Who we are:
Revelio Labs provides workforce intelligence. We absorb and standardize hundreds of millions of public employment records to create the world’s first universal HR database, allowing us to see current workforce composition and trends of any company. Our customers include investors, corporate strategists, HR teams, and governments.
What we’re looking for:
Revelio Labs is looking for an experienced MLOps Engineer to collaborate closely with the modeling team on maintaining and optimizing models in production. You will implement best engineering practices for new modeling projects, and ensure production quality operation of diverse model architectures, including LLMs, Transformers (BERT, etc.), time series models, neural networks, and Bayesian models. The ideal candidate will bring technical expertise in optimizing models for high uptime, inference speed, and scalability while developing infrastructure for deployment, integration, and monitoring.
Essential Skills:
- Experience in ML engineering, DevOps, MLOps, or related roles
- Proficiency in Python and SQL
- Experience with CI/CD tools (e.g., GitHub Actions, Jenkins, Argo CD)
- Experience with containerization and orchestration tools (e.g., Docker, Kubernetes, Argo Workflows)
- Proficiency with cloud platforms (e.g., AWS)
- Familiarity with NLP/ML/Deep Learning frameworks (e.g., PyTorch, scikit-learn, spaCy, HuggingFace)
Preferred Skills:
- Experience with monitoring systems (e.g., Prometheus, Grafana)
- Previous experience as a data scientist or ML engineer working with textual datasets
Responsibilities:
- Collaborate with the modeling and data engineering teams to monitor model performance, detect drift, and ensure stability in production
- Optimize existing models and resources to achieve high uptime, low latency, and efficient inference speeds
- Own model endpoint deployment for the Revelio Dashboard and other client products
- Implement and maintain automated tools and pipelines to streamline the model development and deployment process
- Automate model monitoring workflows to detect performance issues and drift concerns.
Location:
Our offices are based in New York City, but the position can be done remotely.
Salary:
The pay range for this position in New York City is $120,000 - $180,000 per year. The salary range for performing this role outside of New York City may differ. Base pay offered may vary depending on job-related knowledge, skills, and experience. Additionally, you may be eligible to participate in our company’s equity program, plus benefits, including medical, dental, vision, retirement, and other. The range above is for the expectations as laid out in the job description, however we are often open to a wide variety of profiles, and recognize that the person we hire may be more senior or have different experience than this job description as posted. If that ends up being the case, the updated salary range will be communicated to you as a candidate.
Why you should work with us:
We are working on some of the most challenging and cutting-edge data science problems. You will work with a team of PhD data scientists with advanced domain expertise. Our startup is small and growing quickly, with enormous potential for growth.
How you should reach us:
Please email your resume to [email protected] as a PDF file. Please include your GitHub and highlight any projects that you’ve worked on that may be relevant.
