deployment of applications in production environments
  • Proficiency with computer vision libraries including OpenCV and image processing techniques
  • Familiarity with machine learning frameworks such as TensorFlow and/or PyTorch for model deployment and inference
  • Experience with NumPy and scientific computing libraries for data processing and analysis
  • Experience with NVIDIA Jetson or similar edge computing platforms for AI deployment
  • Experience with electrical wiring design, mechanical system integration, and understanding of manufacturing environments
  • Proven ability to work independently in field environments and manage complex technical deployments
  • Excellent communication skills for technical coordination with both technical and non-technical stakeholders
  • Experience with additional AI/ML frameworks and libraries (ONNX, TensorRT, OpenVINO, scikit-learn, Pandas)
  • Proficiency in additional programming languages (C++, C#, JavaScript/Node.js for web interfaces)
  • Experience with cloud platforms and services (AWS, Azure, GCP) for hybrid edge-cloud deployments
  • Familiarity with embedded systems programming and real-time operating systems
  • Experience with version control systems (Git), CI/CD pipelines, and DevOps practices
  • Knowledge of industrial camera and image transport protocols (GenICam, GigE Vision, USB3 Vision)
  • Experience with PLC integration protocols (Ethernet/IP, Modbus, Profinet, OPC-UA) and industrial control systems
  • Database management experience (SQL, InfluxDB, MongoDB) for data storage and analytics
  • Experience with message queuing systems (MQTT, RabbitMQ, Apache Kafka) for industrial IoT
  • Familiarity with web frameworks (Flask, FastAPI, React) for building operator interfaces and dashboards
  • Experience with monitoring and logging tools (Grafana, Prometheus, ELK stack) for production system management
  • Knowledge of cybersecurity best practices for industrial systems
  • Experience with fleet management and remote device management solutions
  • Background in computer vision algorithms, deep learning model optimization, and edge AI acceleration
  • Prior experience in food & beverage, CPG, automotive, or packaging manufacturing environments
  • Experience in startup environments or cross-functional hardware/software product teams
  • Understanding of lean manufacturing principles and continuous improvement methodologies