Machine Learning Engineer

Summary

Join Invisible Technologies, a rapidly growing AI training and scaling partner, as a Machine Learning Engineer. You will work on a team developing and deploying ML-powered tools, collaborating with clients and internal stakeholders. This role blends hands-on model development with backend engineering and infrastructure work, requiring experience in software engineering, ML engineering, or data-focused development. You will contribute to building scalable systems, supporting R&D, and ensuring rapid iteration and deployment of machine learning solutions. Invisible offers competitive compensation, bonuses, and equity, and is a remote-first organization.

Requirements

• Professional Experience: 2+ years of experience in software engineering, ML engineering, or data-focused development roles
• Exposure to deploying machine learning models or supporting AI/ML workloads in production environments
• Experience in client-facing roles or comfort working with external stakeholders
• Technical Expertise: Proficient in Python, with experience building ML models or working with frameworks like PyTorch, TensorFlow, or similar
• Solid understanding of core data science concepts, including statistical modeling, hypothesis testing, and data exploration techniques to inform model development and evaluation
• Experience with cloud platforms (AWS, GCP, Azure), and a solid grasp of deployment workflows and infrastructure best practices
• Ability to write clean, modular code and contribute to automated tests (unit, integration, and end-to-end)
• Comfortable working with relational and/or NoSQL databases
• ML Operations: Familiarity with MLOps concepts, including model tracking, monitoring, and versioning
• Understanding of how DevOps principles apply to ML model development and deployment
• Strong communication skills and a collaborative mindset, with the ability to engage effectively across internal teams and external client environments

Responsibilities

• Develop and Maintain AI/ML Systems: Contribute to the development of reliable, scalable backend systems that power machine learning workflows and data pipelines
• Cloud Operations and Deployment: Help manage and improve cloud infrastructure to support efficient model deployment and operational stability in real-world environments
• Technical Problem Solving: Participate in identifying and addressing engineering challenges, including those surfaced through direct client feedback and usage
• Collaborate Across Functions: Work closely with ML engineers, data scientists, and external stakeholders to integrate machine learning capabilities into production systems
• Tooling and R&D Support: Assist in developing internal tools and infrastructure to streamline experimentation, training, and model serving across varied use cases

Preferred Qualifications

• Familiarity with building or supporting production-grade ML systems, such as RAG pipelines or agent-based applications, is a plus
• Familiarity with containerization tools (e.g., Docker, Kubernetes) is beneficial

Benefits

• Compensation: Invisible is committed to fair and competitive pay, ensuring that compensation reflects both market conditions and the value each team member brings. Our salary structure accounts for regional differences in cost of living while maintaining internal equity
• Tier 1: $128,000 - $151,000
• Bonuses and equity are included in offers above entry level
• Remote work