AI Jobs

Benefits:

• Career Progression

• Employee Stock Options

• Diverse and Talented Team

• Fast-Paced Environment

• Impact on the World

Experience Requirements:

• +2 years of experience as a network technician or a similar role.

Other Requirements:

• Educational background in Computer Science, Computer Engineering, or equivalent technical training.

• Proven expertise in configuring wired and wireless networks across multiple devices.

• Strong diagnostic, analytical, and problem-solving skills.

• Good knowledge of LAN/VLAN/WAN networks, TCP/IP protocols, and network technologies.

• Experience with network hardware and common troubleshooting software.

• Excellent communication skills and a collaborative mindset.

• Experience writing activity and intervention reports.

• Fluency in English, both written and verbal.

Responsibilities:

• Network Design: Design VLAN and WLAN network deployment plans tailored to different types of existing infrastructure to support Smartex’s solutions.

• Performance Monitoring: Evaluate and monitor network performance, identifying and resolving bottlenecks to ensure high availability and service efficiency.

• Troubleshooting & Support: Provide technical customer support, troubleshoot issues, and ensure continuous service availability across multiple customer sites.

• Collaboration: Work closely with customers' IT departments, internal installation teams, and engineering to validate and deploy robust networking solutions.

• Hardware Management: Source, validate, and configure network equipment (routers, switches, access points, etc.) compatible with Smartex’s ecosystem. On-Site Interventions: Regularly visit customer facilities to install, support, and validate network deployments and configurations.

Benefits:

• Career Progression

• Employee Stock Options

• Diverse and Talented Team

• Fast-Paced Environment

• Impact on the World

Experience Requirements:

• 7+ years of experience in hardware development of embedded electronics products.

Other Requirements:

• Proven experience in high-speed design.

• Proven experience in analog electronics.

• Proven experience in hardware product certification, namely IEC norms.

• Proven experience in Kicad and LTSpice.

• Proven experience in Linux Systems (Ubuntu/Debian) and Device Trees for Embeeded Systems.

• Excellent verbal and written communication skills in English & Portuguese.

• Fast Learner, ability to learn quickly, adapt to new technologies, and work in a dynamic and fast-paced environment.

• Collaborative mindset and willingness to work closely with team members to achieve shared goals.

Responsibilities:

• Lead the Electrical design for a variety of projects and products.

• Production of detailed schematics for PCBAs with proper & clean annotation and documentation.

• eCAD for PCBAs and layout for power systems, analog & digital electronics, high-speed signalling and routing.

• Testing & validation of sub-systems, circuits, and components using a variety of prototyping and testing techniques.

• Simulation of electrical sub-systems & circuits using LTSpice.

Benefits:

• Career Progression

• Employee Stock Options

• Diverse and Talented Team

• Fast-Paced Environment

• Impact on the World

Experience Requirements:

• 2+ years of experience in web development across both front-end and back-end technologies.

Other Requirements:

• Proficient in frameworks and languages such as Angular, React.js, Node.js, and Python.

• Strong foundation in software engineering principles and coding best practices.

• Hands-on experience writing unit and integration tests to ensure application reliability.

• Familiarity with web accessibility principles, standards, and guidelines.

• Proven ability to work both independently and collaboratively in fast-paced environments.

• Skilled in setting priorities and managing multiple projects with competing deadlines.

• Fluency in English, both written and verbal.

Responsibilities:

• Application Development: Design, develop, and test web applications tailored for industrial environments, ensuring functionality, scalability, and user-centric design.

• Cross-functional Collaboration: Work closely with both front-end and back-end engineers, as well as other stakeholders, to deliver high-quality, reliable software solutions.

• Performance Monitoring: Continuously monitor and analyze the performance of live applications, implementing optimizations at the code level to ensure smooth and efficient operation.

• Issue Resolution: Identify and resolve performance bottlenecks, debug critical issues, and enhance the overall responsiveness and reliability of applications.

Benefits:

• Fast Learning Opportunity

• Internship Grant

• Freedom & Autonomy

• Launch your Career

• Diverse and Talented Team

Education Requirements:

• Currently enrolled in a Bachelor's or Master's degree in a relevant field such as Informatics and Computing Engineering or similar

Other Requirements:

• Proficiency in Python for backend development

• Basic understanding of machine learning concepts, especially in natural language processing and large language models

• Experience with data integration, cleaning, and preprocessing techniques

• Strong analytical skills and the ability to identify and troubleshoot issues efficiently

• Excellent verbal and written communication skills in English to articulate technical concepts and collaborate with team members

• Eagerness to learn new technologies, frameworks, and methodologies

• Ability to work effectively in a collaborative startup environment

Responsibilities:

• Backend Development: Develop and maintain backend systems to integrate LLMs with knitting machine production and quality data

• Data Integration: Collaborate with data engineers and other team members to collect, clean, and preprocess production and quality data for analysis and insights generation

• Frontend Integration: Assist in integrating generated insights into an Angular-based frontend application, ensuring a seamless user experience

• Collaboration: Work closely with cross-functional teams including data scientists, UX/UI designers, and production engineers to ensure the application meets user needs

Benefits:

• Competitive salary and equity grant

• A high-trust, high-impact environment where your voice matters and your work directly shapes the company’s success

Experience Requirements:

• Strong backend development experience in Python and FastAPI

• Familiarity with frontend technologies like React and willingness to contribute to full-stack delivery

• Experience integrating and deploying LLMs, including prompt engineering and fine-tuning

• Background in software architecture and system design

• AWS deployment knowledge, especially using ECS, Fargate, and Docker Hands-on experience with CI/CD pipelines using GitHub Actions SaaS experience, ideally building B2B products that deliver real customer value Solid product thinking—you understand business needs and shape features that deliver outcomes Comfortable managing epics, writing tickets, and coordinating engineering planning via Jira Proven track record in early-stage startups with fast-paced delivery and cross-functional collaboration

Responsibilities:

• Design, build, and maintain robust and scalable backend services using Python and FastAPI

• Deploy and manage applications in AWS using Docker and Fargate

• Own CI/CD pipelines and ensure reliable, high-quality software releases using GitHub Actions

• Translate product features into technical specifications and Jira epics/tickets

• Collaborate across engineering to remove blockers and maintain execution focus Lead the effort to ship our mbue Submittals MVP and support its launch Contribute to our SOC2 Type 2 compliance process and organize deliverables in Sprinto Prototype new features and resolve technical risks through experimentation Foster a culture of high standards, ownership, and continuous improvement

Benefits:

• A unique opportunity to work on cutting-edge AI technology that is revolutionizing the architectural industry. You'll be at the forefront of developing and implementing AI solutions that have a tangible impact on the world, aligning with mbue's vision of a “world built better with fewer errors.

• A chance to grow your (albeit already great) leadership and mentorship abilities. As the first full-time Principal Machine Learning Engineer, you will play a large role in shaping our company.

• Full-time remote position (if you’re based in Austin, TX or New York, that’s a big plus!)

• Competitive salary and equity grant

• A high-trust, high-impact environment where your voice matters and your work directly shapes the company’s success

Education Requirements:

• A degree in Computer Science, Statistics, Machine Learning, or a related field. Advanced degrees are highly desirable.

Experience Requirements:

• Extensive knowledge of and hands-on experience with computer vision and deep learning techniques

• Proven ability to lead and mentor junior ML engineers to bring leading-edge technology to market.

• Demonstrated experience in early-stage startups with mentoring and growing successful teams.

• Proven experience in early-stage startup environments, thriving in dynamic and collaborative settings, while building from the ground up.

• Proficiency in end-to-end model development, validation, and deployment.

Responsibilities:

• Leading the research and development efforts to tackle our toughest problems.

• Establish our overall training and evaluation pipeline for new solutions

• Find incremental solutions to quickly address issues we see with the models in production

• Hands on experimentation with new approaches that will empower for our next generation of capabilities

• Strategic planning with CTO and CEO Running experiments in an environment that prioritizes knowledge-sharing, inclusivity, and trust Coordinating with junior machine learning engineers and software engineers

Responsibilities:

• Own the complete deployment journey - from model customization to serving infrastructure, ensuring our solutions work flawlessly in variable customer environments,.

• Deploy AI systems to solve use cases others can not - implementing solutions that push beyond base LFMs can deliver and redefine what's possible with our technology

• Work alongside our core engineering team to leverage and enhance our powerful toolkit of Liquid infrastructure

Responsibilities:

• Own end-to-end customer relationships from technical discovery through implementation and success validation

• Translate customer use cases into detailed technical implementation plans for the Applied ML Engineering team

• Conduct technical discovery sessions with customers to deeply understand their requirements, constraints, and success criteria

• Build and maintain the technical roadmap for each customer engagement, identifying risks and dependencies early

• Serve as the escalation point for complex technical challenges encountered during implementations

Responsibilities:

• Create and maintain data cleaning, filtering, selection pipeline that can handle audio-text data.

• Watch out for the release of public high quality audio (ASR and SFT) datasets.

• Create and maintain synthetic data generation pipeline to create task-specific audio SFT data.

• Work with the multimodal audio team to run ablations on new dataset.

Responsibilities:

• Strong ML Experience: Proficiency in Python and PyTorch to effectively interface with the ML team at a deeply technical level.

• Hardware Awareness: Must understand modern hardware architecture, including cache hierarchies and memory access patterns, and their impact on performance.

• Optimization of Low-Level Primitives: Responsible for optimizing core primitives to ensure efficient model execution.

• Self-Guided and Ownership: Ability to independently take a PyTorch model and inference requirements and deliver a fully optimized edge inference stack with minimal guidance

Responsibilities:

• Create and maintain data cleaning, filtering, selection pipeline than can handle >100TB of data.

• Watch out for the release of public dataset on huggingface and other platforms.

• Create crawlers to gather datasets from the web where public data is lacking.

• Write and maintain synthetic data generation pipelines.

• Run ablations to assess new dataset and judging pipelines.

Responsibilities:

• Design, develop, and maintain scalable data pipelines for large-scale multimodal and text-based foundation model training.

• Curate, clean, and validate diverse real-world datasets, ensuring high data quality and relevance.

• Develop and optimize data preprocessing models for automated cleaning, augmentation, and filtering.

• Implement robust data evaluation and benchmarking strategies to assess dataset quality and model impact.

• Develop scalable tools and frameworks for data ingestion, transformation, and annotation.

Responsibilities:

• Design and implement high-performance, scalable training infrastructure that efficiently utilizes our GPU clusters for both specialized and large-scale multimodal models

• Build robust data loading systems that eliminate I/O bottlenecks and enable training on diverse multimodal datasets

• Develop sophisticated checkpointing mechanisms that balance memory constraints with recovery needs across different model scales

• Optimize communication patterns between nodes to minimize the overhead of distributed training for long-running experiments

• Collaborate with ML engineers to implement new model architectures and training algorithms at scale

Responsibilities:

• Fine-tune both general-purpose and specialized models to align with specific use-case requirements.

• Design post-training datasets and develop rigorous evaluation frameworks to target and quantify model improvements.

• Participate in post-training research discussions and collaborate with cross-functional teams to translate novel ideas into practice.

Responsibilities:

• Create and maintain data processing, cleaning, filtering, and selection pipeline that can handle image-text data.

• Watch out for the release of public high quality VLM datasets.

• Create and maintain synthetic data augmentation pipeline to enhance VLM data quality.

• Work with the multimodal vision team to run ablations on new dataset.