Machine Learning Engineer

Summary

Join Invisible Technologies, a leading AI training and scaling partner, as a Machine Learning Engineer. You'll work on a team focused on building and deploying ML-powered tools that solve real-world problems. This role combines hands-on model development with backend engineering and infrastructure work, requiring you to build scalable systems, support R&D initiatives, and ensure rapid iteration and deployment of machine learning solutions in production environments. You'll contribute to the development of reliable, scalable backend systems, manage cloud infrastructure for efficient model deployment, participate in technical problem-solving, collaborate with ML engineers and data scientists, and assist in developing internal tools and infrastructure to streamline experimentation, training, and model serving.

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
• An Invisible Talent Acquisition Partner can provide more information on which locations are included in each of our geographic pay tiers during the interview process
• For candidates outside the U.S., compensation will be adjusted to reflect local market conditions and cost-of-living differentials
• Bonuses and equity are included in offers above entry level
• Final compensation is determined by a combination of factors, including location, job-related experience, skills, knowledge, internal pay equity, and overall market conditions
• Because of this, every offer is unique
• Additional details on total compensation and benefits will be discussed during the hiring process
• At Invisible, we’re not just redefining work—we’re reinventing it
• We operate at the intersection of advanced AI and human ingenuity, pushing the boundaries of what’s possible to unlock productivity and scale
• Ownership is at the core of everything we do
• Here, you won’t just execute tasks—you’ll build, innovate, and shape the future alongside world-class clients pushing the boundaries of AI
• We expect bold ideas, relentless drive, and the ability to turn ambiguity into opportunity
• The pace is fast, the challenges are big, and the growth is unmatched
• We’re not for everyone, and we’re okay with that
• If you’re looking for predictable routines, this isn’t the place for you
• But if you’re driven to create, thrive in dynamic environments, and want a front-row seat to the AI revolution, you’ll fit right in
• Invisible is a remote-first organization and hires new team members in countries around the world
• Although many of our roles are fully remote, some roles may carry specific location-based eligibility requirements
• Our Talent Acquisition team can help answer any questions about location after starting the recruiting process
• We’re committed to providing reasonable accommodations for individuals with disabilities
• If you need assistance or accommodation due to a disability, please contact our Talent Acquisition team during the recruitment process at [email protected]
• We’re an equal opportunity employer
• All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or veteran status, or any other basis protected by law
• Due to a high volume of candidates, Invisible may use automated decision-maker technologies to filter candidates based on response to our application questions and other provided information
• Our use of automated decision-making enables us to be efficient by providing a manageable list of possible candidates that meet our mandatory hiring criteria
• If you object to our use of automated decision-making please contact us