Mid/Senior AI Engineer

<p>We are building a pipeline of talented Machine Learning Engineers for upcoming projects at TensorOps. While we may not have an immediate opening, we are continuously growing and would love to connect with strong candidates for future opportunities.</p> <p>If you are passionate about ML systems, GenAI, and production-grade deployments, we’d love to hear from you.</p> <h2><strong>About the role</strong></h2> <p>We’re looking for Machine Learning Engineers who enjoy building practical, production-ready AI systems and collaborating on meaningful projects.</p> <p>In this role, you will:</p> <ul> <li>Take ownership of key components within ML and GenAI projects, with support from senior team members when needed<br><br></li> <li>Contribute to architectural and technical decisions in a collaborative environment<br><br></li> <li>Build scalable ML systems that move from experimentation to real-world application<br><br></li> <li>Work with international clients to understand requirements and implement thoughtful technical solutions<br><br></li> <li>Support and mentor junior team members as you grow in your own leadership journey<br><br></li> </ul> <p>You’ll be part of a supportive, fast-growing team that values autonomy, open communication, and continuous learning.&nbsp;</p> <h2><strong>Technical Expertise</strong></h2> <p>We’re looking for engineers with strong hands-on experience across:</p> <ul> <li><strong>Python</strong>: Writing clean, efficient, well-documented, production-quality code<br><br></li> <li><strong>Machine Learning Frameworks</strong>: Designing, training, optimizing, and deploying models independently (e.g., PyTorch, TensorFlow, Scikit-learn)<br><br></li> <li><strong>GenAI &amp; LLM Systems</strong>: Building RAG pipelines, chatbot architectures, and applications using tools like LangChain<br><br></li> <li><strong>MLOps &amp; Production ML</strong>: Model versioning, monitoring, CI/CD for ML workflows<br><br></li> <li><strong>Cloud Deployments</strong>: Deploying and scaling ML systems on AWS, GCP, or Azure<br><br></li> <li><strong>Performance Optimization &amp; Debugging</strong>: Diagnosing complex issues and improving system reliability and efficiency<br><br></li> </ul> <p><strong>Requirements</strong>&nbsp;</p> <ul> <li><strong>2+ years of professional experience</strong> in Machine Learning, AI Engineering, or a related role</li> <li>Proven experience building and deploying ML models in production environments</li> <li>Experience working with stakeholders or clients is a plus</li> <li>Bachelor’s degree in Computer Science, Mathematics, Physics, Engineering, or a related field</li> <li>Master’s degree in AI, Machine Learning, Computer Science, or a related field is a strong plus</li> <li>Equivalent practical experience building and deploying production ML systems will also be considered<br><br></li> </ul> <h2><strong>What We Offer</strong></h2> <ul> <li><strong>100% Remote Work</strong>: Work from anywhere with flexibility and autonomy</li> <li><strong>Dynamic, High-Impact Projects</strong>: Work on cutting-edge ML and GenAI solutions across diverse industries</li> <li><strong>International Clients</strong>: Collaborate with global organizations and solve real-world challenges at scale</li> <li><strong>Urban Sports Club Membership</strong>: Supporting your physical and mental wellbeing</li> <li><strong>Monthly Bolt Credits</strong>: For rides</li> <li><strong>Company Events &amp; Offsites</strong>: Regular team gatherings to connect, collaborate, and celebrate</li> </ul>