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Home Side Hustle Jobs Senior Machine Learning Engineer

$161,000–$189,000/yr

Senior Machine Learning Engineer

Apply Now
Full-time Remote 25d ago

Location:

New York, NY, US

Company:

Invisible Technologies is the AI training and scaling partner for leading businesses and governments, leveraging human expertise and technology for AI applications.

Summary:

The Senior Machine Learning Engineer will focus on building and scaling backend infrastructure for machine learning operations, optimizing cloud environments, and integrating technologies. Applicants need 5+ years of software engineering experience, deep expertise in full-stack development, and proficiency in Python, particularly related to ML systems.

Requirements:

Technology: Python, AWS, GCP, Azure, Kubernetes

Hard Skills: software engineering, backend systems, model evaluations, finetuning, cloud operations, MLOps frameworks

Credentials: bachelors-degree

Experience: 5+ years of software engineering experience, Extensive experience in full-stack development

Job Description:

Invisible Technologies is the AI training and scaling partner for the leading foundation model providers, enterprises, and governments, bridging the gap between AI potential and production. Invisible’s unique AI Process Platform combines elite global human expertise, cutting-edge technology, and deep institutional knowledge gained by training 80% of the world’s leading AI models. Trusted by AWS, Microsoft, and Cohere, we have an unparalleled ability to operationalize AI for real-world applications. Our explosive growth landed us the #2 spot on the Inc. 5000 in 2024, closing the year on $134m revenue.

About The Role

We’re looking for a Senior Software Engineer with deep expertise in full-stack development with a strong emphasis on backend systems, model evaluations, and finetuning to join our team. In this role, you’ll support our AI-driven tool development and R&D efforts, playing a key part in building scalable systems and driving operational excellence. You'll help ensure our cloud infrastructure enables fast, reliable shipping and iteration of machine learning solutions.

What You’ll Do

You’ll join our Platform Engineering team, reporting to the Senior Engineering Manager of Evaluations & Finetuning, at a pivotal time of rapid growth. In this role, you'll focus on building and scaling backend infrastructure, optimizing cloud environments, and enabling our ML teams to deploy models more efficiently. Your work will play a critical role in improving the scalability, reliability, and performance of our models and overall platform.

  • 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

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.

For this position, the annual salary ranges by location are:

Tier 1

$161,000 - $189,000 USD

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.

What It’s Like to Work at Invisible:

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.

Country Hiring Guidelines:
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.
AI Interviewing Guidelines:
Our hiring team thoughtfully uses AI to support an efficient, engaging, and inclusive interview process. Since AI can also be a helpful tool for candidates, we've outlined expectations for using it ethically throughout your interview journey. Click here to learn more about how we use AI and our guidelines for candidates.

Accessibility Statement:
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 accommodation@invisible.email.

Equal Opportunity Statement:
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.

Apply Now

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