Job Description

About The Role

We are seeking a highly skilled Senior Software Engineer with a strong background in full-stack development, particularly in backend technologies and Agentic AI, to join our AI/ML team. This role is pivotal in supporting our AI-driven tool development and R&D initiatives, focusing on operational excellence in cloud environments to facilitate rapid shipping and iteration of machine learning solutions.

What You’ll Do

Sitting in our Engineering team reporting to the AI Tech Lead, during a period of high growth as we focus on scalability and performance of our models and platform working on building out backend infrastructure, optimizing cloud infrastructure to enabling ML team to deploy models more effectively.

• Develop and Maintain AI/ML Systems: Build robust, scalable backend systems that support machine learning operations and data processing pipelines

• Cloud Operations and Management: Oversee and optimize cloud infrastructure to ensure efficient deployment and operation of ML models

• Problem Solving: Independently explore and address complex problem spaces to improve system capabilities and performance without extensive guidance

• Cross-Functional Collaboration: Work closely with ML engineers and data scientists to integrate advanced ML technologies, ensuring seamless operations across various platforms

• Innovation and R&D: Actively participate in research and development of new tools that can enhance our AI capabilities and workflows

What We Need

• Professional Experience: 

  • 5+ years of software engineering experience, with a strong focus on ML engineering and deploying machine learning models in production.

  • Extensive experience in full-stack development, particularly in backend environments that support AI/ML workloads.

• Technical Expertise:

  • Strong proficiency in Python, with deep expertise in LLMs, AI Agents, and ML model development.

  • Experience designing and deploying scalable ML systems, such as retrieval-augmented generation (RAG) pipelines and production-grade AI applications.

  • Extensive experience with cloud platforms (AWS, GCP, Azure) and operational best practices for ML workloads.

  • Familiarity with Kubernetes and other container management tools.

  • Ability to write well-structured, organized code and automated unit/E2E tests.

  • Comfortable with polyglot persistence models (SQL vs. NoSQL).

• ML Operations: Experience with MLOps frameworks and best practices; familiarity with DevOps principles as applied to machine learning models, including model versioning, monitoring, and lifecycle management.

• Problem Solving: Ability to operate independently in unstructured environments, demonstrating a proactive and investigative approach to tackling challenges

• Communication: Excellent communication skills, with the ability to collaborate effectively in dynamic, cross-functional teams, including data scientists, researchers, and software engineers.

What’s In It For You

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: $186,000 - $207,000

For more information on which locations are included in each of our geographic pay tiers, please visit  invisible.co/join-us/pay-zones . However, we recommend confirming the specific tier for your location with your recruiter. 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 all offers. 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.

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