Senior Machine Learning Engineer

About Us:
DailyPay is transforming the way people get paid. As a worktech company and the industrys leading on demand pay solution DailyPay uses an award-winning technology platform to help Americas top employers build stronger relationships with their employees. This voluntary employee benefit enables workers everywhere to feel more motivated to work harder and stay longer on the job while supporting their financial well-being outside of the workplace.
DailyPay is headquartered in New York City with operations throughout the United States as well as in Belfast. For more information visit DailyPays Press Center.

We are seeking a Senior Machine Learning Engineer to join our AI & ML team in New York City. You will play a key role in maturing and scaling our machine learning infrastructure ensuring the reliability performance and scalability of ML models in production. This role requires deep hands-on experience with MLOps principles cloud infrastructure and a track record of delivering robust ML systems in a fast-moving environment.

You will work closely with data scientists engineers and product stakeholders to deliver high-quality ML solutions that directly impact DailyPays core products. You are expected to operate with significant autonomy: defining work identifying dependencies and raising the bar for the team around you.

• Platform Ownership: Help architect and build DailyPays unified ML platform - a unified system for model development deployment and monitoring that serves as the backbone for every AI and ML capability at the company.

• MLOps Architecture & Delivery: Design and implement scalable ML pipelines covering model training deployment monitoring and retraining. Own the delivery of end-to-end MLOps solutions with minimal oversight.

• Cloud Infrastructure: Manage and optimize AWS infrastructure for machine learning workloads balancing cost-effectiveness security and availability.

• CI/CD Pipeline Development: Build and maintain robust CI/CD pipelines for continuous integration and deployment of ML models and related infrastructure.

• Monitoring & Observability: Design monitoring and alerting systems for ML infrastructure and models using tools like Datadog. Proactively identify and resolve issues before they impact production.

• Technical Leadership: Lead design discussions contribute to architectural decisions and establish team norms for how ML systems are built tested and maintained. Help identify and remove blockers.

• Mentorship: Mentor junior engineers. Share domain knowledge and help build genuine technical depth on the team.

• Security & Compliance: Approach all engineering work with a security lens. Actively look for vulnerabilities in code and during peer reviews. Ensure ML pipelines handle sensitive data in accordance with company policy.

• 5 years of experience in machine learning engineering MLOps or data engineering

• Strong cloud platform proficiency: AWS preferred (SageMaker Lambda S3 EC2 IAM ECS) or equivalent GCP (Vertex AI Cloud Functions GCS Compute Engine Cloud Run) or Azure (Azure ML Functions Blob Storage VMs AKS) experience

• Proficiency in Python and experience with ML frameworks (scikit-learn TensorFlow PyTorch)

• Solid CI/CD experience: GitHub Actions or equivalent; designing and operating deployment pipelines

• Experience with infrastructure-as-code (Terraform or CloudFormation)

• Knowledge of event streaming platforms (Apache Kafka or equivalent)

• Experience with monitoring and observability tooling (Datadog Prometheus or Grafana)

• Strong SQL skills and experience with data pipeline tooling (dbt Glue Snowflake)

• Excellent communication skills; comfortable working across data science engineering and product teams

• Experience with containerization and orchestration (Docker Kubernetes)

• Familiarity with microservices architecture and RESTful API design

• Experience in fintech or regulated industries

• Contributions to open-source ML or MLOps projects

High-performing cultures arent built in silos they thrive on partnership. At DailyPay we Commit Together to an inclusive professional environment where multifaceted perspectives are our greatest competitive advantage. We recognize that our team members dont live single-issue lives and we lean into the wide-ranging backgrounds and life stages that sharpen our collective decision-making.

In our high-trust environment we empower you to Challenge Norms. Weve created a space where it is safe to ask difficult questions disrupt the status quo and share bold perspectives without fear of professional fallout. We believe that by checking our own assumptions and staying curious about the experiences of others we arrive at better more innovative results.

We provide the space for you to do your best work through peer advocacy and transparent career development. If you are looking for a culture that values intellectual honesty celebrates the unique lived experiences of its people and thrives on collective success youll find it here.

If you require reasonable accommodation for any aspect of the recruitment process please send a request to . All requests for accommodation will be addressed as confidentially as practicable.

DailyPay is an equal opportunity employer. All qualified applicants will receive consideration without regard to race color religion or creed alienage or citizenship status political affiliation marital or partnership status age national origin ancestry physical or mental disability medical condition veteran status gender gender identity pregnancy childbirth (or related medical conditions) sex sexual orientation sexual and other reproductive health decisions genetic disorder genetic predisposition carrier status military status familial status or domestic violence victim status and any other basis protected under federal state or local laws.

Required Experience:

Senior IC