Lead ML Platform Engineer
New York City, NY - Hybrid (3 days per week onsite)
$200,000 - $220,000 Base Salary+ Bonus + RSU package available
THE COMPANY
We are partnering with a leading consumer technology and financial services organization that operates at global scale and serves hundreds of millions of users. The business leverages advanced data, machine learning, and real-time decisioning systems to deliver highly personalized customer experiences across a broad portfolio of digital products.
This is an exciting opportunity to join a rapidly expanding machine learning engineering team at a pivotal stage of growth. The organization is investing heavily in recommendation systems, real-time personalization, machine learning platforms, and next-generation AI capabilities, offering engineers the opportunity to work with large-scale distributed systems and production-grade ML infrastructure.
RESPONSIBILITIES
- Design, build, and maintain scalable infrastructure supporting machine learning training, deployment, and inference workloads.
- Develop and optimize backend services, microservices, and cloud-native applications that power real-time machine learning systems.
- Own and enhance ML platform capabilities across cloud infrastructure, model serving, monitoring, and operational tooling.
- Partner closely with Data Scientists to productionize machine learning models and support real-time recommendation and personalization use cases.
- Improve CI/CD pipelines, infrastructure-as-code frameworks, observability, reliability, and system scalability.
- Participate in operational ownership, incident response, and support for critical production services.
SKILLS AND EXPERIENCE
Must-Have
- 7+ years of software engineering or machine learning engineering experience.
- Strong backend engineering expertise with experience building distributed systems at scale.
- Proven experience developing Scala-based microservices and production-grade backend applications.
- Deep knowledge of AWS cloud services, including machine learning infrastructure and managed platforms.
- Hands-on experience with Kubernetes, Docker, Terraform, and modern CI/CD practices.
- Strong Python programming skills.
- Track record of owning production systems, reliability, monitoring, and operational excellence.
Nice-to-Have
- Experience with machine learning infrastructure, MLOps, or model-serving platforms.
- Knowledge of recommendation systems, personalization engines, or CTR optimization.
- Experience with Datadog observability and monitoring.
- Background in adtech, fintech, e-commerce, or other high-scale consumer platforms.
- Exposure to real-time machine learning applications and online inference systems.
BENEFITS
- Competitive base salary and annual bonus
- Equity participation through RSUs
- Hybrid working model
- Opportunity to work on cutting-edge AI and machine learning initiatives
- Significant career growth and technical leadership opportunities
- Exposure to large-scale, real-time production systems
HOW TO APPLY
Please register your interest by submitting your CV via the Apply link on this page.
KEY TERMS
Lead Machine Learning Engineer | Machine Learning Engineering | Platform Engineer | ML Infrastructure | Scala | Python | AWS | SageMaker | Kubernetes | Docker | Terraform | CI/CD | Distributed Systems | Recommendation Systems | Real-Time Systems | MLOps | Backend Engineering | Cloud Infrastructure | Platform Engineering | Datadog | Fintech | Personalization | ML Platform | Software Engineering | Hybrid NYC | Technical Leadership